Performance Analysis of Various Machine Learning based Algorithms on Cyber security Approaches
Mr. VS.Pavan Kumar
, Dr.S.Arivalagan , Dr.M.Murugesan , Dr.P.Sudhakar
Cybersecurity; Machine learning; Cyberattacks; Data driven models; Security; Artificial Intelligence
Pervasive use and development of the Internet and its mobile applications extended cyberspace. Cyberspace is prone to prolong and automated cyber-attacks. Cyber security methods render advancements in security measures to find cyberattacks. Conventional security systems are ineffective as cybercriminals were smart enough to avoidclassical security systems. Traditional security system is ineffective in identifying polymorphic security attacks. Machine learning (ML) approaches had a significant contributiontovarious applications of cybersecurity. In spite of the success, there exist certain difficultiesin assuringthe reliability of the ML mechanism. There were incentivized malicious adversariespresented in cyberspace that are ready to use these ML vulnerabilities. This study offers a detailed examination of various ML models to detect cyberattacks and accomplish cybersecurity. This study presents a detailed discussion of existing ML models for cyber security comprising intrusion detection, spam detection, and malware detection in recent days. In addition, the basic concepts of cybersecurity and cyberattacks are elaborated in detail. In addition, we have discussed the existing ML models for cybersecurity along with their aim, methodology, and experimental data. At the end of the study, a detailed overview of cybersecurity, cyberattacks, and recent cyberattack detection models are elaborated briefly.
"Performance Analysis of Various Machine Learning based Algorithms on Cyber security Approaches", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.300 - 306, March-2023, Available :https://ijsdr.org/papers/IJSDR2303050.pdf
Volume 8
Issue 3,
March-2023
Pages : 300 - 306
Paper Reg. ID: IJSDR_204379
Published Paper Id: IJSDR2303050
Downloads: 000347183
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
