Performance Evaluation of Artificial Intelligence Enabled Intrusion Detection System with Encryption Scheme for Network Security
Mrs.Swapna Sunkara
, Dr.T.Suresh , Dr.V.Sathiyasuntharam
Network security; Artificial intelligence; Intrusion detection system; Encryption; Machine learning
Network security refers to the exercise of prevention of the unauthorized access of computer networks or their related devices and it comes under cybersecurity. In simpler terms protecting devices and network servers physically from external threats, along with that takinginitiative for network security. In a time of increasingly complicated cyberattacks, network security becomeshighly important. Two major solutions to accomplish network security are intrusion detection systems (IDS) and encryption. Intrusion Detection System (IDS) meansa system that would monitornetwork traffic for doubtful activity and grants alerts once the activity is found.Machine learning (ML) and deep learning (DL) models can be applied to design effective IDS models. On the other hand, encryption schemes can be developed to secure network data. Recently, numerous research works have been developed for attaining network security. This paper performs a study of various artificial intelligence (AI) techniques for IDS and encryption in network security. A detailed overview of various concepts involved in network security is elaborated. In addition, different IDS and encryption techniques can be derived to improve network efficiency. At last, a detailed experimental analysis is performed to demonstrate the performance of different models interms of different measures.
"Performance Evaluation of Artificial Intelligence Enabled Intrusion Detection System with Encryption Scheme for Network Security", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 9, page no.368 - 374, September-2022, Available :https://ijsdr.org/papers/IJSDR2209060.pdf
Volume 7
Issue 9,
September-2022
Pages : 368 - 374
Paper Reg. ID: IJSDR_201638
Published Paper Id: IJSDR2209060
Downloads: 000347240
Research Area: Engineering
Country: -, -, --
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
