dc.contributor.authorYap, Yao Ming
dc.description.abstractExpansion of attack vectors via fuzzing was achieved by acquiring relevant seeds from a large corpus in a short time span. We present a framework capable of extracting, categorising and managing object streams from fuzzing seeds according to type and relevance. Heuristic function of the framework was built upon experimentation and investigation into object streams. The result is a framework capable of processing a 78KB file with multiple objects in 29 seconds, a vast improvement in comparison to similar average timing for manual processing of only 1 object. 100 small to medium sized PDF (< 1000KB each) in 49 minutes. 14 seeds processed by framework were fuzzed using Failure Observation Engine (FOE) 2.1, each with minimum 50k iterations. No crashes were produced.en_US
dc.format.extent59 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineering::Software::Software engineeringen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Software::Operating systemsen_US
dc.titleHacking of the world : investigation on expansion of attack vectorsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLiu Yangen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.researchCentre for Computational Intelligenceen_US

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