Skynet: a Cyber-Aware Intrusion Tolerant Overseer.

DSN-S(2023)

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摘要
The increasing level of sophistication of cyber attacks which are employing cross-cutting strategies that leverage multi-domain attack surfaces, including but not limited to, software defined networking poisoning, biasing of machine learning models to suppress detection, exploiting software (development), and leveraging system design deficiencies.While current defensive solutions exist, they only partially address multi-domain and multi-stage attacks, thus rendering them ineffective to counter the upcoming generation of attacks. More specifically, we argue that a disruption is needed to approach separated knowledge domains, namely Intrusion Tolerant systems, cybersecurity, and machine learning.We argue that current solutions tend to address different concerns/facets of overlapping issues and they tend to make strong assumptions of supporting infrastructure, e.g., assuming that event probes/metrics are not compromised.To address these issues, we present Skynet, a platform that acts as a secure overseer that merges traditional roles of SIEMs with conventional orchestrators while being rooted on the fundamentals introduced by previous generations of intrusion tolerant systems. Our goal is to provide an open-source intrusion tolerant platform that can dynamically adapt to known and unknown security threats in order to reduce potential vulnerability windows.
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关键词
Intrusion Tolerance,Cybersecurity,Machine Learning,System Design
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