Automatic Characterization of Exploitable Faults: A Machine Learning Approach

Characterization of the fault space of a cipher to filter out a set of faults potentially exploitable for fault attacks (FA), is a prob- lem with immense practical value. A quantitative knowledge of the ex- ploitable fault space is desirable in several applications, like security evaluation, cipher construction and implementation, design, and test- ing of countermeasures etc. In this work, we investigate this problem in the context of block ciphers. The formidable size of the fault space of a block cipher mandates the use of an automation to solve this prob- lem, which should be able to characterize each individual fault instance quickly. On the other hand, the automation is expected to be applicable to most of the block cipher constructions. Existing techniques for au- tomated fault attacks do not satisfy both of these goals simultaneously and hence are not directly applicable in the context of exploitable fault characterization. In this paper, we present a supervised machine learning (ML) assisted automated framework, which successfully addresses both of the criteria mentioned. The key idea is to extrapolate the knowledge of some existing FAs on a cipher to rapidly figure out new attack instances on the same. Experimental validation of the proposed framework on two state-of-the-art block ciphers – PRESENT and LED, establishes that our approach is able to provide fairly good accuracy in identifying exploitable fault instances at a reasonable cost. Finally, the effect of different S-Boxes on the fault space of a cipher is evaluated utilizing the framework

Prenos podataka, bezbednost i energetska efikasnost internet stvari (Internet of things) rešenja zasnovanih na tehnologiji bežičnih senzorskih mreža

Glavni doprinos ove doktorske teze jeste model procene potrošnje energije bežičnih senzorskih mreža za zadati skup protokola topologije i kriptografskih algoritama male računske i implementacione zahtevnosti. Predložena metoda procene potrošnje energije analizira se u simulacionom scenariju za nekoliko protokola i kriptografskih algoritama. Matematički model se testira u simulacionom okruženju gde se bežične senzorske mreže primenjuju kao tehnologija za komunikaciju na otvorenom području između senzorskih čvorova i uređaja zasnovanih na tehnologiji internet stvari. Rezultati simulacije potvrđuju formulu predloženu za procenu snage. Model predložen u ovoj tezi može se koristiti za odabir odgovarajućeg protokola topologije i kriptografskog algoritma. Na osnovu definisanog modela i rezultata simulacije predstavljena je sortirana lista kombinacija protokola topologije i algoritma šifrovanja. Najbolji rezultati u smislu potrošnje energije dobijaju se korišćenjem protokola A3 topologije i kriptografskog protokola KATAN64