all InfoSec news
Asset-driven Threat Modeling for AI-based Systems
March 12, 2024, 4:10 a.m. | Jan von der Assen, Jamo Sharif, Chao Feng, G\'er\^ome Bovet, Burkhard Stiller
cs.CR updates on arXiv.org arxiv.org
Abstract: Threat modeling is a popular method to securely develop systems by achieving awareness of potential areas of future damage caused by adversaries. The benefit of threat modeling lies in its ability to indicate areas of concern, paving the way to consider mitigation during the design stage. However, threat modeling for systems relying on Artificial Intelligence is still not well explored. While conventional threat modeling methods and tools did not address AI-related threats, research on this …
adversaries arxiv asset awareness cs.cr cs.se design future lies mitigation modeling popular stage systems threat threat modeling
More from arxiv.org / cs.CR updates on arXiv.org
IDEA: Invariant Defense for Graph Adversarial Robustness
1 day, 13 hours ago |
arxiv.org
FairCMS: Cloud Media Sharing with Fair Copyright Protection
1 day, 13 hours ago |
arxiv.org
Efficient unitary designs and pseudorandom unitaries from permutations
1 day, 13 hours ago |
arxiv.org
Jobs in InfoSec / Cybersecurity
SOC 2 Manager, Audit and Certification
@ Deloitte | US and CA Multiple Locations
Cybersecurity Engineer
@ Booz Allen Hamilton | USA, VA, Arlington (1550 Crystal Dr Suite 300) non-client
Invoice Compliance Reviewer
@ AC Disaster Consulting | Fort Myers, Florida, United States - Remote
Technical Program Manager II - Compliance
@ Microsoft | Redmond, Washington, United States
Head of U.S. Threat Intelligence / Senior Manager for Threat Intelligence
@ Moonshot | Washington, District of Columbia, United States
Customer Engineer, Security, Public Sector
@ Google | Virginia, USA; Illinois, USA