P.Sivasankar

@nitttrc.ac.in

Associate Professor in Electronics Engineering, Department of Electrical, Electronics and Communication Engineering
National Institute of Technical Teachers Training and Research (NITTTR), Chennai

P.Sivasankar


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https://researchid.co/sivasankar
Dr. P. Sivasankar, is working as Associate Professor in Electronics Engineering, Department of Electrical, Electronics and Communication Engineering, National Institute of Technical Teachers Training and Research, Chennai, (Ministry of Education, Government of India) India, since 2006. He was born on 23rd July 1980 at Tiruvannamalai, Tamilnadu, India. He published around 36 articles like papers / book chapters etc. in various reputed International, National Journals and Conferences; published two books titled "LabVIEW Programming Concepts with Examples", Co-authored by G.A.Rathy, in Sci Tech publications, Year : 2015 and "NG Smartphone Users Activity and Direction Detection using MQTT in IoT" with the authors of Kothandaraman, D, and Nagendar, in LAMBERT Academic Publisher, Year : 2019. He coordinated around 130 Faculty Development Programmes, serving as Member of various committees and professional bodies; Evaluated UG, PG, and PHD Thesis works.

EDUCATION

B.E. in Electronics and Communication Engineering at Thanthai Periyar Govt. Inst. of Tech, Vellore-2, UNIVERSITY OF MADRAS, Average marks: 66.13%, completed at 2001

M.E. in Applied Electronics at College of Engineering Guindy, Chennai –25, ANNA UNIVERSITY, CHENNAI, CGPA: 7.804 in 10 point scale completed at 2005

Ph.D. in the Major area of Wireless Communication, with the title "Studying and Improving Energy Efficient On-Demand Routing Protocols in MANET", College of Engineering Guindy, Chennai –25, ANNA UNIVERSITY, CHENNAI, Guide : , 2013

RESEARCH INTERESTS

Wireless Communication, Signal Processing, Embedded Systems, Developing or Applying Bio-inspired Optimization Algorithms in various Engineering Domain according to its scope, Industry 4.0, Society 5.0, Cyber Physical System, Engineering Education by Blooms Taxonomy, Outcome Based Education and CDIO
25

Scopus Publications

341

Scholar Citations

10

Scholar h-index

10

Scholar i10-index

Scopus Publications

  • Squirrel search based localization for IoT enabled WSN in 5G networks
    T. Shankar, A. Rajesh, P. Sivasankar, Sai Pavan, Sivasurya Prakash Reddy
    Soft Computing, 2026
  • Detecting pattern irregularities in astronomical images using deep learning
    Shankar T, Bada Deekshitha, Vempalli Rohini, Venkataraman Muthiah Nakarajan, Sivasankar P, J Murali
    2024 3rd International Conference on Artificial Intelligence for Internet of Things Aiiot 2024, 2024
    Classification of astronomical images is a field of long standing interest. With modern technology, we have been able to obtain many techniques and consequently generated huge amounts and type of data. This amount of new and variety in astronomical data along with the complexities presents itself as a affair that a human analysis is not possible. In our project, we use deep learning techniques to explore the various challenges faced by astronomers when processing huge amounts of data, looking for information relevant to each target. We have implemented existing methods like InceptionV3 and CNN to detect and classify galaxies. Then we proposed to use VGG16, VGG19, and MobileNetV2 for classification and image segmentation to detect and classify galaxies. And we compared the performance of existing and proposed methods. Our proposal was approximately 20% more accurate than existing methods CNN and InceptionV3.
  • Prediction of Parkinson's disease with various ML and DL techniques on speech data
    T Shankar, Gummadapu Sreelekha, Challa Sai Tejaswini, P Sivasankar, N Lavanya, J Murali
    2024 3rd International Conference on Artificial Intelligence for Internet of Things Aiiot 2024, 2024
    Parkinson’s disease(PD) is a degenerative peripheral nervous system syndrome that influences muscle movement. It is incurable. Parkinson’s disease impacts more than one million people in India each year. Because of the disease’s degenerative nature, symptoms usually appear gradually and are barely perceptible, ranging from ordinary trembling of the hand to apparent speech, and voice, as well as writing alterations to serious symptoms such as loss of automatic movements. This research aims to contribute to the improvement of medical technology by assisting in the advanced and premature identification of PD, permitting experimental therapy by the use of a voice dataset from UCI Machine Learning(ML) database. We reviewed the current state of PD discernment in this study and discussed the prototype for quick identification of PD using several classifier propositions of ML and Deep Learning(DL). The best accuracy of about 94.8% was achieved by the usage of the CNN model with optimizer. We have also further built a web-based GUI for the web-based prediction of PD using model build.
  • Design of high sensitive hybrid honeycomb photonic crystal fiber for sensing C8H8O3/AsCl3/C8H10 analyte
    Shankar Thangavelu, A. Rajesh, Sivasankar Perumal, Sai Sravan, Chandini Mani
    Optical and Quantum Electronics, 2023
  • Unmanned aerial vehicle localization for device-to-device communication in fifth generation networks using modified penguin search optimization
    Shankar Thangavelu, Rajesh Anbazhagan, Sivasankar Perumal, Eeswar Gopikrishna, Muppalla Siddartha
    Computers and Electrical Engineering, 2023
  • Vulnerabilities Detection in Cybersecurity Using Deep Learning–Based Information Security and Event Management
    D Kothandaraman, S Shiva Prasad, P Sivasankar
    Artificial Intelligence and Deep Learning for Computer Network Management and Analysis, 2023
    Security information and event management (SIEM) is a technology used for security incident response and threat detection through a real-time acquisition and historical analysis of security events from a broad spectrum of contextual data sources. In fact, this technology is an intersection of two closely related technologies coined security event management (SEM) and security information management (SIM). Nowadays, many organizations find themselves at a distinct disadvantage when it comes to keeping their data safe and secure. As threats grow smarter and stealthier, attack surfaces grow larger and more difficult to defend. After deploying a SIEM, the SIEM analysts monitor user activity, avert data breaches, identify the root cause of security incidents, mitigate sophisticated cyber-attacks, and therefore help meet regulatory compliance requirements of any organizations. Also, various hosts have log security events that don’t have built-in incident detection features. These hosts can only observe events and produce audit log entries, instead of analysing the log entries to identify the signs of suspicious activities. In such a case, SIEM has the capability to correlate events across many hosts. It gathers events from different hosts and sees attacks divided into different parts and observed by distinct hosts, and then re-establish a variety of events to identify whether the attack has been successful or not. Thus, SIEM plays a vital role in improving the next-generation quality of data management in an organization against security attacks. Although traditional SIEM achieves better performance to detect the vulnerabilities in cybersecurity, it has some limitations, as follows: Since it collects all data regarding security events, this makes it hard to correlate security events, it depend on particular events and logs to detect certain threats, inability to monitor raw security events as they occur throughout the organization, and also it fails to monitor noise due to indiscrimination of useful or useless logs Doesn’t operate like other security controls such as firewalls, antivirus programs, intrusion detection systems (IDS), and intrusion prevention systems (IPS) Designed in such a way to utilize log data as recorded by other software tools Accidental misconfiguration can happen in several ways Collecting, storing, and analyzing security events are dreaded tasks that often involve ample money and a good deal of time Very slow in process and cannot reach 100% target achievement A legacy of SIEM systems cannot keep up with the rate at which security events need to be examined Relies on rules to parse all logged data; so it gives false positive alerts that produce an annoying noise across the silent and working environment of an enterprise SIEMs don’t have log management capabilities While many organizations have procured SIEMs, most are not properly configured or managed because the above-mentioned limitations are often cited as the main reasons for not deriving benefit from SIEMs. In this chapter and looking ahead, everything is headed toward cognitive innovation. Deep learning (DL) can be utilized to synergize data both from structured data sources and natural language, and that's what organizations want too. DL technology has gained success in the field of cybersecurity and has overcome limitations of SIEM-based vulnerability detection in cybersecurity. In this chapter, we will present and discuss basic solutions for solving cybersecurity issues through deep learning technique–based SIEM. When well-configured SIEM is paired with DL, SIEMs become even more effective and add significant value by reducing the amount of false positives and noise, which makes security analysts more productive in the security environment. The goal of adding DL to a SIEM is to reduce the time investment to create a baseline and tune with alerting without requiring highly experienced staff.
  • A Novel Technique to Improve Latency and Response Time of AI Models using Serverless Infrastructure
    Bhanu Sankar Ravi, Chepuri Madhukanthi, P Sivasankar, John Deva Prasanna
    6th International Conference on Inventive Computation Technologies Icict 2023 Proceedings, 2023
    Response time for AI-based models in time-critical applications is always a matter of concern. The situation is challenging when the model is deployed in a cloud-based infrastructure. To address this issue, a cloud-native development methodology called serverless infrastructure enables developers to create and execute applications without having to worry about managing servers. Generally, traditional systems require manual scaling, constant maintenance, and dedicated hardware resulting in high costs. To solve this, the AI model is deployed in serverless infrastructure services for hosting APIs that is to identify marine animals which have the potential to attack human beings at the seashores. The serverless infrastructure suffers from an initializing delay called cold start for occasional requests and hence the response time will be delayed even if the lambda function is free. The problem of cold starts is mitigated using the scheduler in the lambda function. The scheduler sends dummy requests to the server to keep the server warm and active. The AI model used as a test case utilizes Convolutional Neural Network Algorithms and Transfer Learning Technique, for detecting predators near the seashore. The model is deployed in a serverless infrastructure and has the benefits of automatic scaling, pay-per-use pricing, and decreased operational costs. The AI model is implemented in both serverless infrastructure and in Elastic Cloud Compute EC2. The performance of both systems was done for cost, latency, and response time. The proposed system provides promising results when compared to traditional server systems.
  • A Battery Monitoring System based on IoT for Electric Vehicles
    P Sasirekha, E Sneka, B Velmurugan, M Sahul Hameed, P Sivasankar
    Proceedings 5th International Conference on Smart Systems and Inventive Technology Icssit 2023, 2023
    Electric vehicles (EVs), which are considered as dynamic electrical energy storage units, are widely used because of their outstanding electrical characteristics and versatility. However, their widespread adoption has a significant adverse effect on the grid and carries the risk of harming their batteries when they become profoundly discharged. EV batteries require a precise state of charge estimation to minimize the lisk of damage, prolong their lifespan, and in order to safeguard the equipment power. Based on simplicity of implementation and reduced overall complexity, this study suggests a real-time Battery Monitoring System (BMS) employing the coulomb method of counting for SOC estimation and MQTT which is messaging-based as an internal communication protocol. Utilizing an ade quate central CPU, interfacing devices, and sensor technology, the proposed BMS is implemented. In order to monitor and regulate the discharging and charging of rechargeable battery packs, which increases the operational efficiency, battery management systems are important in electric vehide technology. Monitoring involves keeping a close eye on the important operating factors including voltage, current, fire, and temperature while charging and draining a battery. This is a hardware-timed sensor system that tracks various variables, like temperature, voltage, and fire and reports them on IOT so you can see exactly when everything has reached the right value.
  • AI based DDOS Attack Detection of SDN Network in Mininet Emulator
    Aditya Raj Yadav, Anant P Jain, Shankar T, A. Rajesh, Sivasankar Perumal, Geoffrey Eappen
    Vitecon 2023 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies Proceedings, 2023
    Software Defined Networking (SDN) is a network architecture of controlling the network devices through software applications. With SDN the network control can be achieve remotely without affecting network devices and reducing expenses of deploying infrastructure. Mininet SDN emulator and controllers provide a lightweight virtual platform for simulating network devices. Mininet emulator and Pox controller based on Transmission Control Protocol (TCP), Iperf3 and Hping3 can be use in testing scenarios which will depend upon throttling bandwidth to evaluate the performance of the emulator and controller by monitoring the throughput. Although having advantage of controlling the network, SDN exposes the network to vulnerable attacks which can be worse than traditional networks. Through this project we want to study the Artificial Intelligence (AI) Distributed Denial of Service (DDoS) attack on SDN network and explore a possible solution to prevent DDoS attacks using Machine Learning (ML). DDoS attack is type of DoS attack which make use of numerous distributed attack sources. Since every network in the system has an entropy and increase in the randomness causes entropy to decrease, we can use this concept to create ML classifiers to interpret the attack.
  • Block Chain based Grey Hole Detection Q Learning based CDS Environment in Cloud - MANET
    D.S. John Deva Prasanna, Dr.D. John Aravindhar, Dr.P. Sivasankar
    Webology, 2021
    Cloud MANET is a latest technique in which individual smart devices joins the Cloud MANET and can communicate in a distributed fashion. This is advantageous, as the Smart device does not need any infrastructural establishments. These nodes communicate together. Several MANETS formed in manner can be connected to cloud and can avail cloud services in real time. In this paper we attempt to establish a virtual backbone of Cloud MANET nodes using the concept Connected Dominating Sets, we also introduced a lightweight security scheme in order to avoid blackhole and greyhole attacks. The algorithm uses Q learning technique for learning about the capacity of nodes and establishes the CDS in Cloud MANET. The entire set up is established with public key infrastructure to emulate block chain based security. The concept of smart contract is used to ensure that every transaction is recorded and any compromised nodes in the CDS is discovered and eliminated.
  • CDS-Based Routing in MANET Using Q Learning with Extended Episodic Length
    D. S. John Deva Prasanna, D. John Aravindhar, P. Sivasankar
    Lecture Notes in Networks and Systems, 2021
  • 3-Axis Robot Arm Using Micro-Stepping with Closed-Loop Control
    G. A. Rathy, P. Sivasankar, Aravind Balaji, K. Gunasekaran
    Lecture Notes in Electrical Engineering, 2021
  • Hybrid PSO-HSA and PSO-GA algorithm for 3D path planning in autonomous UAVs
    B. Abhishek, S. Ranjit, T. Shankar, Geoffrey Eappen, P. Sivasankar, A. Rajesh
    SN Applied Sciences, 2020
  • Developing a knowledge structure using Outcome based Education in Power Electronics Engineering
    Rathy G.A., Sivasankar P, Gnanasambandhan T.G.
    Procedia Computer Science, 2020
  • Reinforcement learning based virtual backbone construction in manet using connected dominating sets
    D. Prasanna, D. Aravindhar, P. Sivasankar, Karthickeyan Perumal
    Journal of Critical Reviews, 2020
  • Treatment of Textile Wastewater by Coagulation–Flocculation Process Using Gossypium herbaceum and Polyaniline Coagulants
    Prakasam Arulmathi, Chellappa Jeyaprabha, Periandavan Sivasankar, Vadivel Rajkumar
    Clean Soil Air Water, 2019
  • Context-aware energy conserving routing algorithm for internet of things
    Kothandaraman D, Chellappan C, Sivasankar P, Syed Nawaz Pasha
    International Journal of Computer Networks and Communications, 2019
  • Successful computer forensics analysis on the cyber attack botnet
    Kavisankar Leelasankar, Chellappan C., Sivasankar P.
    Handbook of Research on Network Forensics and Analysis Techniques, 2018
  • Enhanced efficient SYN spoofing detection and mitigation scheme for DDoS attacks
    L. Kavisankar, C. Chellappan, S. Venkatesan, P. Sivasankar
    International Journal of Internet Technology and Secured Transactions, 2018
  • Efficient SYN spoofing detection and mitigation scheme for ddos attack
    L. Kavisankar, C. Chellappan, S. Venkatesan, P. Sivasankar
    Proceedings 2017 2nd International Conference on Recent Trends and Challenges in Computational Models Icrtccm 2017, 2017
  • Hybrid approach for optimal cluster head selection in wsn using leach and monkey search algorithms
    Journal of Engineering Science and Technology, 2017
  • Ppssm:push/pull smooth video streaming multicast protocol design and implementation for an overlay network
    T. Ruso, C. Chellappan, P. Sivasankar
    Multimedia Tools and Applications, 2016
  • A pioneer scheme in the detection and defense of DrDoS attack involving spoofed flooding packets
    L. Kavisankar, C. Chellappan, P. Sivasankar, A. Karthi, A. Srinivas
    Ksii Transactions on Internet and Information Systems, 2014
  • Performance evaluation of energy efficient on-demand routing algorithms for MANET
    P. Sivasankar, C. Chellappan, S. Balaji
    IEEE Region 10 Colloquium and 3rd International Conference on Industrial and Information Systems Iciis 2008, 2008
  • Cache based energy efficient strategies in mobile ad hoc networks
    IEEE International Conference on Personal Wireless Communications, 2005

RECENT SCHOLAR PUBLICATIONS

  • Squirrel search based localization for IoT enabled WSN in 5G networks
    T Shankar, A Rajesh, P Sivasankar, S Pavan, S Prakash Reddy
    Soft Computing, 1-11 , 2026
    2026
  • ML-Based Object Recognition and Object Picking Robot Using ROS
    GA Rathy, P Sivasankar, B AravindBalaji
    Journal of Technical and Vocational Education, NITTTR Chennai 26 (1), 90-92 , 2025
    2025
    Citations: 1
  • Detecting pattern irregularities in astronomical images using deep learning
    T Shankar, B Deekshitha, V Rohini, VM Nakarajan, P Sivasankar, J Murali
    2024 3rd International Conference on Artificial Intelligence For Internet of … , 2024
    2024
    Citations: 1
  • Prediction of Parkinson’s disease with various ML and DL techniques on speech data
    T Shankar, G Sreelekha, CS Tejaswini, P Sivasankar, N Lavanya, J Murali
    2024 3rd International Conference on Artificial Intelligence For Internet of … , 2024
    2024
  • Vulnerabilities detection in cybersecurity using deep learning–based information security and event management
    D Kothandaraman, SS Prasad, P Sivasankar
    Artificial intelligence and deep learning for computer network, 81-98 , 2023
    2023
    Citations: 6
  • A Novel Technique to Improve Latency and Response Time of AI Models using Serverless Infrastructure
    BS Ravi, C Madhukanthi, P Sivasankar, JD Prasanna
    2023 International Conference on Inventive Computation Technologies (ICICT … , 2023
    2023
    Citations: 4
  • A battery monitoring system based on IoT for electric vehicles
    P Sasirekha, E Sneka, B Velmurugan, MS Hameed, P Sivasankar
    2023 5th International Conference on Smart Systems and Inventive Technology … , 2023
    2023
    Citations: 20
  • CDS-Based Routing in MANET Using Q Learning with Extended Episodic Length
    DS John Deva Prasanna, D John Aravindhar, P Sivasankar
    Inventive Computation and Information Technologies: Proceedings of ICICIT … , 2021
    2021
    Citations: 1
  • Block Chain based Grey Hole Detection Q Learning based CDS Environment in Cloud-MANET.
    DSJD Prasanna, DJ Aravindhar, P Sivasankar
    Webology 18 (SI01), 88-106 , 2021
    2021
    Citations: 5
  • Successful Computer Forensics Analysis on the Cyber Attack Botnet
    K Leelasankar, C Chellappan, P Sivasankar
    Research Anthology on Combating Denial-of-Service Attacks, 151-166 , 2021
    2021
  • An efficient IoT based biomedical health monitoring and diagnosing system using myRIO
    GA Rathy, P Sivasankar, ZF Tamara
    TELKOMNIKA (Telecommunication Computing Electronics and Control) 18 (6 … , 2020
    2020
    Citations: 22
  • Hybrid PSO-HSA and PSO-GA algorithm for 3D path planning in autonomous UAVs
    B Abhishek, S Ranjit, T Shankar, G Eappen, P Sivasankar, A Rajesh
    SN Applied Sciences 2 (11), 1805 , 2020
    2020
    Citations: 103
  • IoT Based Smart Controlled Inverter
    SP GA Rathy , Gunasekaran K, Karthekeyan Perumal
    International Journal of Computer Trends and Technology 68 (4) , 2020
    2020
  • Reinforcement Learning Based Virtual Backbone Construction in MANET using Connected Dominating Sets
    Sivasankar. P, John Deva Prasanna. D. S, John Aravindhar, Karthikeyan Perumal
    Journal of Critical Reviews 7 (9), 146-152 , 2020
    2020
    Citations: 5
  • Estimation of SoC using SVM regression technique for an Efficient Electric Vehicle Battery Management System using c-RIO DAQ
    GK P.Sivasankar, G.A.Rathy, Karthikeyan Perumal
    American Journal of Research, 89-103 , 2020
    2020
    Citations: 2
  • A Study on Charging Infrastructure and the Topologies of Fast Charging Techniques in Electric Vehicle
    GAR P.Sivasankar
    International Journal of Engineering Applied Sciences and Technology 5 (2 … , 2020
    2020
    Citations: 5
  • Developing a knowledge structure using Outcome based Education in Power Electronics Engineering
    GA Rathy, P Sivasankar, TG Gnanasambandhan
    Elsevier Procedia Computer Science 172, 1026-1032 , 2020
    2020
    Citations: 31
  • 3-Axis Robot Arm Using Micro-Stepping with Closed-Loop Control
    GA Rathy, P Sivasankar, A Balaji, K Gunasekaran
    International Conference on Advanced Communication and Computational … , 2019
    2019
    Citations: 5
  • Context-aware energy conserving routing algorithm for internet of things
    D Kothandaraman, C Chellappan, P Sivasankar, SN Pasha
    International Journal of Computer Networks & Communications (IJCNC) Vol 11 , 2019
    2019
    Citations: 12
  • 3 axis robot arm using micro-stepping with closed loop control
    P Sivasankar, GA Rathy, AB Gunasekaran.K
    ICACCT 2019 , 2019
    2019

MOST CITED SCHOLAR PUBLICATIONS

  • Hybrid PSO-HSA and PSO-GA algorithm for 3D path planning in autonomous UAVs
    B Abhishek, S Ranjit, T Shankar, G Eappen, P Sivasankar, A Rajesh
    SN Applied Sciences 2 (11), 1805 , 2020
    2020
    Citations: 103
  • Developing a knowledge structure using Outcome based Education in Power Electronics Engineering
    GA Rathy, P Sivasankar, TG Gnanasambandhan
    Elsevier Procedia Computer Science 172, 1026-1032 , 2020
    2020
    Citations: 31
  • An efficient IoT based biomedical health monitoring and diagnosing system using myRIO
    GA Rathy, P Sivasankar, ZF Tamara
    TELKOMNIKA (Telecommunication Computing Electronics and Control) 18 (6 … , 2020
    2020
    Citations: 22
  • A battery monitoring system based on IoT for electric vehicles
    P Sasirekha, E Sneka, B Velmurugan, MS Hameed, P Sivasankar
    2023 5th International Conference on Smart Systems and Inventive Technology … , 2023
    2023
    Citations: 20
  • Performance evaluation of energy efficient on-demand routing algorithms for MANET
    P Sivasankar, C Chellappan, S Balaji
    2008 IEEE Region 10 and the Third international Conference on Industrial and … , 2008
    2008
    Citations: 19
  • Hybrid approach for optimal cluster head selection in WSN using leach and monkey search algorithms
    T Shankar, A Karthikeyan, P Sivasankar, A Rajesh
    Journal of Engineering Science and Technology 12 (2), 506-517 , 2017
    2017
    Citations: 18
  • Performance evaluation of energy efficient routing protocols for MANET
    P Sivasankar, C Chellappan, S Balaji
    International Journal of Computer Applications 975, 8887 , 2011
    2011
    Citations: 16
  • Context-aware energy conserving routing algorithm for internet of things
    D Kothandaraman, C Chellappan, P Sivasankar, SN Pasha
    International Journal of Computer Networks & Communications (IJCNC) Vol 11 , 2019
    2019
    Citations: 12
  • Efficient syn spoofing detection and mitigation scheme for ddos attack
    L Kavisankar, C Chellappan, S Venkatesan, P Sivasankar
    2017 second international conference on recent trends and challenges in … , 2017
    2017
    Citations: 12
  • Implementation of Smart Sleep Mechanism and Hybrid Data Collection Technique for Maximizing Network Lifetime in WSN's
    T Shankar, A Karthikeyan, P Sivasankar, RR Neha
    Indian Journal of Science and Technology 8, 1 , 2015
    2015
    Citations: 10
  • Cache based energy efficient strategies in mobile ad hoc networks
    K Murugan, S Balaji, P Sivasankar, S Shanmugavel
    2005 IEEE International Conference on Personal Wireless Communications, 2005 … , 2005
    2005
    Citations: 9
  • Ppssm: push/pull smooth video streaming multicast protocol design and implementation for an overlay network
    T Ruso, C Chellappan, P Sivasankar
    Multimedia Tools and Applications 75 (24), 17097-17119 , 2016
    2016
    Citations: 7
  • IOT based traffic monitoring using raspberry Pi
    P Sivasankar, B Brindhavathy
    Int. J. Res. Eng. Sci. Technol.(IJRESTs) 1 (7) , 2016
    2016
    Citations: 7
  • Vulnerabilities detection in cybersecurity using deep learning–based information security and event management
    D Kothandaraman, SS Prasad, P Sivasankar
    Artificial intelligence and deep learning for computer network, 81-98 , 2023
    2023
    Citations: 6
  • A pioneer scheme in the detection and defense of DrDoS attack involving spoofed flooding packets.
    L Kavisankar, C Chellappan, P Sivasankar, A Karthi, A Srinivas
    KSII Transactions on Internet & Information Systems 8 (5), 1726 , 2014
    2014
    Citations: 6
  • Block Chain based Grey Hole Detection Q Learning based CDS Environment in Cloud-MANET.
    DSJD Prasanna, DJ Aravindhar, P Sivasankar
    Webology 18 (SI01), 88-106 , 2021
    2021
    Citations: 5
  • Reinforcement Learning Based Virtual Backbone Construction in MANET using Connected Dominating Sets
    Sivasankar. P, John Deva Prasanna. D. S, John Aravindhar, Karthikeyan Perumal
    Journal of Critical Reviews 7 (9), 146-152 , 2020
    2020
    Citations: 5
  • A Study on Charging Infrastructure and the Topologies of Fast Charging Techniques in Electric Vehicle
    GAR P.Sivasankar
    International Journal of Engineering Applied Sciences and Technology 5 (2 … , 2020
    2020
    Citations: 5
  • 3-Axis Robot Arm Using Micro-Stepping with Closed-Loop Control
    GA Rathy, P Sivasankar, A Balaji, K Gunasekaran
    International Conference on Advanced Communication and Computational … , 2019
    2019
    Citations: 5
  • A Novel Technique to Improve Latency and Response Time of AI Models using Serverless Infrastructure
    BS Ravi, C Madhukanthi, P Sivasankar, JD Prasanna
    2023 International Conference on Inventive Computation Technologies (ICICT … , 2023
    2023
    Citations: 4

Publications

Books Published : 2 , Title of the Book : LabVIEW Programming Concepts with Examples, Authors : P.Sivasankar, G.A.Rathy, Publisher: Sci Tech publications, Year : 2015
Title of the Book : NG Smartphone Users Activity and Direction Detection using MQTT in IoT, Authors : Kothandaraman, D, P.Sivasankar, and Nagendar, Y Publisher: LAMBERT Academic Publishing, Year : 2019