Comprehensive Review of Cybercrime Detection Techniques
dc.cclicence | CC-BY | en |
dc.contributor.author | Ahmed, Abdulghani Ali | |
dc.contributor.author | Al-Khater, Wadha Abdullah | |
dc.contributor.author | Al-Maadeed, Somaya | |
dc.contributor.author | Sadiq, Ali Safaa | |
dc.contributor.author | Khan, Muhammad Khurram | |
dc.date.accessioned | 2020-11-02T16:20:11Z | |
dc.date.available | 2020-11-02T16:20:11Z | |
dc.date.issued | 2020-07-22 | |
dc.description | © 2020 The Authors. Published by IEEE. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1109/ACCESS.2020.3011259 | en |
dc.description.abstract | Cybercrimes are cases of indictable offences and misdemeanors that involve computers or communication tools as targets and commission instruments or are associated with the prevalence of computer technology. Common forms of cybercrimes are child pornography, cyberstalking, identity theft, cyber laundering, credit card theft, cyber terrorism, drug sale, data leakage, sexually explicit content, phishing, and other forms of cyber hacking. They mostly lead to a privacy breach, security violation, business loss, financial fraud, or damage in public and government properties. Thus, this study intensively reviews cybercrime detection and prevention techniques. It first explores the different types of cybercrimes and discusses their threats against privacy and security in computer systems. Then, it describes the strategies that cybercriminals may utilize in committing these crimes against individuals, organizations, and societies. It also reviews the existing techniques of cybercrime detection and prevention. It objectively discusses the strengths and critically analyzes the vulnerabilities of each technique. Finally, it provides recommendations for the development of a cybercrime detection model that can detect cybercrimes effectively compared with the existing techniques. | en |
dc.funder | Other external funder (please detail below) | en |
dc.funder.other | Qatar National Research Fund (a member of the Qatar Foundation). | en |
dc.identifier.citation | Al-Khater, W.A., Al-Maadeed, S., Ahmed, A.A., Sadiq, A.S. and Khan, M.K. (2020) Comprehensive Review of Cybercrime Detection Techniques. IEEE Access, 8, pp. 137293-137311 | en |
dc.identifier.doi | https://doi.org/10.1109/ACCESS.2020.3011259 | |
dc.identifier.issn | 2169-3536 | |
dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/20353 | |
dc.language.iso | en | en |
dc.peerreviewed | Yes | en |
dc.projectid | NPRP grant # NPRP12S-0312-190332 | en |
dc.publisher | IEEE | en |
dc.researchinstitute | Cyber Technology Institute (CTI) | en |
dc.subject | Security | en |
dc.subject | Cybercrime detection techniques | en |
dc.subject | Neural network | en |
dc.subject | Fuzzy logic | en |
dc.subject | Machine learning | en |
dc.subject | Data mining | en |
dc.title | Comprehensive Review of Cybercrime Detection Techniques | en |
dc.type | Article | en |
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