Titlebook: Recent Advances in Intrusion Detection; 12th International S Engin Kirda,Somesh Jha,Davide Balzarotti Conference proceedings 2009 Springer-

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Towards Generating High Coverage Vulnerability-Based Signatures with Protocol-Level Constraint-Guidenerated signatures often can be easily evaded by an attacker with small variations of the exploit message. In this paper, we propose ., a new approach towards generating high coverage vulnerability-based signatures. In particular, our approach generates high coverage, yet compact, ., which capture m

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VirusMeter: Preventing Your Cellphone from Spiesally available. With the growing popularity of mobile devices in the last few years, attacks targeting them are also surging. Existing mobile malware detection techniques, which are often borrowed from solutions to Internet malware detection, do not perform as effectively due to the limited computin

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Regular Expression Matching on Graphics Hardware for Intrusion Detectionations. However, the flexible pattern matching functionality of regular expressions in these systems comes with significant overheads in terms of both memory and CPU cycles, since every byte of the inspected input needs to be processed and compared against a large set of regular expressions..In this

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Multi-byte Regular Expression Matching with Speculationttack or a vulnerability. IPSs need to keep up with ever-increasing line speeds, which leads to the use of custom hardware. A major bottleneck that IPSs face is that they scan incoming packets one byte at a time, which limits their throughput and latency. In this paper, we present a method for scann

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Toward Revealing Kernel Malware Behavior in Virtual Execution Environments complementary to other malware analysis techniques such as static code analysis and debugger-based code analysis. This paper presents ., a sandbox-based malware tracking system that dynamically monitors and analyzes the behavior of Windows kernel malware. Kernel malware samples run inside a virtual

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An Experimental Study on Instance Selection Schemes for Efficient Network Anomaly Detection well studied so far is the selection of normal training data for network anomaly detection algorithm, which is highly related to the detection performance and computational complexities. In this poster, we present two instance selection mechanism – .as well as. for network anomaly detection algorit