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- W3011884707 abstract "Although malware is a threat for most systems, the main line of defense against them (AntiViruses, or AVs) are performance-intensive applications that cause slow down due to the need of constant target-system monitoring. An effective alternative for accelerating AVs operation is to move them from software to hardware, thus eliminating their imposed performance overhead. Hardware-AVs, in turn, present another drawback: the update of malicious definitions is essential for AVs working in constant changing scenarios, but challenging to be deployed in hardware. In this paper, we propose REHAB (REconfigurable, Hardware-Assisted Blocker for malware), a reconfigurable, hardware-based AV that eliminates the performance overhead imposed by standard AVs and streamlines malicious definitions updates. REHAB is based on low-level features (e.g., branch prediction and cache accesses rates) which are classified using machine-learning (ML) algorithms (SVM, Random Forest and MLP) implemented in FPGA to facilitate components integration. We show that REHAB is a practical, effective solution for malware detection that also addresses concept-drift caused by new malware trends, since we are able to adjust the weights of our hardware-modelled neural network through software updates, and we also support fine-grained settings, such as changing the entire ML classifier in runtime (e.g., from Random Forest to MLP)." @default.
- W3011884707 created "2020-03-23" @default.
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- W3011884707 date "2019-07-01" @default.
- W3011884707 modified "2023-10-11" @default.
- W3011884707 title "The AV says: Your Hardware Definitions Were Updated!" @default.
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- W3011884707 doi "https://doi.org/10.1109/recosoc48741.2019.9034972" @default.
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