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Adam Lundqvist

dblp:420/7844 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0009-9887-5836ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Systems and software security · 50% Privacy and data protection · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection
regulatory compliance
0.912025
Poster: Towards Intelligent Assurance for Autonomous AI Pentesters: Concurrent Compliance Auditing and Self-Augmentation via Execution Trace Analysis · CCS 2025

Methods — techniques the papers use, named apart from their topics

execution trace analysis · 0.9
YearPublicationVenuePosition
2025 Poster: Towards Intelligent Assurance for Autonomous AI Pentesters: Concurrent Compliance Auditing and Self-Augmentation via Execution Trace Analysis
abstract
As Artificial Intelligence (AI) increasingly powers autonomous offensive security tools (i.e., AI Pentesters); ensuring their operational integrity, regulatory compliance (e.g., under the EU AI Act), and ethical conduct becomes critical, particularly when direct human oversight is limited or absent. To address these challenges, we propose an Intelligent Assurance System (IAS) that provides continuous oversight and accountability for fully autonomous AI Pentesters. The IAS is designed to enhance trustworthiness by monitoring execution traces, enforcing compliance, delivering real-time feedback, and facilitating self-improvement while being resource-efficient.
Gustavo Sánchez 0001, Adam Lundqvist
CCS2