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Found 6 papers, 3 papers with code
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
In this work, we present Tree of Attacks with Pruning (TAP), an automated method for generating jailbreaks that only requires black-box access to the target LLM.
Support Vector Machines under Adversarial Label Contamination
Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties against deliberate attacks have not yet been widely understood.
Evasion Attacks against Machine Learning at Test Time
In security-sensitive applications, the success of machine learning depends on a thorough vetting of their resistance to adversarial data.
Security Evaluation of Support Vector Machines in Adversarial Environments
Support Vector Machines (SVMs) are among the most popular classification techniques adopted in security applications like malware detection, intrusion detection, and spam filtering.
Bayesian Differential Privacy through Posterior Sampling
All our general results hold for arbitrary database metrics, including those for the common definition of differential privacy.
Poisoning Attacks against Support Vector Machines
Such attacks inject specially crafted training data that increases the SVM's test error.
