activity
20202026
most citedA Survey of Privacy Attacks in Machine Learning

227 citations · 277 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2026

Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents

Ondřej Lukáš, Jihoon Shin, Emilia Rivas +6

Autonomous offensive agents often fail to transfer beyond the networks on which they are trained. We isolate a minimal but fundamental shift -- unseen host/subnet IP reassignment i…

cs.CR2024

Fine-tuning Large Language Models for DGA and DNS Exfiltration Detection

Md Abu Sayed, Asif Rahman, Christopher Kiekintveld +1

Domain Generation Algorithms (DGAs) are malicious techniques used by malware to dynamically generate seemingly random domain names for communication with Command & Control (C&C) se…

cs.CR2023★ 8 cited

The Power of MEME: Adversarial Malware Creation with Model-Based Reinforcement Learning

Maria Rigaki, Sebastian Garcia

Due to the proliferation of malware, defenders are increasingly turning to automation and machine learning as part of the malware detection tool-chain. However, machine learning mo…

cs.CR2023★ 15 cited

Out of the Cage: How Stochastic Parrots Win in Cyber Security Environments

Maria Rigaki, Ondřej Lukáš, Carlos A. Catania +1

Large Language Models (LLMs) have gained widespread popularity across diverse domains involving text generation, summarization, and various natural language processing tasks. Despi…

cs.AI2023★ 3 cited

Catch Me If You Can: Improving Adversaries in Cyber-Security With Q-Learning Algorithms

Arti Bandhana, Ondřej Lukáš, Sebastian Garcia +1

The ongoing rise in cyberattacks and the lack of skilled professionals in the cybersecurity domain to combat these attacks show the need for automated tools capable of detecting an…

cs.CR2022★ 13 cited

Stealing and Evading Malware Classifiers and Antivirus at Low False Positive Conditions

Maria Rigaki, Sebastian Garcia

Model stealing attacks have been successfully used in many machine learning domains, but there is little understanding of how these attacks work against models that perform malware…

cs.CR2020★ 227 cited

A Survey of Privacy Attacks in Machine Learning

Maria Rigaki, Sebastian Garcia

As machine learning becomes more widely used, the need to study its implications in security and privacy becomes more urgent. Although the body of work in privacy has been steadily…

cs.CR2020★ 11 cited

DNS Tunneling: A Deep Learning based Lexicographical Detection Approach

Franco Palau, Carlos Catania, Jorge Guerra +2

Domain Name Service is a trusted protocol made for name resolution, but during past years some approaches have been developed to use it for data transfer. DNS Tunneling is a method…