M. Sundarrajan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
M. Sundarrajan has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
A E Narayanan
Associate Professor, Computer Science and Engineering, Periyar Maniammai Institute of Science & Technology, Thanjavur, India
1 shared publication- Abdulmajeed Alqhatani
Department of Information Systems, College of Computer Science and Information Systems, Najran University
1 shared publication - Mehedi Masud
Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
1 shared publication - Noor Zaman Jhanjhi
Faculty of Engineering and Technology, Sunway University, Malaysia
1 shared publication - Prabakar Dakshinamoorthy
Department of Data Science and Business Systems, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, India
1 shared publication - Ramachandran Manikandan
Sastra university, India
1 shared publication
Latest Publications
- Open Access
- 30 March 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (7) , 6031
Energy Analysis-Based Cyber Attack Detection by IoT with Artificial Intelligence in a Sustainable Smart City
Cybersecurity continues to be a major issue for all industries engaged in digital activity given the cyclical surge in security incidents. Since more Internet of Things (IoT) devices are being used in homes, offices, transportation, healthcare, and other venues, malicious attacks are happening more frequently. Since distance between IoT as well as fog devices is closer than distance between IoT devices as well as the cloud, attacks can be quickly detected by integrating fog computing into IoT. Due to the vast amount of data produced by IoT devices, ML is commonly employed for attack detection. This research proposes novel technique in cybersecurity-based network traffic analysis and malicious attack detection using IoT artificial intelligence techniques for a sustainable smart city. A traffic analysis has been carried out using a kernel quadratic vector discriminant machine which enhances the data transmission by reducing network traffic. This enhances energy efficiency with reduced traffic. Then, the malicious attack detection is carried out using adversarial Bayesian belief networks. The experimental analysis has been carried out in terms of throughput, data traffic analysis, end-end delay, packet delivery ratio, energy efficiency, and QoS. The proposed technique attained a throughput of 98%, data traffic analysis of 74%, end-end delay of 45%, packet delivery ratio of 92%, energy efficiency of 92%, and QoS of 79%.
- 30 March 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (7) , 6031
Open AccessEnergy Analysis-Based Cyber Attack Detection by IoT with Artificial Intelligence in a Sustainable Smart City
Cybersecurity continues to be a major issue for all industries engaged in digital activity given the cyclical surge in security incidents. Since more Internet of Things (IoT) devices are being used in homes, offices, transportation, healthcare, and other venues, malicious attacks are happening more frequently. Since distance between IoT as well as fog devices is closer than distance between IoT devices as well as the cloud, attacks can be quickly detected by integrating fog computing into IoT. Due to the vast amount of data produced by IoT devices, ML is commonly employed for attack detection. This research proposes novel technique in cybersecurity-based network traffic analysis and malicious attack detection using IoT artificial intelligence techniques for a sustainable smart city. A traffic analysis has been carried out using a kernel quadratic vector discriminant machine which enhances the data transmission by reducing network traffic. This enhances energy efficiency with reduced traffic. Then, the malicious attack detection is carried out using adversarial Bayesian belief networks. The experimental analysis has been carried out in terms of throughput, data traffic analysis, end-end delay, packet delivery ratio, energy efficiency, and QoS. The proposed technique attained a throughput of 98%, data traffic analysis of 74%, end-end delay of 45%, packet delivery ratio of 92%, energy efficiency of 92%, and QoS of 79%.
- Open Access
- 1 February 2021
- Published by IOP Publishing in Journal of Physics: Conference Series
- Vol. 1767 (1) , 012055
Securing the MQTT Protocol using Enhanced Cryptographic techniques in IoT Surroundings
Protocol of MQTT - Message Queuing Telemetry Transport process is among the majority of lengthy procedures in IoT protocols. Nevertheless, this particular process doesn’t apply a solid protection pattern by default, and that doesn’t let a protected authentication mechanism between individuals within the reception. In addition, we can’t believe in the confidentiality as well as integrity of information. Little IoT products deliver additional and much smarter details within aspects of IoT and so on. This will make the protection issues within the protocols applied to the IoT particularly crucial. The standard format of MQTT process highly suggests apply it through Transport Layer Security (TLS) rather than basic TCP. Nevertheless, this particular alternative isn’t probable in many little products which form the IoT environment. In many cases, the constrained materials of IoT products stop the usage of protected asymmetric cryptography systems applied through itself. So, we suggest creating a safety scheme of MQTT process by means of Cryptographic techniques, for equally difficulties, the authentication schema and also the reliable information confidentiality & information integrity. We execute this particular protection schema without changing the conventional process emails. And lastly, we show a period benefits test utilizing a Java library.
- 1 February 2021
- Published by IOP Publishing in Journal of Physics: Conference Series
- Vol. 1767 (1) , 012055
Open AccessSecuring the MQTT Protocol using Enhanced Cryptographic techniques in IoT Surroundings
Protocol of MQTT - Message Queuing Telemetry Transport process is among the majority of lengthy procedures in IoT protocols. Nevertheless, this particular process doesn’t apply a solid protection pattern by default, and that doesn’t let a protected authentication mechanism between individuals within the reception. In addition, we can’t believe in the confidentiality as well as integrity of information. Little IoT products deliver additional and much smarter details within aspects of IoT and so on. This will make the protection issues within the protocols applied to the IoT particularly crucial. The standard format of MQTT process highly suggests apply it through Transport Layer Security (TLS) rather than basic TCP. Nevertheless, this particular alternative isn’t probable in many little products which form the IoT environment. In many cases, the constrained materials of IoT products stop the usage of protected asymmetric cryptography systems applied through itself. So, we suggest creating a safety scheme of MQTT process by means of Cryptographic techniques, for equally difficulties, the authentication schema and also the reliable information confidentiality & information integrity. We execute this particular protection schema without changing the conventional process emails. And lastly, we show a period benefits test utilizing a Java library.