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Building APT Malicious Attacker Profiles for Power Monitoring Systems with Machine Learning
In order to meet the demand for building APT Attacker Profiles for power monitoring systems, this paper designs an APT Attacker Profiles construction method from the hidden, variable and organized nature of APT attacks, using multiple machine learning algorithms, building an APT attack organization framework, displaying a topology map, and verifying, dismantling and reconstructing the entire APT Attacker Profiles in a " point", “line” and “surface”, we design and test four experiments with completely different directions, and use them to verify, disassemble and reconstruct the whole APT Attacker Profiles. Finally, through the results of the experiments, the construction method of the traceability system for APT attackers is further introduced. It is more comprehensive than the APT study that proposes feature construction prevention alone, more in-depth than the study that only constructs APT Attacker Profiles, and more detailed than the APT study that introduces constructing system models alone.
Building APT Malicious Attacker Profiles for Power Monitoring Systems with Machine Learning
In order to meet the demand for building APT Attacker Profiles for power monitoring systems, this paper designs an APT Attacker Profiles construction method from the hidden, variable and organized nature of APT attacks, using multiple machine learning algorithms, building an APT attack organization framework, displaying a topology map, and verifying, dismantling and reconstructing the entire APT Attacker Profiles in a " point", “line” and “surface”, we design and test four experiments with completely different directions, and use them to verify, disassemble and reconstruct the whole APT Attacker Profiles. Finally, through the results of the experiments, the construction method of the traceability system for APT attackers is further introduced. It is more comprehensive than the APT study that proposes feature construction prevention alone, more in-depth than the study that only constructs APT Attacker Profiles, and more detailed than the APT study that introduces constructing system models alone.
Building APT Malicious Attacker Profiles for Power Monitoring Systems with Machine Learning
Cao, Yang (author) / Su, Yang (author) / Guo, Shuyang (author) / Wang, Hao (author)
2023-12-01
1871678 byte
Conference paper
Electronic Resource
English