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Found 4 papers, 3 papers with code
MEUZZ: Smart Seed Scheduling for Hybrid Fuzzing
Seed scheduling is a prominent factor in determining the yields of hybrid fuzzing.
Microsoft Malware Classification Challenge
The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0. 5 terabytes, consisting of disassembly and bytecode of more than 20K malware samples.
Cryptography and Security
IntelliAV: Building an Effective On-Device Android Malware Detector
Several anti-malware vendors have claimed and advertised the application of machine learning in their products in which the inference phase is performed on servers and high-performance machines, but the feasibility of such approaches on mobile devices with limited computational resources has not yet been assessed by the research community, vendors still being skeptical.
Cryptography and Security
Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification
This paradigm is presented and discussed in the present paper, where emphasis has been given to the phases related to the extraction, and selection of a set of novel features for the effective representation of malware samples.
