Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

An improved framework for authorship identification in online messages

Abstract: The authorship identification will determine the likelihood of the writing produced, by an author, by means of examining the other writings. The rapid proliferation of technologies along with the applications of the internet, the misuse of online messages for the purpose of inappropriate or for illegal reasons is a major concern in society. The online message distribution and its anonymous nature will make the identity of tracing anyone of critical issue. The work has been developed using a framework for the identification of authorship of the online messages for addressing as well as tracing such problems. For this framework, identification of authorship is done by the four writing style features (the lexical, the syntactic, the structural, and the n-gram features) that are extracted and inductive learning algorithms have been used for building a feature based classification model for the identification of the authorship of the online messages. For this work, the C4.5, the fuzzy and also the Ada boost classifiers will be used for the task of authorship-identification. An experimental study on this framework with the effects of these classification techniques on online messages is evaluated.

Saliency-Based Image Compression Using Walsh–Hadamard Transform (WHT)

Abstract: Owing to the development of multimedia technology, it is mandatory to perform image compression, while transferring an image from one end to another. The proposed method directly highlights the salient region in WHT domain, which results in the saliency map with lesser computation. The WHT-based saliency map is directly used to guide the image compression. Initially, the important and less important regions are identified using WHT-based visual saliency model. It significantly reduces the entropy and also reserves perceptual fidelity. The main aim of the proposed method is to produce the high-quality compressed images with lesser computational effort and thereby achieving high compression ratio. Due to the simplicity and high speed of WHT, the proposed visual saliency-based image compression method is producing reliable results, in terms of peak signal-to-noise ratio (PSNR), compression ratio, and structural similarity (SSIM), compared to the state-of-the-art methods.

Enhanced transductive support vector machine classification with grey wolf optimizer cuckoo search optimization for intrusion detection system

Abstract: These days, the Intrusion detection System (IDS) is the most talked topic among the scientist and researchers and many research is going on in IDS, which is firmly connected to the protected utilization of system administrations. IDS are an essential part of the security infrastructure. The previous research works are focused to detect the attacks efficiently but it is failed to produce more accurate classification results. To stay away from the previously mentioned issues, in the proposed framework, Hybrid Grey Wolf optimizer Cuckoo Search Optimization (HGWCSO) along with Enhanced Transductive Support Vector Machine (ETSVM) is proposed. This exploration incorporates the modules are, for example, preprocessing, selection of features and classification of features. The processing of data is done by using normalization technique by using min‐max technique the main work is to replace the value missed and filters the features from NSL KDD dataset values. The main objective of processing of data is to increase the accuracy of classification. Then, the more relevant and optimal features are selected by using HGWCSO. The GWO robustness and searching performance is increased by cuckoo search algorithm. Then, the classification is performed to identify the intrusion attack types using ETSVM algorithm more efficiently. This classification algorithm is used to improve the attack detection accuracy higher. The experimental result concludes that the proposed HGWCSO with ETSVM algorithm provides better performance metrics in terms of high precision, sensitivity, specificity, and accuracy than the previous algorithms.

Response surface modeling and optimization of upflow anaerobic sludge blanket reactor process parameters for the treatment of bagasse based pulp and paper industry wastewater

Abstract: The interactive effects of influent chemical oxygen demand (CODin), hydraulic retention time (HRT), and temperature on the performance of an upflow anaerobic sludge blanket reactor, operated in continuous mode, were studied for the anaerobic biodegradation of bagasse effluent from pulp and paper industry. Experiments were conducted based on Box–Behnken design and analyzed using response surface methodology. CODin (4,400–6,800 mg/l), HRT (15–27 h), and temperature (20–40°C) were the operating variables considered for this study. Three dependent parameters viz., percentage of COD removal, COD removal rate, and biogas production were either directly measured or calculated as response. Analysis of variance showed a high coefficient of determination value (R2) of 0.9990 for percentage COD removal, 0.9960 for COD removal rate, and 0.9953 for biogas production thus ensuring a satisfactory fit of the second-order polynomial regression model with the experimental data. Maximum values of percentage COD remo...

A packet marking approach to protect cloud environment against DDoS attacks

Abstract: Cloud computing uses internet and remote servers for maintaining data and applications. It offers through internet the dynamic virtualized resources, bandwidth and on-demand software's to consumers and promises the distribution of many economical benefits among its adapters. It helps the consumers to reduce the usage of hardware, software license and system maintenance. Simple Object Access Protocol (SOAP) is the system that allows the communications interaction between different web services. SOAP messages are constructed using either HyperText Transport Protocol (HTTP) and/or Extensible Mark-up Language (XML). The new form of Distributed Denial of Service (DDoS) attacks that could potentially bring down a cloud web services through the use of HTTP and XML. Cloud computing suffers from major security threat problem by HTTP and XML Denial of Service (DoS) attacks. HX-DoS attack is a combination of HTTP and XML messages that are intentionally sent to flood and destroy the communication channel of the cloud service provider. To address the problem of HX-DoS attacks against cloud web services there is a need to distinguish between the legitimate and illegitimate messages. This can be done by using the rule set based detection, called CLASSIE and modulo marking method is used to avoid the spoofing attack. Reconstruct and Drop method is used to make decision and drop the packets on the victim side. It enables us to improve the reduction of false positive rate and increase the detection and filtering of DDoS attacks.