Title: AI\/ML-driven network cyber anomaly prediction
\nProject ID: 0exq325
\nDomain(s): Machine Learning,Systems Engineering,Data Science,Artificial Intelligence,Cybersecurity<\/p>\n
Description:<\/p>\n
By leveraging machine learning algorithms, AI can learn from historical data, recognize patterns, and make accurate predictions about future anomalies. Potential goals: (a) Use AI\/ML to analyze network behavior and predict potential cyber security threats\/anomalies based on network activity, behavior, and system history. (b) Implement AI\/ML to automatically create recommendations for system configuration changes to mitigate cyber threats. (c) Employ AI\/ML to automatically categorize predicted cyber security threats\/anomalies (Data breach, compromised user account, system config change, etc.). It is entirely acceptable to adapt and repurpose existing codes found in open-source libraries or those that are available commercially. <\/p>\n
Desired Skills:
\nArtificial Intelligence (AI), Machine Learning, Cyber Security, Network Analysis, Computer Science, Data Science. <\/p>\n
US Citizenship Required: No
\nActive Clearance or Background Investigation Required: No
\nLevel Needed: <\/p>\n
Targeted Students: Grad
\nTeam Size: 2 to 4
\nDetails: <\/p>\n
Focus on Particular University: No
\nDetails: <\/p>\n
Focus Timeline: Yes
\nDetails: Two semesters<\/p>\n
Potential Funding:No
\nNote: Availability of funds not guaranteed<\/p>\n