Intruder Detection Using Fuzzy Min-Max Neural Network and A Principal Component Analysis (PCA) in Network Data

Al-Dubai, Ahmad; Humbe, V. H.; Chowhan, S. S.; Aldubai, Y.F.

doi:10.26438/ijcse/v5i12.109117

Cited by 2 publications

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Comprehensive Review of Cybercrime Detection Techniques

et al. 2020

View full text Add to dashboard Cite

Cybercrimes describe cases of indictable offences and misdemeanours in which computer or any communication tools are involved as targets, commission instruments, incidental to, or that cases are associated with the prevalence of computer technology. Common forms of cybercrimes could be child pornography, cyberstalking, identity theft, cyber laundering, credit card theft, cyber terrorism, drug sale, data leakage, sexually explicit content, phishing and other cyber hacking. These kinds of cybercrimes are mostly leading to breaching users' privacy, security violation, business loss, financial fraud, or damage in public as well as government properties. Hence, this paper intensively reviews cybercrime detection and prevention methods. It first explores the different types of cybercrimes then discusses their threats against privacy and security in computer systems. It also describes the strategies that cybercriminals might utilize in committing these crimes against individuals, organizations, and societies. The paper then reviews the existing techniques of cybercrime detection and prevention. It objectively discusses the strengths and critically analyses the vulnerabilities of each technique. As a future study, the paper provides recommendations for the development of cybercrime detection model in which it is capable to effectively detect cybercrime in comparison to the existing techniques.

show abstract