Toward cost-sensitive modeling for intrusion detection and response

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Adversarial Feature Selection Against Evasion Attacks (2016, neutral): “in bioinformatics [37], [46], image steganalysis [47], [48], network intrusion detection [49], camera source model identification [50], and spam detection [16], [51].”
Dynamic Security Risk Management Using Bayesian Attack Graphs (2012, background): “Loss can be measured in terms of monetary units, relative magnitudes [15], [16], [17], [18] or multiunits [13], [19], [20].”
“Andromaly”: a behavioral malware detection framework for android devices (2012, background): “Lee et al. (2002) examined the major cost factors associated with an IDS which include development cost, operational cost, damage cost due to successful intrusions, and the cost of manual and automated response to intrusions.”
A model for evaluating IT security investments (2004, background): “For example, Lee et al. [ 8 ] studied the problem of building cost-sensitive IDSs.”
Information-theoretic measures for anomaly detection (2001, background): “, an IDS that provides the best-valued protection [14].”
Applying convolutional neural network for network intrusion detection (2017, background): “Most of the solutions resulted in achieving the high false positive rate with high computational cost [3].”