2015
DOI: 10.1016/j.cose.2014.09.006
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Combating advanced persistent threats: From network event correlation to incident detection

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Cited by 186 publications
(97 citation statements)
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References 26 publications
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“…Firmware-level malware checks are also becoming more important to mitigate the possibility of a sophisticated, and deeplyembedded attack. The concept of Advanced Persistent Threats, i.e., slow-moving and deliberate attacks applied to quietly compromise systems without revealing themselves [14], could be particularly relevant here. We highlight this given that there are increasing concerns about the ability of external parties to influence a country's elections [15].…”
Section: Procedural Security Componentsmentioning
confidence: 99%
“…Firmware-level malware checks are also becoming more important to mitigate the possibility of a sophisticated, and deeplyembedded attack. The concept of Advanced Persistent Threats, i.e., slow-moving and deliberate attacks applied to quietly compromise systems without revealing themselves [14], could be particularly relevant here. We highlight this given that there are increasing concerns about the ability of external parties to influence a country's elections [15].…”
Section: Procedural Security Componentsmentioning
confidence: 99%
“…Unlike traditional attacks, APT attacks are not launched to interrupt services, but to steal intellectual property rights and sensitive data [2]. An APT attack has the stage and longevity characteristics and uncertain attack channel.…”
Section: Introductionmentioning
confidence: 99%
“…System [5] provides a framework that seeks to generate a particular model depending on the scenario, and using dataset obtained by method proposed in [9]. Two datasets are stored on a stage with no attacks in order to develop the model, and a third set with artificial anomalies to train and evaluate its efficiency.…”
Section: Introductionmentioning
confidence: 99%
“…As the attackers are looking to remain persistent once inside the system, log analysis and identification of behavioral anomalies are usually the key for protecting an infrastructure [5]. This work proposes an intelligent system that generates predictive learning based models of behavior that help us detect anomalous activity that might be classified as APT.…”
mentioning
confidence: 99%
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