Title: AI/ML-driven network cyber anomaly prediction
Project ID: 0exq325
Domain(s): Machine Learning,Systems Engineering,Data Science,Artificial Intelligence,Cybersecurity
Description:
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.
Desired Skills:
Artificial Intelligence (AI), Machine Learning, Cyber Security, Network Analysis, Computer Science, Data Science.
Clearance-
US Citizenship Required: No
Active Clearance or Background Investigation Required: No
Level Needed:
Team Information-
Targeted Students: Grad
Team Size: 2 to 4
Details:
Specific Requirements-
Focus on Particular University: No
Details:
Timeline-
Focus Timeline: Yes
Details: Two semesters
Funding-
Potential Funding:No
Note: Availability of funds not guaranteed
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