Forwarded from CyberSecurityTechnologies
25_SOC_Survey.pdf
2 MB
#Analytics
#Whitepaper
"SANS 2025 SOC Survey", 09 Jul, 2025.
// In this white paper, SANS examines the latest trends, challenges, and priorities shaping modern Security Operations Centers (SOCs) based on insights from the 2025 SOC Survey
#Whitepaper
"SANS 2025 SOC Survey", 09 Jul, 2025.
// In this white paper, SANS examines the latest trends, challenges, and priorities shaping modern Security Operations Centers (SOCs) based on insights from the 2025 SOC Survey
Practical_Cyber_Intelligence.pdf
6.1 MB
#DFIR
#Tech_book
"Practical Cyber Intelligence:
A Hands-on Guide to Digital Forensics", 2024.
// This book offers a comprehensive guide to utilizing digital forensics and OSINT in the investigative process, encompassing the latest techniques, tools, and best practices within the field
#Tech_book
"Practical Cyber Intelligence:
A Hands-on Guide to Digital Forensics", 2024.
// This book offers a comprehensive guide to utilizing digital forensics and OSINT in the investigative process, encompassing the latest techniques, tools, and best practices within the field
Forwarded from CyberSecurityTechnologies
FL_Sec.pdf
1.5 MB
#AIOps
#Analytics
#MLSecOps
"On the Security and Privacy of Federated Learning:
A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions", 2025.
// Federated Learning (FL) is an emerging distributed machine learning paradigm enabling multiple clients to train a global model collaboratively without sharing their raw data. While FL enhances data privacy by design, it remains vulnerable to various security and privacy threats..
#Analytics
#MLSecOps
"On the Security and Privacy of Federated Learning:
A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions", 2025.
// Federated Learning (FL) is an emerging distributed machine learning paradigm enabling multiple clients to train a global model collaboratively without sharing their raw data. While FL enhances data privacy by design, it remains vulnerable to various security and privacy threats..
👍3
Forwarded from CyberSecurityTechnologies
TrojAI_Final_Report.pdf
14.2 MB
#Analytics
#Research
#MLSecOps
"Trojans in Artificial Intelligence. Final Report",
IARPA, Jan. 2026.
// This report synthesizes the TrojAI program's key findings, including methodologies for detection through weight analysis and trigger inversion, as well as approaches for mitigating Trojan risks in deployed models. Comprehensive test and evaluation results highlight detector performance, sensitivity, and the prevalence of "natural" Trojans. The report concludes with lessons learned and recommendations for advancing AI security research
#Research
#MLSecOps
"Trojans in Artificial Intelligence. Final Report",
IARPA, Jan. 2026.
// This report synthesizes the TrojAI program's key findings, including methodologies for detection through weight analysis and trigger inversion, as well as approaches for mitigating Trojan risks in deployed models. Comprehensive test and evaluation results highlight detector performance, sensitivity, and the prevalence of "natural" Trojans. The report concludes with lessons learned and recommendations for advancing AI security research
Forwarded from CyberSecurityTechnologies
AI_Governance_RACI_Draft_v01.xlsx
41.7 KB
#Analytics
#MLSecOps
Mapping NIST AI RMF + Forrester RACI -> Microsoft Security Stack
// Key takeaways:
- NIST AI RMF -> the risk lifecycle (Govern -> Map -> Measure -> Manage)
- Forrester RACI -> the ownership model (one clear "A" per activity)
- Microsoft Security -> the governance and protection plane (identity, telemetry, tool gateway, protection, etc.)
#MLSecOps
Mapping NIST AI RMF + Forrester RACI -> Microsoft Security Stack
// Key takeaways:
- NIST AI RMF -> the risk lifecycle (Govern -> Map -> Measure -> Manage)
- Forrester RACI -> the ownership model (one clear "A" per activity)
- Microsoft Security -> the governance and protection plane (identity, telemetry, tool gateway, protection, etc.)