Computer Science Collection, Forsyth Library Database
“Machine learning false positives” with a limiter of “Articles Only”
23 Results
The search was useful as it provided me with results that were directly relevant to my research question.
Muhammad, Musa Abubakar, and Aladdin Ayesh. “A Behaviour Profiling Based Technique for Network Access Control Systems.” International Journal of Cyber-Security and Digital Forensics, vol. 8, no. 1, Jan. 2019, pp. 23+. Gale OneFile: Computer Science, link.gale.com/apps/doc/A607390802/CDB?u=klnb_fhsuniv&sid=bookmark-CDB&xid=93415a45. Accessed 29 Oct. 2021.
The article above discusses a technique used by network access control systems. The technique is able to develop profiles of normal behavior. By setting this baseline the system is able to determine what is abnormal traffic. By looking at differences in traffic the behavioral technique establishes patterns.
Applied Science & Technology, Forsyth Library Database
“Machine learning improvements” with a limiter of “Articles Only”
30 Results
The search was very helpful as it found direct results considering machine learning in cybersecurity.
Batyha, R. M., Aburashed, T. K., & Alshammari, B. R. (2021). Difficulties Faced and Applications of Machine Learning in Cyber-Security. International Journal of Advances in Soft Computing & Its Applications, 13(2), 162–172.
This article discusses the difficulties facing machine learning in cybersecurity. This has been the most useful, directly-related article I have found. It discusses the inefficiencies in machine learning systems used in cybersecurity. Software is always being changed and new things are being developed. This can be troubling for machine learning because if it comes across something that is new but not malicious and blocks it, it can result in issues for business operations.
Computer Science Collection, Forsyth Library Database
“Machine learning improvements” with a limiter of “Articles Only”
26 Results
The search was not as useful but still provided me with key information that helped me better understand what my research is about.
Lo, O., Buchanan, W. J., Griffiths, P., & Macfarlane, R. (2018). Distance Measurement Methods for Improved Insider Threat Detection. Security and Communication Networks, 2018. https://link.gale.com/apps/doc/A596644750/CDB?u=klnb_fhsuniv&sid=bookmark-CDB&xid=418c79dd
This article offers methods to improve insider threat detection. However, it widely discusses the uses of machine learning as a tool. Machine learning has its negatives because it does not always directly understand the behavior of users and how it can change. This is what leads to false positives and negatives.
Applied Science & Technology, Forsyth Library Database
“Machine learning cybersecurity” with a limiter of “Articles Only”
9 Results
The search was helpful but still missed key points that I was looking for, however, it did help me better understand how cybersecurity and machine learning interact.
Liu, S., Lin, G., Han, Q.-L., Wen, S., Zhang, J., & Xiang, Y. (2020). DeepBalance: Deep-Learning and Fuzzy Oversampling for Vulnerability Detection. IEEE Transactions on Fuzzy Systems, 28(7), 1329–1343. https://doi-org.ezproxy.fhsu.edu/10.1109/TFUZZ.2019.2958558
The article above discusses machine learning and how it must be improved to be a consistent, useful tool for cybersecurity. This type of improvement would need to account for false positives and negatives in ensuring they are mitigated.