MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Computer Engineering & Technology

CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is a security mechanism designed to differentiate between humans from malicious bot program. Captcha's are the security checks which prevents spammers and hackers from getting the important data from the web pages through this malicious code or robotic software program. Text-based captcha's were most widely deployed across the web to secure against malicious bot programs. Numerous successful attacks on this single layer text-based attacks were deployed by Google, Microsoft, Yahoo, Amazon, and other Internet giants. These attacks on text-based captcha's achieved a success rate from 5% to 77 % in less than 10 seconds on a standard desktop computer (with 3.5 GHz Intel Core i5 CPU and 8 GB RAM). In 2015 Microsoft deployed a new two-layer Captcha scheme which was more difficult for bots to attack. But recent survey state that the two-layer Microsoft's Captcha can be attacked with an average speed of 9.05s on a standard desktop computer. In this paper, Microsoft two layer captcha is analysed studied and new multilayer captcha is being proposed which will make bots difficult to attack the Captcha and get the important data from web maliciously. The proposed Captcha will be composed multilayer text-based captcha combined with an image which can be solved using a checkbox. The proposed captcha can be solved by humans in less than two seconds but will be very difficult for bots to solve. The proposed captcha is also time-based which should be solved within 10 seconds which will make bots even more challenging to attack the captcha. © 2019 Newswood Limited. All rights reserved.

Engineering and Technology

World University root node

Lecture Notes in Engineering and Computer Science

Smart Captcha to Provide High Security Against Bots

A mobile grid (MG) consists of interconnected mobile devices which are used for high performance computing. Fault tolerance is an important property of mobile computational grid systems for achieving superior arrangement reliability and faster recovery from failures. Since the failure of the resources affects task execution fatally, fault tolerance service is essential to achieve QoS requirement in MG. The faults which occur in MG are link failure, node failure, task failure, limited bandwidth etc. Detecting these failures can help in better utilisation of the resources and timely notification to the user in a MG environment. These failures result in loss of computational results and data. Many algorithms or techniques were proposed for failure handling in traditional grids. The authors propose a checkpointing based failure handling technique which will improve arrangement reliability and failure recovery time for the MG network. Experimentation was conducted by creating a grid of ubiquitously available Android-based mobile phones.

International Journal of Grid and High Performance Computing

Application Checkpointing Technique for Self-healing from Failures in Mobile Grid Computing

Routing in the Internet of Things (IoT) renders the protection against various network attacks as any attacker intrudes the routing mechanism for establishing the destructive mechanisms against the network, which insists the essentiality of the security protocols in IoT. Thus, the paper proposes a secure protocol based on an optimization algorithm, Monarch-Earthworm Algorithm (Monarch-EWA), which is the modification of the Monarch Butterfly algorithm using the Earthworm Optimization Algorithm (EWA) in order to render effective security to the network. Initially, the effective nodes are selected using the Deep Convolutional Neural Network (deep CNN) classifier based on the factors, trust and energy of the node, and stochastic gradient descent algorithm trains the deep CNN classifier. The secure nodes are involved in routing for which the secure multipath is chosen optimally using the proposed Monarch-EWA, which chooses the secure multipath based on the factors, energy and trust. The analysis of the proposed method in the presence of attacks, such as black hole, message replicate and distributed denial of service, reveals that the proposed method outperformed the existing methods. The proposed Monarch-EWA protocol acquired the maximal energy, throughput and detection rate of 0.2268 J, 48.2759% and 82.6231%, respectively, with the minimal delay of 0.0959 ms.

The Computer Journal, Oxford University Press UK

Monarch-EWA: Monarch-Earthworm-Based Secure Routing Protocol in IoT

Maintaining human healthcare is one of the biggest challenges that most of theincreasing population in Asian countries are facing today. There is an unrelentingneed in our medical community to develop applications that are low on cost, withhigh compression, as huge number of patient’s data and images need to be transmittedover the network to be reviewed by the physicians for diagnostic purpose. Thisimplemented work represents discrete wavelet-based threshold approach. Using thisapproach by applying N-level decomposition on 2D wavelet types like Biorthogonal,Haar, Daubechies, Coiflets, Symlets, Reverse Biorthogonal, and Discrete Meyer, var-ious levels of wavelet coefficients are obtained. The lossless hybrid encoding algo-rithm, which combines run-length encoder and Huffman encoder, has been used forcompression and decompression purpose. This work is proposed to examine theefficiency of different wavelet types and to determine the best. The objective of thisresearch work is to improve compression ratio and compression gain.

The DICOM Image Compression and Patient Data Integration using Run Length and Huffman Encoder

Opportunistic forwarding mechanism in Delay Tolerant Networks (DTN), are prone to get disconnected from the nodes in the network. These types of networks deal with intermittent connectivity, large delays.Existing routing protocols of DTNs fights with these issues, but fail to integrate the security available for delay tolerant networks,it is necessary to design a secure routing protocol to overcome these issues. There are centralized Trust Authority (TA) based security systems but the disconnection or failure of TA, affects the security model and network performance. It becomes crucial to have the distributed approach for security system and have multiple TAs working on security model. This reduces the possibility of poor network performance. The paper presents a distributed misbehavior detection system, and implements multiple TAs for implementing the security model for DTN.

Fulltext

International Journal of Innovative Technology and Exploring Engineering

Distributed Misbehavior Detection System for Delay Tolerant Networks

Stress has become a universal emotion that people experience in day to day life. In this paper, emotion detection is carried out using benchmark DEAP dataset by implementing a new feature extraction techniques named as Teager-Kaiser Energy Operator (TKEO) with a k-nearest neighbor (KNN), neural network(NN) and Classification Tree (CT) classifiers based on Electroencephalography (EEG). The study evaluates the performance and accuracy of emotion detection which is further used for stress identification as EEG gives good correlation with stress. Also, the present work compares the implemented TKEO feature extraction technique with Relative Energy Ratio (RER), and Kernel Density Estimation (KDE) techniques regarding accuracy. This paper demonstrates how the inclusion of TKEO enhances feature extraction and proves a promising approach to emotion detection as compared to other conventional techniques. The experimental results show that TKEO when used with KNN, NN, CT classifier gives comparatively higher accuracy than KDE and RER for channel 1 alpha band and channel 17 beta band for stress detection.

International Journal of Innovative Technology and Exploring Engineering (IJITEE)

Human Emotion Detection and Stress Analysis using EEG Signal

Energy of nodes plays an important role in all kinds of networks whether it is wired network or wireless network, since most of the nodes are battery powered and it is not possible to recharge the battery whenever necessary. In most of the networks, the data cannot be sent completely when the connection is terminated from source to destination. Hence, the concept of delay-tolerant network (DTN) is introduced. In DTN, due to the mobility of nodes most of the nodes have sufficient amount of energy which is required for transferring of data. Energy is crucial issue in the concept of DTN, especially in disastrous like scenario, where recharging of battery becomes difficult. The proper use of energy for data transmission increases nodes lifetime and network lifetime situation. In this paper, some of the energy-saving techniques are explained to reduce the energy consumption of the node and also increase the packet delivery ratio. © Springer Nature Singapore Pte Ltd. 2019.

Advances in Intelligent Systems and Computing

Social energy-based techniques in delay-tolerant network

Technology is being used everywhere in our daily life to fulfill our requirements and aid our lives in every sphere including communication, traveling, entertainment, etc. But it has not been used up to its full potential in the field of health care. Real-time monitoring of patients and doctors is the primary concern of any healthcare facility and the conventional methods used in the hospitals are not being able to address these concerns efficiently. Our proposed system aims to provide a better service to the patients as compared to the conventional methods. It comprises of sensors for measuring temperature and pulse rate. A processor working in synchronization monitors the vitals of the patient and sends the captured data to the personal digital assistant (PDA) of head nurse and the doctors. In the PDA, an intelligent application gives statistical data of the vitals of patient in real-time manner. This data is used to analyze the health condition of patient over a period of time as well as monitor the patient in a real-time environment, remotely. We are also incorporating a coronary heart disease (CHD) predicting mechanism to determine whether a patient is susceptible to CHD. This mechanism is based on the concept of Traditional Chinese Medicine (TCM), which states that a large number of diseases (immaterial of the amount of severity they pose) can be diagnosed by sensing the pulse variations. This methodology is the foundation on which support vector machine (SVM) is predicting CHD in patients. © 2019, Springer Nature Singapore Pte Ltd.