Titlebook: Research in Attacks, Intrusions, and Defenses; 20th International S Marc Dacier,Michael Bailey,Manos Antonakakis Conference proceedings 201

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书目名称Research in Attacks, Intrusions, and Defenses影响因子(影响力)




书目名称Research in Attacks, Intrusions, and Defenses影响因子(影响力)学科排名




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书目名称Research in Attacks, Intrusions, and Defenses网络公开度学科排名




书目名称Research in Attacks, Intrusions, and Defenses被引频次




书目名称Research in Attacks, Intrusions, and Defenses被引频次学科排名




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书目名称Research in Attacks, Intrusions, and Defenses年度引用学科排名




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书目名称Research in Attacks, Intrusions, and Defenses读者反馈学科排名

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Research in Attacks, Intrusions, and Defenses978-3-319-66332-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

哑剧

addict

Restenosis

floodgate

DRILL

VDF: Targeted Evolutionary Fuzz Testing of Virtual Deviceseen virtual devices implemented within the QEMU hypervisor, executing over two billion test cases and revealing over one thousand unique crashes or hangs in one third of the tested devices. Our custom test case minimization algorithm further reduces the erroneous test cases into only 18.57% of the original sizes on average.

Gudgeon

ILAB: An Interactive Labelling Strategy for Intrusion Detectionble with a real-world annotation project carried out on a large unlabelled NetFlow dataset originating from a production environment. We provide an open source implementation (.) to allow security experts to label their own datasets and researchers to compare labelling strategies.

mucous-membrane

Android Malware Clustering Through Malicious Payload Miningique and an efficient bit-vector format to represent Android apps. Experimental results demonstrate that our clustering approach achieves precision of 0.90 and recall of 0.75 for Android Genome malware dataset, and average precision of 0.98 and recall of 0.96 with respect to manually verified ground-truth.

大气层