Network Hardening: An Automated Approach to Improving by Lingyu Wang

By Lingyu Wang

This Springer short examines the instruments in response to assault graphs that support demonstrate community hardening threats. present instruments element all attainable assault paths resulting in serious community assets. although no present instrument presents an instantaneous strategy to get rid of the threats, they're a extra effective technique of community protection than depending completely at the adventure and abilities of a human analyst. Key historical past details on assault graphs and community hardening is helping readers comprehend the complexities of those instruments and methods. community Hardening: an automatic method of enhancing community protection is a important source for researchers and execs operating in community protection. it's also a great tool for advanced-level scholars excited about safety in laptop technological know-how and electric engineering.

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Extra info for Network Hardening: An Automated Approach to Improving Network Security

Sample text

Now, let us consider a different example showing how the value of k may have an impact on the optimality of the solution. Intuitively, the higher the value of k, the closer the computed solution is to the optimal one. 2. Consider the attack graph of Fig. fA3 g/ D 10.

Kaushik. Scalable, graph-based network vulnerability analysis. In Proceedings of ACM CCS’02, 2002. 2. Christian Blum and Andrea Roli. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. , 35(3):268–308, 2003. 3. R. Deraison. Nessus scanner, 1999. org. 4. Manfred GILLI and Peter WINKER. A review of heuristic optimization methods in econometrics. Swiss Finance Institute Research Paper Series 08–12, Swiss Finance Institute, 2008. 5. G. H. Osman. Metaheuristics: A bibliography.

Jha, R. M. Wing. Automated generation and analysis of attack graphs. In Proceedings of the IEEE S&P’02, 2002. Chapter 5 Linear-Time Network Hardening Abstract Attack graph analysis has been established as a powerful tool for analyzing network vulnerability. However, previous approaches to network hardening look for exact solutions and thus do not scale. Further, hardening elements have been treated independently, which is inappropriate for real environments. For example, the cost for patching many systems may be nearly the same as for patching a single one.

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