Author List: Yue, Wei T.; Çakanyildirim, Metin;
Journal of Management Information Systems, 2007, Volume 24, Issue 1, Page 329-353.
Intrusion prevention requires effective identification of and response to malicious events. In this paper, we model two important managerial decisions involved in the intrusion prevention process: the configuration of the detection component, and the response by the reaction component. The configuration decision affects the number of alarms the firm has to investigate. It is well known that the traditional intrusion detection system generates too many false alarms. The response decision determines whether alarms are going to be investigated or rejected outright. By jointly optimizing these two decision variables, a firm may apply different strategies in protecting its informational assets: slow but accurate, rapid but inaccurate, or a mixture of the two strategies. We use the optimal control approach to study the problem. Unlike previous literature, which studied the problem with a static model, in our model, the decision on balancing the desire to detect all malicious events with the opportunity costs required to do so is time dependent. Furthermore, we show how the choice of an optimal mixture of reactive and proactive responses depends on the values of cost parameters and investigation rate parameters. We find that in our model, a high damage cost does not immediately translate to a preference of proactive response, or a high false rejection cost does not translate to a preference of proactive response. The dynamics of the problem, such as how fast alarms accumulate and how fast they can be cleared, also affect the decisions.
Keywords: information security;intrusion detection;intrusion prevention;intrusion response
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List of Topics

#73 0.259 security threat information users detection coping configuration avoidance response firm malicious attack intrusion appraisal countermeasures benefit costs threats ability rate
#97 0.148 set approach algorithm optimal used develop results use simulation experiments algorithms demonstrate proposed optimization present analytical distribution selection number existing
#147 0.128 process problem method technique experts using formation identification implicit analysis common proactive input improvements identify traditional stages identifying explicit setting
#128 0.126 dynamic time dynamics model change study data process different changes using longitudinal understanding decisions develop temporal reveal associated state identifies
#10 0.105 strategies strategy based effort paper different findings approach suggest useful choice specific attributes explain effective affect employ particular online control
#8 0.062 decision making decisions decision-making makers use quality improve performance managers process better results time managerial task significantly help indicate maker
#241 0.056 information stage stages venture policies ewom paper crowdfunding second influence revelation funding cost important investigation ventures session studied electronic multiple