Author List: Guo, Hong; Cheng, Hsing Kenneth; Kelley, Ken;
Journal of Management Information Systems, 2016, Volume 33, Issue 1, Page 296-325.
Malicious software, commonly termed Òmalware,Ó continuously presents one of the top security concerns, and causes tremendous worldwide financial losses for organizations. In this paper, we propose a structural risk model to analyze malware propagation dynamics measured by a four-parameter (asymptote, point of inflection, rate, and infection proportion at inflection) growth curve. Using both social network data and technological network infrastructure from a large organization, we estimate the proposed structural risk model based on incident-specific nonlinear growth curves. This paper provides empirical evidence for the explanatory power of the structural characteristics of the underlying networks on malware propagation dynamics. This research provides useful findings for security managers in designing their malware defense strategies. We also simulate three common malware defense strategies (preselected immunization strategies, countermeasure dissemination strategies, and security awareness programs) based on the proposed structural risk model and show that they outperform existing strategies in terms of reducing the size of malware infection. > >
Keywords: information systems security; malware defense; malware propagation ;malware propagation ;trajectory network analysis ;social networks ;technological networks
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#249 0.235 network networks social analysis ties structure p2p exchange externalities individual impact peer-to-peer structural growth centrality participants sharing economic ownership embeddedness
#10 0.144 strategies strategy based effort paper different findings approach suggest useful choice specific attributes explain effective affect employ particular online control
#187 0.142 learning model optimal rate hand domain effort increasing curve result experts explicit strategies estimate acquire learn referral observational skills activities
#108 0.109 model research data results study using theoretical influence findings theory support implications test collected tested based empirical empirically context paper
#264 0.060 risk risks management associated managing financial appropriate losses expected future literature reduce loss approach alternative mitigate failures failure cause mitigation