scispace - formally typeset
Search or ask a question
Author

Sannasi Ganapathy

Bio: Sannasi Ganapathy is an academic researcher from VIT University. The author has contributed to research in topics: Intrusion detection system & Wireless sensor network. The author has an hindex of 21, co-authored 77 publications receiving 1239 citations. Previous affiliations of Sannasi Ganapathy include Anna University & College of Engineering, Guindy.


Papers
More filters
Journal ArticleDOI
TL;DR: From the experiments conducted in this research work using the proposed model, it is proved that the proposed routing algorithm provided better network performance in terms of the metrics namely energy utilization, packet delivery ratio, delay and network lifetime.

243 citations

Journal ArticleDOI
TL;DR: A survey on intelligent techniques for feature selection and classification for intrusion detection in networks based on intelligent software agents, neural networks, genetic algorithms, neuro-genetic algorithms, fuzzy techniques, rough sets, and particle swarm intelligence is proposed.
Abstract: Rapid growth in the Internet usage and diverse military applications have led researchers to think of intelligent systems that can assist the users and applications in getting the services by delivering required quality of service in networks. Some kinds of intelligent techniques are appropriate for providing security in communication pertaining to distributed environments such as mobile computing, e-commerce, telecommunication, and network management. In this paper, a survey on intelligent techniques for feature selection and classification for intrusion detection in networks based on intelligent software agents, neural networks, genetic algorithms, neuro-genetic algorithms, fuzzy techniques, rough sets, and particle swarm intelligence has been proposed. These techniques have been useful for effectively identifying and preventing network intrusions in order to provide security to the Internet and to enhance the quality of service. In addition to the survey on existing intelligent techniques for intrusion detection systems, two new algorithms namely intelligent rule-based attribute selection algorithm for effective feature selection and intelligent rule-based enhanced multiclass support vector machine have been proposed in this paper.

170 citations

Journal ArticleDOI
TL;DR: A novel feature selection algorithm, which selects an optimal number of features from the data set and an intelligent fuzzy temporal decision tree algorithm integrated with convolution neural networks to detect the intruders effectively are proposed.
Abstract: Intrusion detection systems assume a noteworthy job in the provision of security in wireless Sensor networks. The existing intrusion detection systems focus only on the detection of the known types of attacks. However, it neglects to recognise the new types of attacks, which are introduced by malicious users leading to vulnerability and information loss in the network. In order to address this challenge, a new intrusion detection system, which detects the known and unknown types of attacks using an intelligent decision tree classification algorithm, has been proposed. For this purpose, a novel feature selection algorithm named dynamic recursive feature selection algorithm, which selects an optimal number of features from the data set is proposed. In addition, an intelligent fuzzy temporal decision tree algorithm is also proposed by extending the decision tree algorithm and integrated with convolution neural networks to detect the intruders effectively. The experimental analysis carried out using KDD cup data set and network trace data set demonstrates the effectiveness of this proposed approach. It proved that the false positive rate, energy consumption, and delay are reduced in the proposed work. In addition, the proposed system increases the network performance through increased packet delivery ratio.

92 citations

Journal ArticleDOI
TL;DR: A novel technique to obtain the solution of load flow in radially operated distribution networks, in which the loads can be represented by any model, based on the formation of a constant sparse upper triangular matrix, which is used to determine the bus voltages.

92 citations

Journal ArticleDOI
TL;DR: From the experiments conducted, it is proved that the proposed trust based routing algorithm achieves significant performance improvement over the existing schemes in terms of security, energy efficiency and packet delivery ratio.
Abstract: Security is an important phenomena for energy conservation in wireless sensor networks (WSN). Moreover, the management of trust in the WSN is a challenging task since trust is used when collaboration is critical to achieve reliable communication. In a military application using WSN, it is often necessary to communicate secret information such as military operation urgently. However, the existing routing algorithms do not consider security in the routing process. Moreover, since security is an important aspect in WSN, it is necessary to consider the security aspects in routing algorithms. Different approaches for providing security are trust management, intrusion detection, firewalls and key management are considered in the literature. Among them, trust management can provide enhanced security when it is compared with other security methods. Therefore, a new secure routing algorithm called energy aware trust based secure routing algorithm is proposed in this paper where the trust score evaluation is used to detect the malicious users effectively in WSN and spatio-temporal constraints are used with decision tree algorithm for selecting the best route. From the experiments conducted, it is proved that the proposed trust based routing algorithm achieves significant performance improvement over the existing schemes in terms of security, energy efficiency and packet delivery ratio.

83 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: This survey presented a comprehensive investigation of PSO, including its modifications, extensions, and applications to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology.
Abstract: Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

836 citations

Journal ArticleDOI
TL;DR: An extensive literature review on load-frequency control (LFC) problem in power system has been highlighted in this article, where various configuration of power system models and control techniques/strategies that concerns to LFC issues have been addressed in conventional as well as distribution generation-based power systems.
Abstract: In this paper an extensive literature review on load–frequency control (LFC) problem in power system has been highlighted. The various configuration of power system models and control techniques/strategies that concerns to LFC issues have been addressed in conventional as well as distribution generation-based power systems. Further, investigations on LFC challenges incorporating storage devices BESS/SMES, FACTS devices, wind–diesel and PV systems etc have been discussed too.

485 citations

Journal ArticleDOI
TL;DR: A new systematic approach is used for the diabetes diseases and the related medical data is generated by using the UCI Repository dataset and the medical sensors for predicting the people who has affected with diabetes severely and a new classification algorithm called Fuzzy Rule based Neural Classifier is proposed for diagnosing the disease and the severity.

270 citations

Journal ArticleDOI
20 Sep 2018-Energies
TL;DR: This paper presents a comprehensive literature survey on the topic of LFC, and investigates the used LFC models for diverse configurations of power systems and proposes proposed control strategies for LFC for both conventional and future smart power systems.
Abstract: Power systems are the most complex systems that have been created by men in history To operate such systems in a stable mode, several control loops are needed Voltage frequency plays a vital role in power systems which need to be properly controlled To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance Likewise, the power exchanges between different control areas are controlled by LFC approaches In recent decades, many control approaches have been suggested for LFC in power systems This paper presents a comprehensive literature survey on the topic of LFC In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC

253 citations