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On Parallel Real-Time Security Improvement Using Mixed-Integer Programming
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DOI：10.1109/ACCESS.2021.3073089.png)
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Abstract
En 中文
Network security defenses evolve, responding to real-time attack incidents, modifying the underlying topology, or reallocating defense systems across the network. The present work emphasizes reducing the time to compute new optimal reallocations of defense systems, responding to emerging real-time remote attacks. The proposed heuristic method utilizes parallel processing by slicing the underlying graphical model representing the network topology, solving in parallel multiple mixed-integer programming problems corresponding to the created subgraphs, and producing an estimate of the optimal defense. The parallelized method to compute a new defense enables producing a response, in real-time, before remote attackers compromise a target machine in the network. Our prototype tool to compute a new defense, the high-performance security analyzer, has a speedup of at least 20 over solving the original problem using a serial algorithm, and with an insignificant difference between the performance of the (computed in parallel) approximately optimal defense and the (serially computed) optimal defense. A major conclusion is that further speedups will come from parallel integer programming algorithms rather than from graph partitioning.
Keywords:
Security
Optimization
Real-time systems
Computational modeling
Probabilistic logic
Parallel processing
Bayes methods
Security management
parallel processing
tree graphs
mathematical programming
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