相关论文: PIXHELL Attack: Leaking Sensitive Information from…

Pixel diffusion generates images directly in pixel space, avoiding the VAE artifacts and representational bottlenecks of two-stage latent diffusion. Recent JiT further simplifies pixel diffusion with x-prediction, where the model predicts…

Cache side-channel attacks extract secrets by examining how victim software accesses cache. To date, practical attacks on cryptosystems and media libraries are demonstrated under different scenarios, inferring secret keys and reconstructing…

People are not always receptive to their voice data being collected and misused. Training the audio intelligence systems needs these data to build useful features, but the cost for getting permissions or purchasing data is very high, which…

Covert channels can be utilized to secretly deliver information from high privileged processes to low privileged processes in the context of a high-assurance computing system. In this case study, we investigate the possibility of covert…

Evasion attacks pose significant threats to AI systems, exploiting vulnerabilities in machine learning models to bypass detection mechanisms. The widespread use of voice data, including deepfakes, in promising future industries is currently…

Physical-layer group secret-key (GSK) generation is an effective way of generating secret keys in wireless networks, wherein the nodes exploit inherent randomness in the wireless channels to generate group keys, which are subsequently…

Recent discovery of security attacks in advanced processors, known as Spectre and Meltdown, has resulted in high public alertness about security of hardware. The root cause of these attacks is information leakage across "covert channels"…

High-speed particle image velocimetry (PIV) was used to quantify the dispersion of aerosol-laden gas clouds generated during phonetic vocalization by a human subject at different sound intensity levels. The measured PIV data was used to…

Speaker verification has been widely and successfully adopted in many mission-critical areas for user identification. The training of speaker verification requires a large amount of data, therefore users usually need to adopt third-party…

Mobile devices have access to personal, potentially sensitive data, and there is a growing number of applications that transmit this personally identifiable information (PII) over the network. In this paper, we present the AntShield system…

Language models are defined over a finite set of inputs, which creates a vocabulary bottleneck when we attempt to scale the number of supported languages. Tackling this bottleneck results in a trade-off between what can be represented in…

Despite their immense popularity, deep learning-based acoustic systems are inherently vulnerable to adversarial attacks, wherein maliciously crafted audios trigger target systems to misbehave. In this paper, we present SirenAttack, a new…

Recent research has found that neural networks are vulnerable to several types of adversarial attacks, where the input samples are modified in such a way that the model produces a wrong prediction that misclassifies the adversarial sample.…

Eavesdropping on sounds emitted by mobile device loudspeakers can capture sensitive digital information, such as SMS verification codes, credit card numbers, and withdrawal passwords, which poses significant security risks. Existing schemes…

Music is an expression of our identity, showing a significant correlation with other personal traits, beliefs, and habits. If accessed by a malicious entity, an individual's music listening habits could be used to make critical inferences…

Smart devices, such as light bulbs, TVs, fridges, etc., equipped with computing capabilities and wireless communication, are part of everyday life in many households. Previous work has already shown that a passive eavesdropper can derive…

Language-queried audio source separation (LASS) is a new paradigm for computational auditory scene analysis (CASA). LASS aims to separate a target sound from an audio mixture given a natural language query, which provides a natural and…

With the increasing popularity of voice-based applications, acoustic eavesdropping has become a serious threat to users' privacy. While on smartphones the access to microphones needs an explicit user permission, acoustic eavesdropping…

Deepfakes - manipulated or forged audio and video media - pose significant security risks to individuals, organizations, and society at large. To address these challenges, machine learning-based classifiers are commonly employed to detect…

Audio Packet Loss Concealment (PLC) is the hiding of gaps in audio streams caused by data transmission failures in packet switched networks. This is a common problem, and of increasing importance as end-to-end VoIP telephony and…