Dr. Yabesh Abraham Durairaj Isravel
@sacas.ac.in
Associate Professor and School of Management
S. A. College of Arts & Science
RESEARCH, TEACHING, or OTHER INTERESTS
Organizational Behavior and Human Resource Management, General Business, Management and Accounting, Social Sciences, Business, Management and Accounting
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Suresh Kumar Kollapudi, Yabesh Abraham Durairaj Isravel, Rakesh Natesan, and Satheesh Kumar Subramaniyan
AIP Publishing
Gurusubramani S, N. Arockia Rosy, D Chitra, Anwar Basha H, Yabesh Abraham Durairaj Isravel, and Pundru Chandra Shaker Reddy
IEEE
As the frequency of security breaches continues to climb, cyber-security remains a major concern across all industries operating online. Because of the proliferation of new protocols, most of which originate with the Internet-of-Things(IoT), thousands of new zero-day attacks appear every day. Cyberattacks on the IoT have skyrocketed due to the proliferation of connected devices and the inherent security flaws in many network infrastructures. The safety of those systems depends on the ability to recognize and categorize harmful communications. This recommends that even cutting-edge methods, like conventional machine learning (ML) systems, have trouble spotting these atypical, yet dangerous, mutations in attacks over time. However, deep learning's (DL) widespread success in big data applications has piqued the curiosity of many in the cybersecurity community. In order to address multiple potential entry points at once, the authors of this research employ a distributed-framework built on DL to do so. The feedforward neural-network(FFNN) and the long short-term memory (LSTM) are two DL strategies that are compared and contrasted. Both the NSL-KDD and the BoT-IoT datasets are used to test the models' abilities to detect and prevent various cyberattacks. Accuracy of up to 99.98% was achieved across all configurations, proving that the proposed distributed system is successful in detecting multiple classes of cyberattacks.
Yabesh Abraham Durairaj Isravel, B. Lakshmi, V. Mahalakshmi, and D. Chitra
Inderscience Publishers
B. Lakshmi, Yabesh Abraham Durairaj Isravel, D. Chitra, and V. Mahalakshmi
Inderscience Publishers
V. Mahalakshmi, D. Chitra, Yabesh Abraham Durairaj Isravel, and B. Lakshmi
Springer International Publishing
D. Chitra, V. Mahalakshmi, B. Lakshmi, and Yabesh Abraham Durairaj Isravel
Inderscience Publishers
Yabesh Abraham Durairaj Isravel, Lakshmi Balakrishnan, V. Mahalakshmi, and Chitra Devarajulu
Inderscience Publishers
This paper empirically analysed Employee Engagement in the NBFC’s located in the Districts of Chennai, Kancheepuram and Thiruvallur of Tamilnadu, India, by considering the three dimensions such as, Vigor, Absorption and Dedication. The respondents for the study were 321 employees employed with different NBFC’s located in the Districts of Chennai, Kancheepuram and Thiruvallur of Tamilnadu, India. The result of the study showed that there are more respondents with High level of Employee Engagement and in the Dimensions of Employee Engagement, more respondents have Low level of Vigor; and Moderate level of Dedication and Absorption.