Mobile ADHOC Networks,
Wireless Communication,
IoT
12
Scopus Publications
72
Scholar Citations
5
Scholar h-index
3
Scholar i10-index
Scopus Publications
Data Mining, Machine Learning, and Statistical Modeling for Predictive Analytics with Behavioral Big Data Arunkumar, M., Rajkumar, K., Jeyaseelan, W. R. Salem, Natraj, N. A. Tehnicki Vjesnik, 2025 This research delves into the transformative impact of the widespread adoption of big data and advancements in predictive analytics on decision-making processes across industries.The study specifically concentrates on the paradigm of behavioral big data computation, integrating a spectrum of data sources, including social media, online platforms, and IoT devices.Employing a comprehensive analysis involving data mining, machine learning, and statistical modeling, the research unveils intricate patterns and insights within the data.The methodology aims to extract meaningful behavioral indicators that significantly influence the outcomes of predictive analytics.Additionally, the study explores how behavioral big data computation impacts the accuracy, timeliness, and reliability of predictive models.Embracing a systematic and in-depth approach, the research aims to provide a thorough understanding of the potential applications and challenges associated with harnessing behavioral big data computation for predictive analytics.Anticipated outcomes encompass insights into the development of robust predictive models capable of anticipating trends, consumer behavior, and market dynamics.This, in turn, empowers organizations to make well-informed strategic decisions in today's dynamic and competitive business landscape.The findings of this research are poised to contribute valuable knowledge, enhancing the efficacy of predictive analytics in diverse business scenarios.
Improved Grey Wolf Optimization Based Node Localization Approach in Underwater Wireless Sensor Networks WR Salem Jeyaseelan, T Jayasankar, K Vinoth Kumar, R Ponni Measurement Science Review, 2024 Underwater Wireless Sensor Networks (UWSNs) are established by Autonomous Underwater Vehicles (AUVs) or static Sensor Nodes (SN) that collect and transmit information over the underwater environment. Localization plays a vital role in the effective deployment, navigation and coordination of these nodes for many applications, namely underwater surveillance, underwater exploration, oceanographic data collection and environmental monitoring. Due to the unique characteristics of underwater transmission and acquisition, this is a fundamental challenge in underwater networks. However, localization in UWSNs is problematic due to the unique features of underwater transmission and the harsh underwater environment. To address these challenges, this paper presents an Improved Grey Wolf Optimization Based Node Localization Approach in UWSN (IGWONL-UWSN) technique. The presented IGWONL-UWSN technique is inspired by the hunting behavior of grey wolves with the Dimension Learning-based Hunting (DLH) search process. The proposed IGWONL-UWSN technique uses the Improved Grey Wolf Optimization Based (IGWO) algorithm to calculate the optimal location of the nodes in the UWSN. Moreover, the IGWONL-UWSN technique incorporates the DLH search process to improve the convergence and accuracy. The simulation results of the IGWONL-UWSN technique are validated using a set of performance measures. The simulation results show the improvements of the IGWONL-UWSN method over other approaches with respect to various metrics.
Detecting and Mitigating Low-Rate DoS and DDoS Attacks: Multimodal Fusion of Time-Frequency Analysis and Deep Learning model Thangavel Yuvaraja, Winston Gnanathika Rajan, Salem Jeyaseelan, Rengasamy Ashokkumar, Magudeeswaran Premkumar, PhD W. R. Salem JEYASEELAN, PhD S. R. ASHOKKUMAR Tehnicki Vjesnik, 2024 : This paper outlines a method for identifying and counteracting distributed denial of service (DDoS) and low-rate denial of service (DoS) attacks. These impair significant threats to network security and can disrupt the accessibility and efficacy of systems under attack. The proposed method combines Time-Frequency Analysis (TFA) using Short-Time Fourier Transform (STFT) and a Deep Learning model (DLM), namely Recurrent Neural Network (RNN), to enhance network security. By leveraging the strengths of STFT and RNN, the approach achieves improved detection capabilities and enables timely response and effective mitigation. The CICDDoS2019 dataset has been employed to conduct the evaluation, which provides a diverse set of realistic attack traffic scenarios. The results show that the proposed approach is effective, with an impressive accuracy rate of 99.1%. Compared to traditional methods, the integrated achieves higher accuracy and lower false positive rates. This research highlights the potential of Multimodal Fusion method, for addressing the growing need for advanced defense mechanisms in today's evolving threat landscape.
Support Vector Machine Classification using Proximity Authentication and Surveillance System in IoT Industrial Network W. R., Salem Jeyaseelan, P., Sudhakaran, V., Rajakani, A., Parameswari Tehnicki Vjesnik, 2024 This research focuses on developing a proximity-based authentication and surveillance system using Internet of Things (IoT) devices in industrial networks. The system aims to improve security measures by ensuring only authorized personnel have access to critical areas of the network. Researching authentication mechanisms and protocols, examining network authentication system features and application environments, and developing an online-based, real-time monitoring authentication system are the goals of this article. The system will utilize sensors and cameras installed in strategic locations to detect and track personnel movement within the network. When a person approaches a secured area, their identity will be verified using proximity-based authentication using RFID technology. The system will also monitor and record any suspicious activity, providing real-time alerts to security personnel. To detect malicious behavior on short-range, low-rate, and low-power networks, such as those found in the Internet of Things (IoT), we advise utilizing SVM models. The proposed system is expected to increase security and reduce the risk of unauthorized access to industrial networks, ultimately enhancing overall network reliability and safety. The results are compared with various parameters.
QoS based Adaptive Multi-Constrained Energy Efficient Routing for Vehicular Ad hoc Networks Krishnan, Rajkumar, Kalimuthu, Vinoth Kumar, Jeyaseelan W R, Salem, Venkatachalam, Bharathi Tehnicki Vjesnik, 2024 A QoS-based Adaptive Multi-Constrained Energy-Efficient (AMQoS) routing approach addresses the limitations of the current single-constrained and multi-constrained Quality of Service (QoS) routing algorithms for Vehicular Ad-hoc Networks (VANETs). The proposed method aims to enhance packet delivery effectiveness by effectively managing the utilization of QoS resources. Unlike the current reactive Dynamic Source Routing (DSR) algorithm, the suggested routing algorithm incorporates QoS parameters and network stack parameters into the route discovery process. This cross-layer model is established by aggregating QoS and network stack parameters from various layers of the TCP/IP protocol stack. Additionally, the proposed routing method integrates a Rough Set Theory-based analysis of multi-layer stack parameters pertaining to VANET QoS to determine the relevant stack parameters for routing packets. In terms of network scalability, the proposed routing algorithm demonstrates superior performance over Priority-Aware Dynamic Source Routing (PA-DSR) for various metrics, including energy efficiency, goodput, Packet Error Rate (PER), delay, and more. PA-DSR, while effective in small networks with low mobility, establishes QoS routes with reserved bandwidth from source to destination. The performance evaluation of AMQoS, DSR, and PA-DSR encompasses several QoS measures, considering factors such as the number of mobile nodes and mobility speed. The proposed routing stands out due to its strategies for load distribution across the network and efficient routing cost management, outperforming DSR and PA-DSR across various metrics, including goodput, delay, and energy efficiency.
Efficient Intelligent Smart Ambulance Transportation System using Internet of Things Jeyaseelan W. R., Salem, Krishnan, Rajkumar, M., Arunkumar, Alagarsamy, Parameswari Tehnicki Vjesnik, 2024 This research is significant, as traffic jam has become the main challenge in current metropolitan cities. Both in developed and developing nations, it is a concern for an ambulance to carry an emergency patient. Despite the fact, ambulance receives special traffic protocols, it is still challenging that the ambulance reaches the hospital on time. In the context of a smart city, this proposal suggests a smart ambulance management system. If the patient needs an ambulance, the operator finds the nearest emergency vehicle and points it in the patient's direction. The programme dynamically tracks the positions of the ambulances to determine the quickest path to the injured person using maps provided by Google as an external service. Here we are tracking the ambulance with an IR transmitter and the road nearby speed breaker will have IR Receiver. Arduino Node MCU sends the alert message through the Internet of Things (IoT) and Global Positioning System (GPS). Then the necessary action can be taken after conforming to the location at a time. If an ambulance is on a nearby speed breaker, then it will turn automatically to the bottom and the even space will come up. It will give the chance for no need to reduce the speed of ambulance. During system analysis and experimentation, the system's efficiency, and dependability can be enhanced as well as a significant reduction in healthcare costs, a reduction in the number of intermediaries and timely and efficient service, and the avoidance of wasting time. This paper is to examine different IoT techniques for movement control and the different approaches to assist the emergency vehicle to reach nearby healing facility on time. The main focus is on finding the best techniques to reduce the traffic congestion.
Dynamic data delivery and terrific transfer in wireless sensor networks R. J. Kavitha, W. R. Salem Jeyaseelan Applied Mathematics and Information Sciences, 2018 Load Balanced Clustering (LBC) framework is a innovative te chniques that enhance energy efficiency to extend the networ k lifetime. Clustering is an effective topology manipulate a roach in wireless sensor networks, which can explosion netw ork scalability and lifetime. A load balanced clustering algorithm is propo sed for sensors to self-arrange themselves into clusters.c ell divider is used for split the statistics aroximately cluster and cluster he ad calculation.. The results show that LBC can significantly reduce energy consumptions by assuaging routing techniques on nodes and b alancing workload among cluster heads, which achieves 20 pe rcent less facts series time in comparison to SISO cell data accumulati ng and over 60 percentage energy saving on cluster heads. It a lso justified the packet overhead and explored the consequences with diff erent numbers of cluster heads within the cluster. The main m otivation is to utilize disbursed clustering for scalability, to aoint mob ility for energy saving and uniform energy consumption, and to take advantage of a couple of-input and more than one-output MIMO (Multiple Input and Multiple Output) method for concurrent statistic importing to shorten latency.
Malware detection and elimination using bayesian technique and Nymble algorithm W. R. Salem Jeyaseelan, S. Hariharan Indian Journal of Science and Technology, 2015 Background/Objectives: DTN becomes popular because of its ability to cope with the problems in traditional infrastructural model. Like other kinds of network it is also subjected to malware attacks. Methods/Statistical Analysis: Pattern matching technique is so far used. But that is not secure in DTN as there is changing network topology. In this paper, a novel malware processing technique is proposed which uses Bayesian technique and Nymble algorithm. Bayesian technique is used to fabricate a secure DTN and Nymble algorithm helps in removing malware. Findings: Bayesian technique is used in non DTN techniques for malware processing. While using Bayesian techniques to generate a secure DTN without false positive, active attacks, passive attacks, false negative, effect of liars, effect of malware affected nodes, inadequate evidence and malware spreading. All the challenges are addressed using dogmatic filtering, adaptive look ahead, cut off strategy techniques. Nymble algorithm enhances the security of DTN. It provides ambiguity, rate limiting, subjective blacklisting and non-frame ability. Application/Improvements: The proposed techniques are used to identify any abnormal behavior of the nodes and complaints will be posted. Only authenticated users can post complaints. In addition to this, it provides cryptographic security to the users. The non-legitimate nodes in the network will be blocked and displayed. This improves the QoS of the DTN.
Secure multicast transmission W. R. Salem Jeyaseelan, Shanmugasundaram Hariharan 2013 4th International Conference on Computing Communications and Networking Technologies Icccnt 2013, 2013
Enhanced route discovery in Mobile Adhoc Networks S. A. V. Ali, W. R. Salem Jeyaseelan, S. Hariharan 2012 3rd International Conference on Computing Communication and Networking Technologies Icccnt 2012, 2012
RECENT SCHOLAR PUBLICATIONS
Improved Grey Wolf Optimization Based Node Localization Approach in Underwater Wireless Sensor Networks WRS Jeyaseelan, KV Kumar, T Jayasankar, R Ponni Measurement Science Review 24 (3), 95-99 , 2024 2024.0 Citations: 8
THE NOVEL APPROACH FOR AUTOMATIC FACIAL MASK RECOGNITION FOR VISITORS AND EMPLOYEE IN AN ORGANIZATION TO PROVIDE FACE MASK RS GANITHA AARTHI N, Dr. W. R. SALEM JEYASEELAN, P. DINESH KUMAR The Saybold Report 17 (11), 2018 -2024 , 2022 2022.0
HYBRID ENCRYPTION FRAMEWORK FOR SECURING BIG DATA STORAGE IN MULTI-CLOUD ENVIRONMENT DRWRS NANDHAKUMAR M International Journal for Science and Advance Research in Technology (IJSART … , 2022 2022.0
Detection, prevention and mitigation of wormhole attack in wireless adhoc network by coordinator RA Prakash, WRS Jeyaseelan, T Jayasankar Appl. Math 12 (1), 233-237 , 2018 2018.0 Citations: 26
Dynamic Data Delivery and Terrific Transfer in Wireless Sensor Networks RJ Kavitha, WRS Jeyaseelan Appl. Math 12 (3), 529-535 , 2018 2018.0
Comparative study on MANET routing protocols [J] WRS Jeyaseelan, S Hariharan Asian Journal of Information Technology, 1411-1415 , 2016 2016.0 Citations: 4
Malware detection and elimination using Bayesian technique and nymble algorithm WRS Jeyaseelan, S Hariharan Indian Journal of Science and Technology 8 (34), 1-7 , 2015 2015.0 Citations: 2
Secure multicast transmission WRS Jeyaseelan, S Hariharan 2013 Fourth International Conference on Computing, Communications and … , 2013 2013.0
Enhanced Route Discovery in Mobile Adhoc Networks SAV Ali, WRS Jeyaseelan, S Hariharan 2012 Third International Conference on Computing, Communication and … , 2012 2012.0 Citations: 15
Study on Congestion Aovidance in MANET WRS Jeyaseelan, S Hariharan IJCA Special Issue on “Network Security and Cryptography”, NSC , 2011 2011.0 Citations: 5
Study on Congestion Avoidance in MANET WRSJ Shanmugasundaram Hariharan. IJCA 5 (2), 7-10 , 2011 2011.0
Investigation on routing protocols in MANET WRS Jeyaseelan, S Hariharan International Journal of Research and Reviews in Information Sciences … , 2011 2011.0 Citations: 12
A New Way to Protect Video Steganography Method Based on Discrete Wavelet Transform and Multiple Object Tracking K Oviya, NG Aarthi, WRS Jeyaseelan Special Issue in Communication and Information Technology, 85 , 0
A Multi Model Approach for Video Data Steganography with Avoiding Jellyfish Delay Variance Attack WRS Jeyaseelan, K Oviya, NG Aarthi Special Issue in Communication and Information Technology, 80 , 0
Enhanced RSA Encrypted AODV Routing Protocol for MANET WRS Jeyaseelan, R Madhumitha, D Yuvaraj Special Issue in Communication and Information Technology, 91 , 0
Chaotic Encryption for Fingerprint Authentication NG Aarthi, WRS Jeyaseelan, K Oviya Special Issue in Communication and Information Technology, 70 , 0
BEHAVIOR BASED MALWARE PROCESSING IN DTN USING BAYESIAN MODEL K Dhivya, WRS Jeyaseelan
MOST CITED SCHOLAR PUBLICATIONS
Detection, prevention and mitigation of wormhole attack in wireless adhoc network by coordinator RA Prakash, WRS Jeyaseelan, T Jayasankar Appl. Math 12 (1), 233-237 , 2018 2018.0 Citations: 26
Enhanced Route Discovery in Mobile Adhoc Networks SAV Ali, WRS Jeyaseelan, S Hariharan 2012 Third International Conference on Computing, Communication and … , 2012 2012.0 Citations: 15
Investigation on routing protocols in MANET WRS Jeyaseelan, S Hariharan International Journal of Research and Reviews in Information Sciences … , 2011 2011.0 Citations: 12
Improved Grey Wolf Optimization Based Node Localization Approach in Underwater Wireless Sensor Networks WRS Jeyaseelan, KV Kumar, T Jayasankar, R Ponni Measurement Science Review 24 (3), 95-99 , 2024 2024.0 Citations: 8
Study on Congestion Aovidance in MANET WRS Jeyaseelan, S Hariharan IJCA Special Issue on “Network Security and Cryptography”, NSC , 2011 2011.0 Citations: 5
Comparative study on MANET routing protocols [J] WRS Jeyaseelan, S Hariharan Asian Journal of Information Technology, 1411-1415 , 2016 2016.0 Citations: 4
Malware detection and elimination using Bayesian technique and nymble algorithm WRS Jeyaseelan, S Hariharan Indian Journal of Science and Technology 8 (34), 1-7 , 2015 2015.0 Citations: 2
THE NOVEL APPROACH FOR AUTOMATIC FACIAL MASK RECOGNITION FOR VISITORS AND EMPLOYEE IN AN ORGANIZATION TO PROVIDE FACE MASK RS GANITHA AARTHI N, Dr. W. R. SALEM JEYASEELAN, P. DINESH KUMAR The Saybold Report 17 (11), 2018 -2024 , 2022 2022.0
HYBRID ENCRYPTION FRAMEWORK FOR SECURING BIG DATA STORAGE IN MULTI-CLOUD ENVIRONMENT DRWRS NANDHAKUMAR M International Journal for Science and Advance Research in Technology (IJSART … , 2022 2022.0
Dynamic Data Delivery and Terrific Transfer in Wireless Sensor Networks RJ Kavitha, WRS Jeyaseelan Appl. Math 12 (3), 529-535 , 2018 2018.0
Secure multicast transmission WRS Jeyaseelan, S Hariharan 2013 Fourth International Conference on Computing, Communications and … , 2013 2013.0
Study on Congestion Avoidance in MANET WRSJ Shanmugasundaram Hariharan. IJCA 5 (2), 7-10 , 2011 2011.0
A New Way to Protect Video Steganography Method Based on Discrete Wavelet Transform and Multiple Object Tracking K Oviya, NG Aarthi, WRS Jeyaseelan Special Issue in Communication and Information Technology, 85 , 0
A Multi Model Approach for Video Data Steganography with Avoiding Jellyfish Delay Variance Attack WRS Jeyaseelan, K Oviya, NG Aarthi Special Issue in Communication and Information Technology, 80 , 0
Enhanced RSA Encrypted AODV Routing Protocol for MANET WRS Jeyaseelan, R Madhumitha, D Yuvaraj Special Issue in Communication and Information Technology, 91 , 0
Chaotic Encryption for Fingerprint Authentication NG Aarthi, WRS Jeyaseelan, K Oviya Special Issue in Communication and Information Technology, 70 , 0
BEHAVIOR BASED MALWARE PROCESSING IN DTN USING BAYESIAN MODEL K Dhivya, WRS Jeyaseelan