Home>Articles>Fingerprinting Malicious Code Through Statistical Opcode Analysis
Fingerprinting Malicious Code Through Statistical Opcode Analysis
by Daniel Bilar
AUTHORS' DESCRIPTION
This paper discusses a detection mechanism for malicious code through statistical analysis of opcode distributions. 67 malware executables were sampled and their opcode frequency distribution statistically compared with the aggregate statistics of twenty non-malicious samples. It was found that malware opcode distributions differ statistically significantly from non-malicious software. Furthermore, rare opcodes seem to be a stronger predictor, explaining 12-63% of frequency variation.
Home>Articles>Fingerprinting Malicious Code Through Statistical Opcode Analysis
IMPORTANT! Installing computer monitoring tools on computers you do not own or do not have permission to monitor may violate local, state or federal law.
