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https://sites.cs.ucsb.edu/~chong/290N-F06/anomaly-detection.pdf
the anomalous path checking technique and efficiency of our hardware implementation. Finally, section 7 concludes the paper. 2. RELATED WORK First, we would like to clarify the difference between anomaly detection and the buffer overflow detection. There has been a lot of work on using specialized software and hardware to detect
https://www.researchgate.net/publication/221147880_Anomalous_path_detection_with_hardware_support
Anomalous path detection with hardware support [105] is a technique designed by researchers at Georgia Tech to combat control-flow attacks. It involves a " training " stage for software, where ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.7374
In this paper, we propose a hardware-based approach to verify program execution paths of target applications dynamically and to detect anomalous executions. With hardware support, our approach offers multiple advantages over software based solutions including minor performance degradation, much stronger detection capability (a larger variety of ...
https://dl.acm.org/citation.cfm?id=1086305
In this paper, we propose a hardware-based approach to verify program execution paths of target applications dynamically and to detect anomalous executions. With hardware support, our approach offers multiple advantages over software based solutions including minor performance degradation, much stronger detection capability (a larger variety of ...Cited by: 90
http://nueess.coe.neu.edu/nueess/index.php/Anomalous_Path_Detection
We propose a new hardware-based approach by leveraging the existing speculative architectures for run-time program validation. The on-chip branch target buffer (BTB) is utilized as a cache of the legitimate control flow transfers stored in a secure memory region. In addition, the BTB is extended to store the correct program path information.
https://jorge-cardoso.github.io/publications/Papers/CP-2019-089-CCGrid-Anomaly_Detection_and_Classification_using_DT_and_DL.pdf
heterogeneous hardware and has multiple scenarios of normal ... aim at exploring an additional path for anomaly detection using a second category of data, namely the tracing data ... A network was trained on non-anomalous data and used as a predictor over a number of time steps. The
http://www.cercs.gatech.edu/tech-reports/tr2004/git-cercs-04-11.pdf
Hardware Supported Anomaly Detection: down to the Control Flow Level ... anomalous executions. With hardware support, our approach offers multiple advantages over software based solutions including near ... which constructs a return address table and a virtual path
http://www.cs.columbia.edu/~simha/preprint_raid14.pdf
Unsupervised Anomaly-based Malware Detection using Hardware Features Adrian Tang, Simha Sethumadhavan, and Salvatore Stolfo Columbia University, New York, USA fatang, simha, [email protected] Abstract. Recent works have shown promise in detecting malware pro-grams based on their dynamic microarchitectural execution patterns.
https://www.researchgate.net/publication/261278999_Adaptable_intrusion_detection_using_partial_runtime_reconfiguration
Intrusion detection approaches have been presented which detect anomalous malware behavior at runtime. Most techniques involve software-based analysis which is too slow to support the tight timing ...
https://x9q3r9j3.stackpathcdn.com/wp-content/uploads/2019/04/NovaLCT-LED-Configuration-Tool-for-Synchronous-System-User-Guide-V5.2.0.pdf
Perfect anomalous type support: arbitrary cabling, arbitrary point extraction, arbitrary point insertion, anomalous plate, anomalous cabinet, anomalous screen and easy load. Low grey scale with richness and smoothness: first-class build-up of luminance, and grey scale of 16-bit, which makes the image of the screen fine and smooth;
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