By Kazuto Ogawa, Katsunari Yoshioka
This e-book constitutes the refereed complaints of the eleventh overseas Workshop on safety, IWSEC 2016, held in Tokyo, Japan, in September 2016. The 15 common papers and four brief papers awarded during this quantity have been conscientiously reviewed and chosen from fifty three submissions. They have been prepared in topical sections named: method protection; searchable encryption; cryptanalysis; permutation and symmetric encryption; privateness holding; protection; post-quantum cryptography; and paring computation.
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Additional info for Advances in Information and Computer Security: 11th International Workshop on Security, IWSEC 2016, Tokyo, Japan, September 12-14, 2016, Proceedings
Even if the structure of a FRAM does not change with detections, its probabilities of conditions and attack sources can be updated. For example, the condition probability of a vulnerability that has already been exploited is set to “1”. The way FRAMs are built and cycles solved is identical to the DRCMs, starting from an attack source rather than from a target. See Sects. 4 for more details. Model nodes. A FRAM is a Bayesian Network with 5 types of nodes, each one representing a Boolean random variable.
Its CPT is the same as DRCM Attack Steps. – A FRAM Condition represents the random variable describing that the condition of an attack step is veriﬁed. Its a priori probability is the same as DRCM Conditions. Figure 6 shows an example of a Future Risk Assessment Model starting from host h1 in a topology of 3 hosts. The FRAM Attack Source is represented by a ﬁve-sided shape, FRAM Topological Assets by a rectangle shape, FRAM Attack Steps by a diamond shape, and FRAM Conditions by an oval shape. Probability reconciliation in FRAMs.
In each subnet, all accesses between hosts are authorised. Each host has 30 random vulnerabilities for a maximum total of around 3600 vulnerabilities. 1 Performances To evaluate the performances of the model, we ﬁrst generate the topological attack graphs of the simulated topologies. Then, for each simulation, we generate one random attack scenario of 7 successive attack steps, to which are added false positives and steps with no sensor information. Finally, we evaluate the HRAM. Figure 7b shows the duration in seconds of the generation of the HRAM (TAG generation then DRCM and FRAM) on such topologies, with one scenario of 7 attack steps.
Advances in Information and Computer Security: 11th International Workshop on Security, IWSEC 2016, Tokyo, Japan, September 12-14, 2016, Proceedings by Kazuto Ogawa, Katsunari Yoshioka