N SREEKANTH

@mallareddyecw.com

PROFESSOR & HOD / ELECTRONICS AND COMMUNICATION ENGINEERING (ECE)
Malla Reddy Engineering College for Women

RESEARCH INTERESTS

MICROWAVE ANTENNAS, COMMUNICATIONS, IMAGE & SIGNAL PROCESSING

5

Scopus Publications

Scopus Publications

  • Ensemble Framework of Artificial immune system based on Network Intrusion Detection System for Network Security Sustainability
    Sarangam Kodati, Nara Sreekanth, K.S.R.K. Sarma, P. Chandra Sekhar Reddy, Archana Saxena, and Boya Palajonna Narasaiah

    EDP Sciences
    The popularity and rapid growth of the internet have reemphasized the importance of intrusion detection systems (IDS) significance in the network security. IDS decreases hacking, data theft risk, privacy intrusion, and others. To save the system from external and internal intruders, the primary approaches of IDS are used. Many techniques[13], like genetic algorithms, artificial neural networks, and artificial immune systems, have been applied to IDS. This paper describes an Ensemble Framework of Artificial Immune System (AIS) based on Network Intrusion Detection System. Without placing a significant additional load on networks and monitoring systems, the large volume of data is analysed by a network-based Intrusion Detection System (NIDS). For determining the connection type, data from KDD Cup 99 competitions is utilized. To differentiate between attacks and valid connections, IDS can be utilized. Optimized feature selection is used to speed up the time-consuming rough set. The results obtained from the IDS system indicate that it can effectively identify the attacking connections with a high success rate.

  • Fusion-Based Celebrity Profiling Using Deep Learning
    K. Adi Narayana Reddy, Naveen Kumar Laskari, G. Shyam Chandra Prasad, and N. Sreekanth

    Springer Nature Singapore

  • Analysis of Heart Disease Data Using K-Means Clustering Algorithm in Orange Tool
    Sarangam Kodati, Kumbala Pradeep Reddy, G. Ravi, and Nara Sreekanth

    Springer Singapore

  • Region based age classification using cross diagonal centre symmetric motif matrix (CD-CS-MM)


  • Age classification based on appearance model using local ternary direction pattern approach