Effective and Reliable Malware Group Classification for a Massive Malware Environment

摘要: Most of the cyber-attacks are caused by malware, and damage from them has escalated cyber space to home appliances infrastructure, thus affecting daily living people. As such, anticipative analysis countermeasures for malware have become more important. programs created as variations existing malware. This paper proposes a scheme detection group classification some measures improve dependability using local clustering coefficient, technique selecting managing leading each classify cost-effectively in massive environment. study also developed system proposed model compared its performance with methods on actual verify level improvement. The technology this is expected be used effective new trend same group, automatic identification interest, attacker addition program.