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Xiaojing Ma

7 accepted papers

2025

Consensus-Robust Transfer Attacks via Parameter and Representation Perturbations

NeurIPS 2025poster

Adversarial examples crafted on one model often exhibit poor transferability to others, hindering their effectiveness in black-box settings. This limitation arises from two key factors: (i) \emph{decision-boundary variation} across models and (ii) \emph{representation drift} in feature space. We add…

Cited by 0SourceScholar
2025

ESF: Efficient Sensitive Fingerprinting for Black-Box Tamper Detection of Large Language Models

ACL 2025finding

The rapid adoption of large language models (LLMs) in diverse applications has intensified concerns over their security and integrity, especially in cloud environments where internal model parameters are inaccessible to users. Traditional tamper detection methods, designed for deterministic classifi…

2025

Enhancing Adversarial Transferability with Checkpoints of a Single Model's Training

CVPR 2025poster

Adversarial attacks threaten the integrity of deep neural networks (DNNs), particularly in high-stakes applications. In this paper, we present a novel black-box adversarial attack that leverages the diverse checkpoints generated during a single model's training trajectory. Unlike conventional ensemb…

2025

RESF: Regularized-Entropy-Sensitive Fingerprinting for Black-Box Tamper Detection of Large Language Models

EMNLP 2025

The proliferation of Machine Learning as a Service (MLaaS) has enabled widespread deployment of large language models (LLMs) via cloud APIs, but also raises critical concerns about model integrity and security. Existing black-box tamper detection methods, such as watermarking and fingerprinting, rel

2025

SDBF: Steep-Decision-Boundary Fingerprinting for Hard-Label Tampering Detection of DNN Models

CVPR 2025poster

Cloud-based AI systems offer significant benefits but also introduce vulnerabilities, making deep neural network (DNN) models susceptible to malicious tampering. This tampering may involve harmful behavior injection or resource reduction, compromising model integrity and performance. To detect model…

2024

Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models

ICML 2024poster

Cloud-based AI services offer numerous benefits but also introduce vulnerabilities, allowing for tampering with deployed DNN models, ranging from injecting malicious behaviors to reducing computing resources. Fingerprint samples are generated to query models to detect such tampering. In this paper,…

2019

Decoding Homomorphically Encrypted Flac Audio without Decryption

ICASSP 2019accepted

Homomorphic Encryption (HE) allows processing cipher-text data, but it is a challenge to enable complex methods such as multimedia decompression in the HE domain. In this paper, we propose a novel scheme to enable FLAC (Free Lossless Audio Codec) decompression in the HE domain. FLAC applies linear p…

Cited by 0SourceScholar