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This paper describes a data driven approach to studying the science of cyber security (SoS). It argues that science is driven by data. It then describes issues and approaches towards the following three aspects: (i) Data Driven Science for Attack Detection and Mitigation, (ii) Foundations for Data Trustworthiness and Policy-based Sharing, and (iii) A Risk-based Approach to Security Metrics. We believe...
Machine learning models deployed in real world applications, operate in a dynamic environment where the datadistribution can change constantly. These changes, calledconcept drifts, cause the performance of the learned modelto degrade over time. As such it is essential to detect andadapt to changes in the data, for the model to be of any realuse. While, model adaptation requires labeled data (for retraining),...
Data from computer log files record traces of events involving user activity, applications, system software and network traffic. Logs are usually intended for diagnostic and debugging purposes, but their data can be extremely useful in system audits and forensic investigations. Logs created by intrusion detection systems, web servers, antivirus and anti-malware systems, firewalls and network devices...
The Traveling Salesman Problem (TSP) was first formulated in 1930 and is one of the most studied problems in optimization. If the optimal solution to the TSP can be found in polynomial time, it would then follow that every NP-hard problem could be solved in polynomial time, proving P=NP. It will be shown that our algorithm finds P~NP with scale. Using a δ –ε proof, it is straightforward to show that...
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