Attack-detection mechanisms should be able to reliably detect, predict, and understandably explain both known and novel threats, while also being able to cope with evasion techniques (like obfuscation, polymorphism, or stealth low-volume attacks). They should not just be able to detect any critical incident, but also raise alarms when it matters only; the more false alarms are raised, the higher the risk that users will ignore warnings or even disable the detection permanently. Moreover, to provide a strong line of defense, attack detection methods should be complemented by suitable defensive technologies, ideally selected autonomously by the system under attack, to counter whatever threat it encounters. In this research area we pursue this ideal, currently amongst others by focusing on the detection and analysis of modern malware, on the prevention and attribution of DDoS attacks, and on the identification and mitigation of novel system vulnerabilities.
USENIX-Security
USENIX Security Symposium31st USENIX Security Symposium
USENIX-Security
USENIX Security Symposium31st USENIX Security Symposium
USENIX-Security
USENIX Security Symposium31st USENIX Security Symposium
CCS
ACM CCSACM CCS 2021
ICCV
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)IEEE International Conference on Computer Vision (ICCV), 2021
ICCV
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)IEEE International Conference on Computer Vision (ICCV), 2021
