01392nas a2200205   4500008004100000022001400041245005100055210005100106260004200157300001000199490000600209520084000215653001801055653001201073653001901085653001601104653001201120100001801132856003601150       2014                        eng d  a1927-032100aAssessing the Intentions and Timing of Malware0 aAssessing the Intentions and Timing of Malware  aOttawabTalent First Networkc11/2014  a34-400 v43 aMalware has become a significant, complex, and widespread problem within the computer industry. It represents one of the most prevalent threats to cybersecurity and is increasingly able to circumvent current detection and mitigation techniques. To help better understand when a malware attack might happen, this article proposes an intention-based classification of malware and merges it with an optimal timing model to help predict the timing of malware based on its classification. The classification model is based on an examination of eight malware samples, and it identifies four malware classifications and commonalities based on the dimensions of persistence and stealth. The goal of the article is to provide a better understanding of when cyber-conflict will happen, and to help defenders better mitigate the potential damage.10acybersecurity10amalware10aoptimal timing10apersistence10astealth1 aMaheux, Brent  uhttp://timreview.ca/article/848