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书目名称Research in Attacks, Intrusions, and Defenses影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0827937<br><br> <br><br>书目名称Research in Attacks, Intrusions, and Defenses读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0827937<br><br> <br><br>CREEK 发表于 2025-3-21 23:54:10
Research in Attacks, Intrusions, and Defenses978-3-319-66332-6Series ISSN 0302-9743 Series E-ISSN 1611-3349哑剧 发表于 2025-3-22 03:19:20
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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 发表于 2025-3-22 23:40:48
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 发表于 2025-3-23 02:18:05
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 发表于 2025-3-23 06:00:43
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