1 citations · 1 across the 3 of their papers we have counts for
4 papers
On the Security Risks of ML-based Malware Detection Systems: A Survey
Ping He, Yuhao Mao, Changjiang Li +3
Malware presents a persistent threat to user privacy and data integrity. To combat this, machine learning-based (ML-based) malware detection (MD) systems have been developed. Howev…
On the Reliability and Stability of Selective Methods in Malware Classification Tasks
Alexander Herzog, Aliai Eusebi, Lorenzo Cavallaro
The performance figures of modern drift-adaptive malware classifiers appear promising, but does this translate to genuine operational reliability? The standard evaluation paradigm…
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems
Ping He, Lorenzo Cavallaro, Shouling Ji
Android malware presents a persistent threat to users' privacy and data integrity. To combat this, researchers have proposed machine learning-based (ML-based) Android malware detec…
Context is the Key: Backdoor Attacks for In-Context Learning with Vision Transformers
Gorka Abad, Stjepan Picek, Lorenzo Cavallaro +1
Due to the high cost of training, large model (LM) practitioners commonly use pretrained models downloaded from untrusted sources, which could lead to owning compromised models. In…