01794nas a2200193   4500008004100000022001400041245005300055210005300108300001200161490000600173520127900179653001801458653001301476653002001489100001501509700001901524700002001543856003701563       2009                        eng d  a1939-012200aNetwork risk management using attacker profiling0 aNetwork risk management using attacker profiling  a83–960 v23 a<p>Risk management refers to the process of making decisions that minimize the effects of vulnerabilities on the network hosts. This can be a difficult task in the context of high-exploit probability and the difficult to identify new exploits and vulnerabilities. For many years, security engineers have performed risk analysis using economic models for the design and operation of risk-prone, technological systems using attack profiles. Based on the type of attacker identified, security administrators can formulate effective risk management policies for a network. We hypothesize that sequence of network actions by an attacker depends on the social behavior (e.g., skill level, tenacity, financial ability). We extended this and formulated a mechanism to estimate the risk level of critical resources that may be compromised based on attacker behavior. This estimation is accomplished using behavior based attack graphs representing all the possible attack paths to all the critical resources. The risk level is computed based on these graphs and are used as a measure of the vulnerability of the resource and forming an effective basis for a system administrator to perform suitable changes to network configuration. Copyright © 2008 John Wiley &amp; Sons, Ltd.</p>
10aattack graphs10abehavior10arisk management1 aDantu, Ram1 aKolan, Prakash1 aCangussu, João  uhttp://dx.doi.org/10.1002/sec.5801661nas a2200241   4500008004100000022001400041245003500055210003500090300001500125490000600140520105900146653001301205653003001218653001301248653001301261653001301274653001401287653001701301100001901318700001501337700002001352856004701372       2008                        eng d  a1551-685700aNuisance Level of a Voice Call0 aNuisance Level of a Voice Call  a6:1–6:220 v53 a<p>In our everyday life, we communicate with many people such as family, friends, neighbors, and colleagues. We communicate with them using different communication media such as email, telephone calls, and face-to-face interactions. While email is not real-time and face-to-face communications require geographic proximity, voice and video communications are preferred over other modes of communication. However, real-time voice/video calls may create nuisance to the receiver. In this article, we describe a mathematical model for computing nuisance level of incoming voice/video calls. We computed the closeness and nuisance level using the calling patterns between the caller and the callee. To validate the nuisance model, we collected cell phone call records of real-life people at our university and computed the nuisance value for all voice calls. We validated the nuisance levels using the feedback from those real-life people. Such a nuisance model is useful for predicting unwanted voice and video sessions in an IP communication network.</p>
10abehavior10aMultimedia communications10anuisance10apresence10aSecurity10atolerance10aunwantedness1 aKolan, Prakash1 aDantu, Ram1 aCangussu, João  uhttp://doi.acm.org/10.1145/1404880.1404886