ABES Engineering College

About: ABES Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Routing protocol. The organization has 576 authors who have published 621 publications receiving 2165 citations.

An Exhaustive Research on the Application of Intrusion Detection Technology in Computer Network Security in Sensor Networks

Abstract: Intrusion detection is crucial in computer network security issues; therefore, this work is aimed at maximizing network security protection and its improvement by proposing various preventive techniques. Outlier detection and semisupervised clustering algorithms based on shared nearest neighbors are proposed in this work to address intrusion detection by converting it into a problem of mining outliers using the network behavior dataset. The algorithm uses shared nearest neighbors as similarity, judges whether it is an outlier according to the number of nearest neighbors of a data point, and performs semisupervised clustering on the dataset where outliers are deleted. In the process of semisupervised clustering, vast prior knowledge is added, and the dataset is clustered according to the principle of graph segmentation. The novelty of the proposed algorithm lies in outlier detection while effectively avoiding the dependence on parameters, thus eliminating the influence of outliers on clustering. This article uses real datasets: lypmphography and glass for simulation purposes. The simulation results show that the algorithm proposed in this paper can effectively detect outliers and has a good clustering effect. Furthermore, the experimentation reveals that the outlier detection-based SCA-SNN algorithm has the best practical effect on the dataset without outliers, clearly validating the clustering performance of the outlier detection-based SCA-SNN algorithm. Furthermore, compared to the other state-of-the-art anomaly detection method, it was revealed that the anomaly detection technology based on outlier mining does not require a training process. Thus, they overcome the current anomaly detection problems caused due to incomplete normal patterns in training samples.

Approach to accurate circle detection: Circular Hough Transform and Local Maxima concept

Abstract: Detecting circular objects over digital images have received considerable attention from industries for applications such as detection of pellets in pelletization plant, target detection, inspection of manufactured products etc. Several algorithms were proposed in past few years to detect circular features. One powerful approach for circle detection is the Circular Hough Transform and its variants. This article presents an algorithm which is based on CHT and Local Maxima concept. Finding one or several maxima considering different accumulators simultaneously and mapping the found parameters corresponding to the maxima back to the original image is key concept of proposed algorithm. Experiments were performed on real industrial images to validate the efficiency of proposed algorithm regarding good accuracy of detection.

Statistical Resultant Analysis of Psychosomatic Survey on Various Human Personality Indicators: Statistical Survey to Map Stress and Mental Health

Abstract: Machines are getting intelligent day by day. Modern science has gifted us many boons but simultaneously the mental, physical and spiritual disorders have surprisingly disturbed smile, peace and definite attitude and lifestyle of individual and all human beings. The stress has been the biggest challenge against mankind like nuclear weapons, global warming, and epidemics. It leads towards tension, frustration, and depression and ultimately in extreme cases towards the suicide or murder of innocents. The happiness index, safety of individual, living parameters have drastically challenged us and India specially has pathetic situation among global quality of life (QoL) index. This chapter is an effort to define a simulated model and framework for the subjective quality of stress into quantitative parameters and mathematically analyzing it with help of popular machine learning tools and applied methods. Using machine intelligence, authors are trying to establish a framework which may work as an expert system and may help the individual to grow self as better human being.

Analysis of Different Text Steganography Techniques: A Survey

Abstract: Steganography is helping individual to send confidential data between two parties. It enables user to hide data in different digital mediums. Steganography is of many types such as image steganography, text steganography, audio/video steganography etc. Text Steganography is quite difficult than other techniques because of less amount of redundancy and changes can be detected quite easily. Some of the techniques of text steganography has been discussed along with characteristics and working.