A novel cyber security capability

摘要: This paper presents a new approach to infer worldwide malware-infected machines by solely analyzing their generated probing activities. In contrary other adopted methods, the proposed does not rely on symptoms of infection detect compromised machines. allows inference malware at very early stages contamination. The aims detecting whether are infected or as well pinpointing exact type/family. latter insights allow network security operators diverse organizations, Internet service providers and backbone networks promptly clients' in addition effectively providing them with tailored anti-malware/patch solutions. To achieve intended goals, exploits darknet space initially filters out misconfiguration traffic targeting such using probabilistic model. Subsequently, employs statistical methods large-scale activities perceived dark space. Consequently, correlated samples leveraging fuzzy hashing entropy based techniques. is empirically evaluated recent 60 GB real 65 thousand samples. results concur that rationale exploiting for detection indeed promising. Further, results, which were validated publically available data resources, demonstrate extracted inferences exhibit noteworthy accuracy can generate significant cyber could be used effective mitigation.