Herpetologist
发表于 2025-3-30 09:37:33
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乐器演奏者
发表于 2025-3-30 14:31:52
DroidDivesDeep: Android Malware Classification via Low Level Monitorable Features with Deep Neural Neatures (e.g., CPU, Memory, Network, Sensors etc.). Our proposal employs low level device runtime attributes unlike the existing techniques considering static extraction approach. D. evaluates a reasonable dataset consisting 24,343 genuine playstore apps against 8,779 real-world Android malware. In
处理
发表于 2025-3-30 19:22:04
EvadePDF: Towards Evading Machine Learning Based PDF Malware Classifierslassifier AnalyzePDF and found significant improvement over the EvadeML. We have also tested our modified approach for the PDFRate malware classifier and found 100% success rate as in the original EvadeML.
讥笑
发表于 2025-3-30 22:08:13
Machine Learning Based Approach to Detect Position Falsification Attack in VANETs” on the road, by broadcasting false position information in the safety messages, must be detected and revoked permanently from the VANETs. The goal of our work is analyzing safety messages and detecting false position information transmitted by the misbehaving nodes. In this paper, we use machine l
彻底检查
发表于 2025-3-31 03:54:39
An Approach to Meta-Alert Generation for Anomalous TCP Trafficbers of alerts. Hence, it would be beneficial to generate meta-alerts for similar alerts. In this research work, an approach has been proposed to detect, log and generate meta-alerts for the packets, which contain anomalous TCP flags. To analyze the performance and usefulness of the proposed method
有组织
发表于 2025-3-31 08:57:21
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尖叫
发表于 2025-3-31 12:55:34
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