Wireless Infrastructure less networks consist of wireless mobile nodes with
heterogeneous and constrained resources, to establish internet connectivity regardless of the
location. The applications the networks are disaster relief, health care and military. These
applications are sensitive, and demands the reliable, and best quality of communication.
Routing is one of the resources to enable the communication. Routing is acceptable in an
infrastructure less networks if it satisfies the quality of service requirements. Thus the paper
aims to investigate the existing QoS routing protocol performance in various conditions. The
aim is to achieve a broad understanding of QoS routing protocol designed for Wireless
Infrastructure less networks, and further pave the pathway for future research. The paper
analyses the QoS routing protocol performance in presence of bottleneck intermediate node,
and it is the novel aspect of the work.

Mobile Ad Hoc Network (MANETs) is a wireless infrastructure less network consist of mobile
nodes distributed in radio communication area. The network allows its users to free to move i.e.,
enter anytime as well as leave the network anytime. Characteristics of network are cost effective,
time effective, and self-forming. Application of network are military communication, disaster
relief, and medical. Thus, communication information is very sensitive, and suitable protocol is
needed to enable effective communication. One of the approaches to solve the effective
communication is clustering. In this paper we propose a clustering in MANETs based on the
current-status. The proposed work performance is evaluated with NS2 simulator, and results are
compared with existing cluster-based mechanisms. The results show that the proposed work
performance is good in terms of packet delivery, energy awareness, and delay.

Mobile ad hoc networks as an infrastructure free, and constrained resource environment network. The network aim is to establish internet connectivity everywhere regardless of location. The applications of network are healthcare,
disaster relief and military, where reliable communication is major concern. Communication in the network is initiated by establishing the communication route between source and destination and sending the information through it. One of the characteristics of MANETs is a peer-to-peer network, where intermediate nodes have to cooperate for reliable communication by acting as routers. In literature number of routing protocols have been designed based on the MANET’s peer to peer characteristic. However, it may not be every time true that the intermediate nodes act as faithful routers, and they may untrustworthy either due to malicious behavior or bottleneck. Number of secure protocols have been designed to mitigate malicious behavior by neglecting the bottleneck. The paper aims to define the bottleneck, and its importance in communication. Finally, how bottleneck influence on the MANETs performance during malicious nodes mitigation

The outbreak of COVID-19 put the whole world in an unprecedentedly harsh situation, horribly disrupting life around the world and killing thousands. COVID-19 remains a real threat to the public health system as it spreads to 212 countries and territories and the number of cases of infection and deaths increases to 5,212,172 and 334,915 (as of May 22, 2020). This treatise provides a response to virus eradication via artificial intelligence (AI). Several deep learning (DL) methods have been described to achieve this goal, including GAN (Generative Adversarial Network), ELM (Extreme Learning Machine), and LSTM (Long / Short Term Memory). It describes an integrated bioinformatics approach that combines various aspects of information from a series of orthopedic and unstructured data sources to form a user-friendly platform for physicians and researchers. A major advantage of these AI-powered platforms is to facilitate the diagnosis and treatment process of the COVID-19 disease. The latest relevant publications and medical reports have been investigated to select inputs and targets for networks that will facilitate arriving at reliable artificial neural network-based tools for COVID-19-related challenges. There are also several specific inputs per platform, including clinical data and data in various formats, such as medical images, which can improve the performance of the introduced
method for the best response in real application.

Mobile ad-hoc network tools are blueprints to set up internet access anywhere and anytime, describes by not having infrastructure, nodes in a system free to portable and categorized themselves in an critic advance, Communication may have additional than one link and diverse radio, can operate in a stand-alone mode. Due to its distinguishing, it needs an proficient dynamic routing protocol in terms of energy as well as refuge due to its characteristic.We propose a “sheltered energy aware routing against black hole attack”. It improves the life time of arrangement and shield from black hole attack. It considers the node’s power reduction ratio with esteem to current energy & traffic circumstances for -energy awareness, and loose mode for -securing against black hole attack. The results produced by replication have shown that this work is better than existing MBCR and MRPC interns of network lifetime and sheltered interns of black hole attack using NS2.

Routing protocols developed in MANET by assumption that the nodes in the network are supportive, as
the network is infrastructure less. But this consideration of routing protocols is always not trustworthy.
The nodes do not supportive all the time and they act as misbehaving nodes by not following the routing
protocols specifications. One such misbehaving activity is packet dropping from routing path. Various
intrusion detection systems are designed to prevent the packet dropping attack in MANET. These IDS
must consider the energy awareness during the intrusion detection otherwise performance of MANET
greatly influenced. Through simulation work concluded that the IDS must incorporate with energy
awareness of the nodes

Mobile ad hoc networks is wireless infrastructure free networks. It consists of heterogeneous mobile nodes. These nodes are distributed in wireless communication area. The characteristics of the network are adaptation, autonomous and self-formation and distributed peer to peer network. Applications of the network are military, health care and disaster recovery. Characteristics and applications of MANET demands reliable efficient communication. Multi hop communication is enabling in the network by cooperation of the intermediate nodes. The intermediate nodes drop the packets due to either system fault or malicious behavior. Different way of packets drop due to system fault is recognized and isolated from malicious packet dropping nodes during the communication in existing ―secure knowledge algorithm‖. However, it does not prevent the packet drop due to system fault in the network and it is very essential to enhance the performance and reliability of the communication. Thus the paper design ―Efficient Intrusion Detection System to Avoid the Packet Dropping Nodes from Communication Route‖. Performance of the proposed IDS is tested in the simulator NS-2 and compares the results with existing work. Results are clearly indicating that the proposed IDS out perform in comparison with existing work in terms of reliability and packet delivery.

The underlying element that supports the device communication in the MANET is the wireless connection capability. Each node has the ability to communicate with other nodes via the creation of routing path. However, due to the fact that nodes in MANET are autonomous and the routing paths created are only based on current condition of the network, some of the paths are extremely instable. In light of these shortcomings, many research works emphasizes on the improvement of routing path algorithm. Regardless of the application the MANET can support, the MANET possesses unique characteristics, which enables mobile nodes to form dynamic communication irrespective the availability of a fixed network. However the inherent nature of MANET has led to nodes in MANET to be vulnerable to denied services. A typical Denial of Service (DoS) in MANET is the Black Hole attack, caused by a malicious node, or a set of nodes advertising false routing updates. Typically, the malicious nodes are difficult to be detected. Each node is equipped with a particular type of routing protocol and voluntarily participates in relaying the packets. However, some nodes may not be genuine and has been tampered to behave maliciously, which causes the Black Hole attack. Several on demand routing protocol e.g. Ad hoc On Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) are susceptible to such attack. In principle, the attack exploits the Route Request (RREQ) discovery operation and falsifies the sequence number and the shortest path information. The malicious nodes are able to utilize the loophole in the RREQ discovery process due to the absence of validation process. As a result, genuine RREQ packets are exploited and erroneously relayed to a false node(s). This paper highlights the effect Black Hole nodes to the network performance and therefore substantiates the previous work done [1]. In this paper, several simulation experiments are iterated using NS-2, which employed various scenarios and traffic loads. The simulation results show the presence of Black Hole nodes in a network can substantially affects the packet delivery ratio and throughput by as much as 100%.

The mobile Ad Hoc network (MANET) is a self-organizing and self-configuring wireless network, consisting of a set of mobile nodes. The design of efficient routing protocols for MANET has always been an active area of research. In existing routing algorithms, however, the current work does not scale well enough to ensure route stability when the mobility and distribution of nodes vary with time. In addition, each node in MANET has only limited initial energy, so energy conservation and balance must be taken into account. An efficient routing algorithm should not only be stable but also energy saving and balanced, within the dynamic network environment. To address the above problems, we propose a stable and energy-efficient routing algorithm, based on learning automata (LA) theory for MANET. First, we construct a new node stability measurement model and define an effective energy ratio function. On that basis, we give the node a weighted value, which is used as the iteration parameter for LA. Next, we construct an LA theory-based feedback mechanism for the MANET environment to optimize the selection of available routes and to prove the convergence of our algorithm. The experiments show that our proposed LA-based routing algorithm for MANET achieved the best performance in route survival time, energy consumption, energy balance, and acceptable performance in end-to-end delay and packet delivery ratio.

In business, the Stock market or Share market is a more perplexing and sophisticated way to do business. Every business owner wants to reduce the risk and make an immense profit using an effective way. The bank sector, brokerage corporations, small ownerships, all depends on this very body to earn profit and reduce risks. However, using the machine learning algorithm of this paper to predict the future stock price and shuffle by using subsist algorithms and open source libraries to assist in inventing this unsure format of business to a bit more predictable. The proposed system of this paper works in two methods – Linear Regression and Decision Tree Regression. Two models like Linear Regression and Decision Tree Regression are applied for different sizes of a dataset for revealing the stock price forecast prediction accuracy. Moreover, the authors of this paper have revealed some development that could be the club to acquire better validity in these approaches

In the era of globalization of goods and services difficulties in knowledge diffusion still remain. The effective exchange of experiences and skills is not guaranteed by the enormous potentials of internetworking systems and devices. E-learning technologies represent a good opportunity to reduce the digital divide and to ensure faster and higher development trends. Several universities and companies are currently involved in using e-learning systems to provide a valid solution; this notwithstanding several problems related to e-learning activities still remain open. This paper presents an analysis of the e-learning technologies used in the Italian Universities. The most widespread open source and commercial Learning Management Systems (LMSs) are investigated and presented. Successively, a simple model is proposed and used to perform a comparative evaluation of the adopted systems. Finally, the activity experienced at the “Rete Puglia” Centre of the University of Bari is described and the most relevant results are illustrated.

Even though advanced Machine Learning (ML) techniques have been adopted for DDoS detection, the attack remains a major threat of the Internet. Most of the existing ML-based DDoS detection approaches are under two categories: supervised and unsupervised. Supervised ML approaches for DDoS detection rely on availability of labeled network traffic datasets. Whereas, unsupervised ML approaches detect attacks by analyzing the incoming network traffic. Both approaches are challenged by large amount of network traffic data, low detection accuracy and high false positive rates. In this paper we present an online sequential semi-supervised ML approach for DDoS detection based on network Entropy estimation, Co-clustering, Information Gain Ratio and Exra-Trees algorithm. The unsupervised part of the approach allows to reduce the irrelevant normal traffic data for DDoS detection which allows to reduce false positive rates and increase accuracy. Whereas, the supervised part allows to reduce the false positive rates of the unsupervised part and to accurately classify the DDoS traffic. Various experiments were performed to evaluate the proposed approach using three public datasets namely NSL-KDD, UNB ISCX 12 and UNSW-NB15. An accuracy of 98.23%, 99.88% and 93.71% is achieved for respectively NSL-KDD, UNB ISCX 12 and UNSW-NB15 datasets, with respectively the false positive rates 0.33%, 0.35% and 0.46%.

A Smart Helmet is protective and advanced headgear which not only protects the rider but also provides modern features which helps in concentrate on riding. Systems like Heads up Display (HUD)/Augmented Reality overlay are used to. Superimpose information onto a field of view These systems have the capability to reflect projected digital images as well as allow the user to see through it or see better with it. It may support wireless technologies like Bluetooth, Wi-Fi, and GPS. Few models run a mobile operating system and function as portable media players to send audio and video files to the user via a Bluetooth or Wi-Fi headset. The Smart helmet also protects the driver this can be implemented by using advanced features like accident identification, location tracking, use as a hands-free device, fall detection. In case of an accident, it will send a message through GSM along with location with the help of GPS module. The distinctive utility of project is fall detection; if the rider falls from the bike, it sends a message

The project discuss in this paper is aimed to solve problems of common peoples in day-to-day life. The internet of things (IoT) is connecting the devices and tools to the internet network to be controlled by websites and smart phone applications remotely, also, to control tools and instruments by codes and algorithms structures. With the advancement of technology, the need for efficient controlling is more as it optimizes performance and saves unnecessary wastage of power. A system has been proposed to control home appliances anytime from anywhere in the world and efficiently utilize power by controlling appliances properly. Blynk app is used as third-party application. It provides open source to user make to design automation. Sensors are connected to node MCU ESP8266 controller and can operate from any part of world with help of Blynk app.

Communicating with customers through live chat interfaces has become an increasingly
popular means to provide real-time customer service in different industries. Today, human chat agents
are replaced by virtual chat agents/bots which are designed to communicate with humans by using
Natural Language Processing based on Artificial Intelligence. With the advancement of technology,
these chatbots can be integrated as a VIRTUAL RECEPTIONIST with added features enclosed in an
Android Device at the schools and college premises, enhancing productivity and operational
effectiveness.

The quality management of horticultural agricultural goods in the food and beverage industry is a crucial concern. The main problem is to maintain a consistent cold chain from supplier to customer, and for that it is important to count with adequate tracking, control and assurance schemes, as well as techniques of collection and review of accurate data. At present, FAO reports that one third of the world’s food supply is lost, principally because the measuring systems used do not include truthful details about the state of the goods and under which circumstances they are; control systems do not function properly or are not implemented as rigorously necessary. Therefore, this study discusses the use of modern management strategies and methods for the cold chain, concentrating on the use of tracking systems, particularly in the early analysis of data, and the use of new technology to mitigate the effect of environmental variations on perishable goods.

Cities across the globe are considering transitioning into a smart city concept by implementing big data applications which help them in reaching the requisite level of sustainability and improving the standards of living of people. This paper reviews the applications of big data to smart cities by searching different databases using specific keywords and following a systematic data mining methodology for selecting the desired literature for further review. It identifies the appropriate definition of the smart city and big data and discusses the various opportunities, challenges and benefits of incorporating big data applications for smart cities

A wireless sensor network (WSN) consists of autonomous nodes with sensors to sense and collect the status of the surrounding environment continuously. Characteristics of WSN are infrastructure-less, self-organizing, and fault tolerance. One of the applications of WSN is living and sleeping pattern reorganization in the home environment. Where the sink node is equipped with a sufficient amount of processing and battery capabilities, but sensor nodes are outfitted with the restricted battery as well as processing capabilities. The sensed information is transmitted to the sink node in a single or multi-hop communication manner. The energy depletion of any sensor node directly affects the sensing coverage and thereby on the network performance. Particularly the sensor node that is neighbour to the sink node faces the extra overload and drops the information due to insufficient buffer. Moreover, the neighbour of sink node exhaust soon due to the energy depletion. Thus the placing the sink node in a suitable position in WSN is a quite vital design issue, as the performance of the WSN is greatly affected by the proper placement of the sink node. The paper designs an efficient mechanism for deploying the sink node to a suitable position. The deployment is based on the sensor node’s residual buffer and energy status. The performance of the proposed mechanism is evaluated by a network simulator and compared the results with recent existing mechanisms in an identical environment. The performance results indicate that the proposed work enhances the network lifetime and energy efficiency in WSN. Finally, it prevents packet drops in WSN by avoiding the nodes becoming the bottleneck.

This paper tends to examine the current state of educational system with the subject of robotics, also to identify the emerging challenges, and trends, and focuses on the use of robotics as a tool to support creativity and 21st century learning skills. Finally, conclusions and recommendations are provided to encourage collaboration and networking among researchers and educators in India to support the advancement of robotics in education.

The research and communications for detecting mobile security threats with the best protection practices of applications have become essential goals nowadays due to the continuous discoveries of new vulnerabilities. The internet and web-based activities have been increased drastically in recent times by users of all categories. Users have extensively started involved in gaming, banking, frequent bill payment, entertainment, and other network and online activities that are requiring a large number of mobile phone protection and security mechanisms in response to advancements in full-stack applications and wireless networks. The goal of this paper is to uncover the best-applied practices in the domain of mobile security to protect smartphone devices. The main advantages of smartphones are small size with easiness in carrying anywhere and can be a replacement for computing devices in some ways for example emails. Unfortunately, the convenience of using smartphones to do the private task is the loophole cyber attackers need to gain access to personal data. Thus, this paper proposed eight best practices to protect and secure smart mobile phones.

Outsourcing data to a third-party administrative control, as is done in cloud computing, gives rise to security concerns. The data compromise may occur due to attacks by other users and nodes within the cloud. Therefore, high security measures are required to protect data within the cloud. However, the employed security strategy must also take into account the optimization of the data retrieval time. In this paper, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) that collectively approaches the security and performance issues. In the DROPS methodology, we divide a file into fragments, and replicate the fragmented data over the cloud nodes. Each of the nodes stores only a single fragment of a particular data file that ensures that even in case of a successful attack, no meaningful information is revealed to the attacker. Moreover, the nodes storing the fragments, are separated with certain distance by means of graph T-coloring to prohibit an attacker of guessing the locations of the fragments. Furthermore, the DROPS methodology does not rely on the traditional cryptographic techniques for the data security; thereby relieving the system of computationally expensive methodologies. We show that the probability to locate and compromise all of the nodes storing the fragments of a single file is extremely low. We also compare the performance of the DROPS methodology with ten other schemes. The higher level of security with slight performance overhead was observed.

Wireless ad hoc network system is a foundation less multi-hop system of versatile remote hubs with
heterogamous assets. The attributes of WANETs are adjustment, self-shaping and shared systems administration.
The transmission of data is happen legitimately if the conveying hubs present in the radio scope of each other
generally the correspondence is hand-off on the transitional hubs. The utilization of WANETs and qualities of
WANETs requests the safe and productive correspondence. Anyway the correspondence of WANETs is powerless,
and endures because of a few malicious activities in various layers. One of the system layer malicious activity is a
dark opening malicious activity. The point of Malicious activity is to intrude on the correspondence session. The
dark opening Malicious activity play out the disavowal of administration sort of thing. So as to dispatch the
malicious activity it draws in the correspondence traffic towards it by sending the productive course replay parcel
towards the imparting hub. Later the assailant hub essentially drops the parcels that are send by the imparting hub. In this work we examine the exhibition debasement of the correspondence in the WANETs because of the nearness of dark ole hub in the correspondence way. We have done the precise presentation investigation of the WANETs
correspondence within the sight of the assailant hub. One of the explanation behind the starting malicious activity by
dark opening hub in WNAETs condition is because of spare and safeguard its assets. The major compelled asset in
WANETs is control, as the utilization of WANETs is at military side, where we couldn’t ready to revive or supplant
the battery of the hub. Along these lines in this work we process the presentation debasement of the WANET
correspondence regarding the vitality within the sight of assailant hub. Execution results are figured with Network
Simulator 2. The outcomes are pay the way for future research to structure the protected vitality productive
correspondence in WANETs.

Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage.
In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keyword search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS-PEKS). As another main contribution, we define a new variant of the smooth projective hash functions (SPHFs) referred to as linear and homomorphic SPHF (LH-SPHF). We then show a generic construction of secure DS-PEKS from LH-SPHF. To illustrate the feasibility of our new framework, we provide an efficient instantiation of the general framework from a Decision Diffie– Hellman-based LH-SPHF and show that it can achieve the strong security against inside the KGA.

After the 2020 pandemic, everyone realized that the collaborations which were being done offline had to go online. This created a stir among the community as there was no legal bond between the two entities working together. Be it a large company working for another one or an individual working as a contractor. Smart contracts are computer protocols intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract. Smart contracts have a broad range of applications, such as financial services, prediction markets, and Internet of Things (IoT), etc. In this paper, we propose how we use blockchain technology and utilize the built-in feature of the blockchain technology called smart contracts to create an agreement between two entities which is then automatically executed/initiated whenever the conditions or the requirements of the contract are met. This makes everything transparent between the contractors which in turn eliminates the need for a third person to testify or the need of depending and trusting the contractor or anyone. This also creates micro-collaborations much easier as it saves time and money spent behind a lawyer to register a company for a trivial collaboration. Smart contracts can be made based on the requirements. This is a decentralized application built using react and solidity

The evolution of technology especially in the Cloud industry has generated a big shift from the traditional way in terms of the use of the IT resources and has also become increasingly important in our day to day lives. With advanced technology the risk of cyber-attacks to IT resources has also become a major concern. To prevent which, many types of scans such as static scans, dynamic scans, or firewall scans are used by companies to keep their resources/ data secure. With the evolution of Big Data, it has become more vulnerable to attacks than before. This study is an effort to analyze the effect of an application response time, when the application is hosted on a cloud and it is exposed to security scans, whose nature can be dynamic/static scan or even firewall scans. We study this performance issue by the measure of the response time, and it is done by the means of Delta time which is associated with the TCP/IP 3-way handshake data. The real-time data of a user application is collected which is hosted on a Google® cloud, whose Delta times are analyzed using statistical methods, such as mean, skewness, etc. yielding no definitive answer. Further by analyzing using ToH and ANOVA tests however resulted in showing a difference in Delta times when the application was exposed to full scans. This is in depth analyzed using various clustering techniques, namely K-Means and Hierarchical Clustering techniques. A comparison between which, resulted in the discovery of the outliers. These are then removed and the results are computed showing a change in the response times, prior and post the outlier removal. Based on the tests conducted, we found that there is not a significant difference in running dynamic or static scans on the application or the data and its impact is not statistically significant to the performance, and while the K-Means Clustering technique is sensitive to outliers, the hierarchical technique validates the choices of clusters and gives information regarding outliers

Smart contracts are simply programs stored on a blockchain that run when predetermined conditions are met. They typically are used to automate the execution of an agreement so that all participants can be immediately certain of the outcome, without any intermediary’s involvement or time loss. They can also automate a workflow, triggering the next action when conditions are met. After the 2020 pandemic, everyone realized that the collaborations which were being done offline had to go online. This created a stir among the community as there was no legal bond between the two entities working together. Be it a large company working for another one or an individual working as a contractor. Smart contracts are computer protocols intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract. Smart contracts have a broad range of applications, such as financial services, prediction markets, and Internet of Things (IoT), etc. In this paper, we propose how we use blockchain technology and utilize the built-in feature of the blockchain technology called smart contracts to create an agreement between two entities which is then automatically executed/initiated whenever the conditions or the requirements of the contract are met. This makes everything transparent between the contractors which in turn eliminates the need for a third person to testify or the need of depending and trusting the contractor or anyone. This also creates micro-collaborations much easier as it saves time and money spent behind a lawyer to register a company for a trivial collaboration. Smart contracts can be made based on the requirements. This is a decentralized application built using react and solidity

Online social networks are becoming more and more prevalent in people’s life, but they face the problem of privacy leakage due to the centralized data management mechanism. Evolvement of blockchain technology has greatly changed the network and it makes many applications to be distributed, decentralized without loss of security. Ethereum is an open-source blockchain platform that provides a runtime environment for running smart contracts, which is called Ethereum Virtual Machine (EVM). Ethereum-based applications are usually referred to as Decentralized Applications (DApps), since they are based on the decentralized EVM, and its smart contracts. By combining smart contracts, we use the blockchain as a trusted server to provide central control services. Blockchain helps us incentivise users of the platform with cryptocurrency as a reward for moderation. This is a decentralised application based on Ethereum blockchain built using solidity and react. In this paper, we examine how blockchain and incentivisation can enable more functionalities of traditional social network systems

To avoid fraudulent post for job in the internet, an automated tool using machine learning based classification techniques is proposed in the paper. Different classifiers are used for checking fraudulent post in the web and the results of those classifiers are compared for identifying the best employment scam detection model. It helps in detecting fake job posts from an enormous number of posts. Two major types of classifiers, such as single classifier and ensemble classifiers are considered for fraudulent job posts detection. However, experimental results indicate that ensemble classifiers are the best classification to detect scams over the single classifiers

Humanoid robotics is an emerging research field that has received significant attention during the past years and will continue to play an important role in robotics research and many applications of the 21st century and beyond. In this rapid moving world, there is a need of robot such a “A Human Following Robot” that can interact and co-exist with them. Because of its human following capability, these robots can work as assistants for humans in various situations and it can also acquire or monitor certain information associated with the human subject. In this paper we present a prototype that uses Arduino Uno along with basic sensors such as ultrasonic and IR sensor. All the processing is carried out by the microprocessor while the control of the motors is carried out by the controller. This robot can further be modified by using many technologies such as Bluetooth, PixyCamera etc.

Distributed computing gives another method for administration by offering different assets over Internet. One of the essential administrations given by cloud benefit is information stockpiling. So as to save the protection of clients, these information are put away in cloud in a scrambled shape. Deduplication ends up critical and a testing errand when the information is put away in scrambled shape, which additionally prompts intricacy in putting away extensive information and handling in cloud. A customary deduplication strategy does not take a shot at scrambled information. Existing arrangements accessible for deduplicating encoded information has different security issues. They doesn’t give get to control and repudiation as far as capacity. Thus, the deduplication plans are not for the most part conveyed practically speaking. In this paper, we propose a system to deduplicate encoded information put away in cloud dependent on access control along these lines evading repetitive capacity. It coordinates cloud information deduplication with access control. The aftereffect of our plan demonstrates prevalent proficiency and has potential for functional arrangement on account of enormous information stockpiling

The project aims to represent a prototype of a monocular vision self-driving car model using latest technology of
OpenCV2 and Machine Learning. Self-driving cars are autonomous vehicles that would minimize human intervention thereby minimizing the risk of accidents and make transportation safer, comfortable and that which can be done anytime. The car model will be able to detect the lane path, sign boards, traffic light signals and respond to real time traffic. Raspberry Pi is the central processing unit used along with peripheral devices such as Arduino Uno, L298 H-Bridge and the raspi Cam2 to bring about the desired control needed for our car. Algorithms like Lane Detection, Object Detection, Canny Edge Detection, Harr Cascade Classifier are amalgamated with Computer Vision to provide the necessary functionalities in the car.

With the development of artificial intelligence (AI), the automatic analysis of video interviews to recognize individual personality traits has become an active area of research and has applications in personality computing, human[1]computer interaction, and psychological assessment. Advances in computer vision and pattern recognition based on deep learning (DL) techniques have led to the establishment of convolutional neural network (CNN) models that can successfully recognize human nonverbal cues and attribute their personality traits with the use of a camera. In this study, an end-to-end AI interviewing system was developed using asynchronous video interview (AVI) processing and a TensorFlow AI engine to perform automatic personality recognition (APR) based on the features extracted from the AVIs and the true personality scores from the facial expressions and self-reported questionnaires of 120 real job applicants. The experimental results show that our AI-based interview agent can successfully recognize the “big five” traits of an interviewee at an accuracy between 90.9% and 97.4%. Our experiment also indicates that although the machine learning was conducted without large[1]scale data, the semisupervised DL approach performed surprisingly well with regard to automatic personality recognition despite the lack of labor-intensive manual annotation and labeling. The AI-based interview agent can supplement or replace existing self-reported personality assessment methods that job applicants may distort to achieve socially desirable effects.

Start-up companies use a variety of SaaS products to automate things and get the job done which is required by the consumers. SaaS products types of software that are hosted by a central provider and offered to customers through the internet. Rather than installing or downloading a copy of the application, users can access the product from a web or mobile browser. The SaaS company then manages and updates the software based on user needs. Often, they come across options for softwares which offers the same services yet have many differences. It takes alot of effort to decide which service suits the purpose well and is accustomed to the particular needs of the projects, thus it is a hard job to decide which product is best according to the company’s various needs and fits best accordingly. As it is a time consuming task for the companies to filter out the existing services we are going to minimize the time complexity of this task by bringing all the Saas Products to a single platform where the users can compare the services, products etc and use the services that serve their purpose optimally. In our work, we use twitter data to analyze public views towards a product. Firstly, we have developed a natural language processing (NLP) based pre[1]processed data framework to filter tweets. Secondly, we incorporate Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF) model concept to analyze sentiment. This is an initiative to use BoW and TFIDF are used together to precisely classify positive and negative tweets. We have found that by exploiting TF-IDF vectorizer, the accuracy of sentiment analysis can be substantially improved and simulation results show the efficiency of our proposed system. We achieved 85.25% accuracy in sentiment analysis using NLP technique

Block chain technology has been seeing widespread interest as a means to ensure the integrity, confidentiality and
availability of data in a trustless environment. They are designed to protect data from both internal and external
cyber attacks by utilizing the aggregated power of the network to resist malicious efforts. In this article, we will
create our own decentralized messaging application utilizing the Ethereal Whisper protocol. Our application will be
able to send encrypted messages both securely and anonymously. We will utilize the ethereal platform to deploy our
block chain network. This application would be resistant to most suppression tactics due to its distributed nature and Adaptability of its communication protoco

With the introduction of biometrics technology which is an advanced computer technique now
widely adopted as a front line security measure for both identity verification and crime detection,
and also others an effective crime deterrent. In an increasingly digital world, reliable personal
authentication has become an important human computer interface activity. Fingerprint
recognition could be very complex pattern recognition problem. It is difficult to design accurate
algorithms that are capable of extracting prolific features and comparing them in a robust way,
especially in poor quality fingerprint images and when low-cost acquisition devices with small
area are adopted. There is a greatest misconception that the fingerprint recognition is a fully
solved problem considering it was one of the first applications of all amongst machine pattern
recognition. A fingerprint is the feature pattern on the finger. It is proved through strong
evidences that each fingerprint is almost unique in nature. Each individual retains his own
fingerprints with the permanent and durable uniqueness. Hence fingerprints are being adapted for
identification and forensic investigation. The fingerprint recognition problem can be grouped
into two sub-categories: one is termed as fingerprint verification and while the other is termed as
fingerprint identification. Additionally, apart from the manual approach of fingerprint
recognition by the experts, fingerprint recognition here is usually referred as AFRS (Automatic
Fingerprint Recognition System), which is drastically program-based. The proposed system
presents the variation of Fast Fourier Transform on finger print recognition by fast fingerprint
minutiae extraction and recognition algorithm that improves the clarity between the ridge and
valley structures of the supposed to be provided finger print images in accordance with the
frequency as well as the orientation of the local ridges and extracting correct minutiae.

Cloud computing has grown to become an integral part of present as well as future information technologies. This technology has been designed to be used with internet by providing features such as information storage, remote access, etc. Cloud computing has been proved as an effective tool for all the provided services but it also comes with various types of threats. Over the years of its development, different fire attacks and data theft has been reported as a crucial factor since the data stored in the cloud by an organization or an individual user is basically confidential and sensitive. These data are illegally accessed by many hackers and further it will be used to fire attack the user. This paper mainly aims to highlight such attacks and provide suggestions for sorting the data breaching issues.

In the age of modernization, A Parent’s life undergoes various changes due to child monitoring. Our project focuses on the relevant problems faced by parent in monitoring and nurturing their child while working. This project aims at reducing the challenges faced by parent by developing an IOT based Smart Cradle monitoring System that will assist Parent in monitoring their child. This cradle is equipped with a swinging mechanism which swings automatically on detection of baby crying sound. This proposed smart cradle has been integrated with a camera to provide continuous surveillance to parents. An Arduino, sound sensors, wetness sensor, swinging mechanism along with other electronic components are used to upgrade existing cradle to meet the Present-day requirements. This project is quite efficient and reliable which can deliver result better than conventional cradle.

Artificial intelligence has had a significant impact on how people live their lives in a novel and unusual way and One of these advances is the Voice Based Assistant. Similarly, like a “chatbot” which takes the users command analyses it and return the corresponding action or task given by the user in the form of a text command. A chatbot can be described as software that communicates with people using Artificial Intelligence. Voice based Assistant is a Laptop and Desktop software which can perform an Individual user’s tasks or Services according to the instruction/command given by the user. But it communicates with the user with Voice as the input and responds with the corresponding action/Task with voice over of the action being performed. Everything in the twenty-first century is automated, including items we use every day like browsing YouTube, sending messages, creating files, fetching information, and opening applications of a pc with a single click using Voice based Assistant all of these can be controlled via the voice of the user without even need to go and physically doing the task or manually doing certain task. The three steps that make up the process are pre-processing, categorization, and feature extraction. Desktop voice assistants are applications that understand and react to human voices using integrated voice systems with the appropriate reaction or task execution.

A series of connected eye conditions known as glaucoma harm the optic nerve, which transmits information from the eye to the brain, and can eventually result in blindness. For proper treatment, it is crucial that glaucoma is identified as soon as possible. A Convolutional Neural Network (CNN) approach for the early identification of Glaucoma is suggested in this research. To start, augmented ocular pictures are used to produce data for deep learning. The ocular pictures are then pre-processed using the Gaussian Blur technique to reduce noise and prepare the image for additional processing. When new input images are provided to the system, it classifies them as either normal eyes or glaucoma eyes based on the features collected during training. The system is trained using the pre-processed images.

Driver fatigue is one of the major causes of collisions and incidents globally. Identifying the driver’s fatigue is one of the most dependable ways to assess their level of exhaustion. The creation of a functional prototype for a drowsiness detection method is the aim of this work. This gadget watches a driver’s face and triggers an alarm if it detects signs of fatigue. The application is a superb, unobtrusive tracking system. The goal is to enhance the driver’s comfort without becoming overbearing. This study records the eye blink of the driver. An alert is triggered and the driver is deemed sleepy if their eyes remain shut for an endless period of time. OpenCV is currently configured to recognize face traits was used to the model for facial location detection.

One of the most fundamental tasks in computer vision for autonomous driving is lane lines detection on road. Lane lines are painted for humans to see and follow while driving. In a very similar way, an autonomous vehicle that uses human designed infrastructure, needs to see the lane markings to steer accordingly and follow the road trajectory. In this project I implemented a computer vision algorithm that processes real data recorded with the front facing camera of a vehicle driving on a California highway. The result is a processed video that highlights the lane lines on the paved road. With the positions of the lane lines identified, the vehicle’s offset from the lane’s center can be calculated and feed a PD controller to compute the necessary steering angle. While only the lane lines detection is the scope. Then we create a function called draw line (the dram line method’s purpose is to draw lines or lines). The Hough line transform method is used to detect lanes or lanes from the replacement image in polygon images. The detected line or lanes are then drawn. Finally, when the lines are drawn, we blend the previous image.

This paper presents an automated smart car parking system that utilizes IR sensors to detect vehicles and provide feedback on available parking spaces in complex multi-storeyed parking structures. The system is designed to navigate drivers to the nearest available parking space using visual aids, effectively reducing search time. This cost-effective system is ideal for use in malls, IT hubs, and other parking facilities, and eliminates the need for expensive equipment and complex lines of code. The paper provides an overview of the system, including its functional and non-functional requirements, tools, and technologies used for prototype development and deployment. The system also includes a web-based application that allows users to reserve a parking space in advance. Field testing and demonstration results are discussed, highlighting the system’s effectiveness in managing parking spaces and reducing labour requirements. The system’s development and deployment offer valuable insights into creating a smart parking system that can enhance the overall user experience in a range of parking facilities. In summary, the automated smart car parking system presented in this paper provides an efficient and effective solution for managing parking spaces in multi-storeyed parking structures, thereby reducing search time and improving the overall user experience.

A system for automatic detection and characterization of cracks in road flexible pavement surfaces is proposed. It does not require manually labeled samples to minimize human subjectivity. Crack detection is based on unsupervised training of a learning from samples paradigm using a subset of the image database. The system classifies image blocks as containing crack pixels or not. Crack type characterization is accomplished by constructing another classification system to label cracks according to types defined in the Portuguese Distress Catalog. A novel methodology for assigning crack severity levels is introduced. The system’s experimental results are based on images captured during a visual road pavement surface survey over Indian roads. The results show promise, and a quantitative evaluation methodology is introduced, including a comparison with human experts’ manual labeling results. To evaluate the performance of our method, we use various metrics such as precision, recall, and F1-score. We compare our results with manual inspection and other traditional methods to assess the effectiveness of our deep learning-based approach.

The aim of this project is to develop a Chrome extension that can detect crypto-jacking attempts in real-time and block the websites containing such attempts. Crypto-jacking is the unauthorized use of someone’s computing resources to mine cryptocurrencies. This type of attack can go undetected for long periods and cause damage to the user’s device, such as overheating and reduced battery life. To detect crypto-jacking, the extension will use the blacklisting-based approach combined with a resources monitoring approach. This approach uses a blacklist of known crypto-jacking scripts and domains frequently associated with crypto-jacking. If the extension detects any of these scripts or domains on a website, it will block the website from opening in the first place. This approach prevents crypto-jacking attempts by blocking websites with known crypto-jacking codes.

Overall, this project is crucial to protect users from the increasing prevalence of crypto-jacking attacks. By blocking known crypto-jacking websites, the extension will prevent attackers from using the user’s computing resources for their gain.

Mobile ad-hoc network technology is developed to establish the internet connectivity regardless of geographical location all the time. It is an infrastructure less network and allows the nodes to move freely and organize in an arbitral manner. Nodes in a network are autonomous, self-organize and act in a peer to peer fashion. MANET needs an effective dynamic routing protocol to achieve efficient communication. The paper analyzes the performance of various reactive routing protocols designed for MANET. The aim is to achieve a broad understanding of reactive routing protocols developed for MANET and Pave the path for future research. The paper evaluates the performance with respect to different scenarios, and analyzes the results with different performance metrics. The analysis shows the systematic evaluation of reactive routing protocols performance in terms of dynamic and static topology with multi hop communication, and variable data rates.

Routing is the process to establish the communication path between
communicating entities to enable communication in any networking model by
forwarding the information in terms of packets. MANET is wireless
infrastructure free peer to peer network. Routing in MANET is establish based
on consideration that the nodes are cooperative. Malicious nodes do not
cooperate for communication activities such as they drop the packets. In order
to prevent malicious routing activities various intrusion detection and
prevention systems designed for MANET. The main objective of these systems
is to identify the malicious activities of the nodes by their packet operations. If
node drops the packet more than the predefined value than it considered as
malicious. But in MANET, reputed nodes also drops the packets if itbecomes
bottleneck intermediate node. Thus the work aims to examine the IDS
performance in the presence of bottleneck intermediate node. Further, the work
shows the importance of considering bottleneck intermediate nodeduring the
design of novel IDS.

The mobility for communication devices has generated the requirement of next generation wireless network technology development, several type of wireless technologies have been developed and implemented, one of them is ad hoc mobile network system which facilitates to a cluster of mobile terminals which are animatedly and randomly changing locations in such a way that the interconnections need to be handled continually. A routing procedure is used to find the routes between the mobile terminals in the set of connections for easy and reliable communication; main purpose of this protocol is to find a proper route from caller to called terminals with minimum of overhead and bandwidth consumption during construction of route. This paper provides an impression of a broad range of routing protocols projected in the literature and has in addition provided a piece comparison of all routing protocols with discussion of their respective merits and drawbacks.

The coping, modifying a block of code is identified as cloning and is the most basic means of software reuse. It has been extensively used within the software development community. An official survey which is carried out within
large, long term software development project suggested that 25-30% of modules in system may be cloned. This paper begins with background concept of code cloning, presents overcall taxonomy of current techniques and tools, and classify evolution tools in two different format as static code clone and dynamic code cloning, this together presented with program analysis, secondly as a solution the static code is divided into four parts as T1, T2, T3, T4, to finally develop a process to detect and remove code cloning

Software development is a knowledge-intensive work and the main attention is how to manage it. The systematic reviews of empirical studies presents, how knowledge management is used in software engineering and development work. This paper presents how knowledge is used in agile software development and how knowledge is transferred to agile software using agile manifesto. It then argues for the need to scale agile development strategies in knowledge management to address the full delivery. The paper explores the eight agile software scaling factors with knowledge management and their implication for successfully scaling of agile software delivery to meet the real world needs of software development organization

Software is critical assets for modern enterprises and incorporates key knowledge over the life of an organization. Although this software must be update continuously to reflect evolving business practices, repeated modification has cumulative effect on system complexity and too fragile to modify and too important to discard. However  organization must consider modernizing this software to remain viable. Many approaches used to analyze legacy code, unfortunately, as the legacy code tend to grow over time, many unrelated field come at the time of migration. This paper presents how different techniques used to identify object in legacy code by using the concept of functions, modules and metrics. The methodology uses measurement of change to benefits the system development process and to generate insights about software evolution

The availability of computer-aided systems-engineering environments has redefined the organization system development. Pace of change accelerates in the twenty-first century as a result of technological opportunities, liberalization of the world markets, demands for innovation and continually decreasing life cycle of software. Organizations have to continuously re-adjust and re-align their operation to meet all these challenges. This pace of changes has increasingly forced organization to be more outward looking, market-oriented and knowledge driven. This paper present integrated framework of how reverse engineering process work goes in Enterprise Information System(EIS).The essential functions in reverse engineering, how they are associated with EIS, what will be the impact on the organization which is using reverse engineering

Hacking has become an extensive trouble with the beginning of the digital age, almost worldwide access to the internet and other digital media. It is significant for individuals, corporations, and the government to guard them from being susceptible to such attacks. The purpose of this paper is to provide information about ethical hacking; their skill to share advanced security knowledge and capabilities with organization and pointing out their vulnerabilities.

Mobile ad-hoc network tools are blueprints to set up internet access anywhere and anytime, describes by not having infrastructure, nodes in a system free to portable and categorized themselves in an critic advance, Communication may have additional than one link and diverse radio, can operate in a stand-alone mode. Due to its distinguishing, it needs an proficient dynamic routing protocol in terms of energy as well as refuge due to its characteristic.We propose a “sheltered energy aware routing against black hole attack”. It improves the life time of arrangement and shield from black hole attack. It considers the node’s power reduction ratio with esteem to current energy & traffic circumstances for -energy awareness, and loose mode for -securing against black hole attack. The results produced by replication have shown that this work is better than existing MBCR and MRPC interns of network lifetime and sheltered interns of black hole attack using NS2.

MANETs (Mobile Ad-hoc networks) are a group of self-forming and self-healing mobile hosts communicating with each other, which do not require central authority or fixed infrastructure. MANETs are mobile and heterogeneous networks. Due to their mobility and heterogeneity, they are more vulnerable to attacks. Grey hole attack is an attack, in which all the packets in a network are forwarded to the attacker node by neighbour nodes and are intentionally dropped. In this work, we proposed a secure data protocol which intends to identify and avert the grey hole attacks by considering the causes of packet drop in promiscuous mode. We improved an existing AODV based routing protocol for detection and prevention of grey hole attacks. The results of this experiments show that MANETs are secure against grey hole attacks with our proposed algorithm with AODV based routing protocol.

As opposed to the present authenticated structures, for example skip list and Merkle tree, we design a singular authenticated structure known as Homomorphic Authenticated Tree, we present additional information about PoS and dynamic PoS. Whenever a verifier wants to determine the integrity of the file, it at random selects some block indexes from the file, and transmits these to the cloud server. To the very best of our understanding, no existing dynamic PoSs supports this method. We developed a novel tool known as HAT which is an excellent authenticated structure. We suggested the excellent needs in multi-user cloud storage systems and introduced the type of deduplicatable dynamic PoS. Existing dynamic PoSs can’t be extended towards the multi-user atmosphere. Because of the problem of structure diversity and tag generation, existing system can’t be extended to dynamic PoS. An operating multi-user cloud storage system needs the secure client-side mix-user deduplication technique, which enables a person to skip the uploading process and acquire the possession from the files immediately, when other proprietors of the identical files have submitted these to the cloud server. to lessen the communication cost both in the evidence of storage phase and also the deduplication phase concentrating on the same computation cost. We prove the safety in our construction, and also the theoretical analysis and experimental results reveal that our construction is efficient used. Within this paper, we introduce the idea of deduplicatable dynamic evidence of storage and propose a competent construction known as DeyPoS, to attain dynamic PoS and secure mix-user deduplication, concurrently.

The future of mobile wireless communication networks will be experiencing several generations. This kind of development will drive the researches of information technology in industrial area of continuous development and evolution. In this paper, we have explored future generations of mobile wireless communication networks including 4th, 5th，and so forth. If looking to past, wireless access technologies have been followed different evolutionary paths with aim at unified target related to performance and efficiency in high mobile environment. Android develops one of the most popular mobile operating system in the whole world, as a side effect of this popularity, Android becomes the most preferred destination of hackers with different aims, some of them looking for making money and others are just having fun by raid the privacy of the others without their authorization. Nowadays, Android security has become a major problem because of the free application provided and functionalities that make it very easy for anyone to progress it. However, various systems have been planned by a large number of scholars to address these problems.