CASSOCK: Viable Backdoor Attacks against DNN in The Wall of Source-Specific Backdoor Defences

no code implementations • 31 May 2022 • Shang Wang, Yansong Gao, Anmin Fu, Zhi Zhang, Yuqing Zhang, Willy Susilo, Dongxi Liu

Compared with a representative SSBA as a baseline ($SSBA_{Base}$), $CASSOCK$-based attacks have significantly advanced the attack performance, i. e., higher ASR and lower FPR with comparable CDA (clean data accuracy).

Resurrecting Trust in Facial Recognition: Mitigating Backdoor Attacks in Face Recognition to Prevent Potential Privacy Breaches

1 code implementation • 18 Feb 2022 • Reena Zelenkova, Jack Swallow, M. A. P. Chamikara, Dongxi Liu, Mohan Baruwal Chhetri, Seyit Camtepe, Marthie Grobler, Mahathir Almashor

Biometric data, such as face images, are often associated with sensitive information (e. g medical, financial, personal government records).

Backdoor Attack Face Recognition +1

Enabling Efficient Privacy-Assured Outlier Detection over Encrypted Incremental Datasets

no code implementations • 14 Nov 2019 • Shangqi Lai, Xingliang Yuan, Amin Sakzad, Mahsa Salehi, Joseph K. Liu, Dongxi Liu

It realises several cryptographic modules via efficient and interchangeable protocols to support the above cryptographic operations and composes them in the overall protocol to enable outlier detection over encrypted datasets.

Anomaly Detection Outlier Detection +1

KASR: A Reliable and Practical Approach to Attack Surface Reduction of Commodity OS Kernels

no code implementations • 20 Feb 2018 • Zhi Zhang, Yueqiang Cheng, Surya Nepal, Dongxi Liu, Qingni Shen, Fethi Rabhi

In this paper, we propose a reliable and practical system, named KASR, which transparently reduces attack surfaces of commodity OS kernels at runtime without requiring their source code.

Cryptography and Security Operating Systems