Malicious Detection Based on ReliefF and Boosting Multidimensional Features

@article{Luo2015MaliciousDB,
  title={Malicious Detection Based on ReliefF and Boosting Multidimensional Features},
  author={Yangxia Luo},
  journal={J. Commun.},
  year={2015},
  volume={10},
  pages={910-917}
}
—Aiming at the problem of large overhead and low accuracy on the identification of obfuscated and malicious code, a new algorithm is proposed to detect malicious code by identifying multidimensional features based on ReliefF and Boosting techniques. After a disassembly analysis and static analysis for the clustered malicious code families, the algorithm extracts features from four dimensions: two static properties (operation code sequences and bytecode sequence) and two features (system call… 

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