Complex safety-critical systems require multiple models for a comprehensive description, resulting in error-prone development and laborious verification. Bidirectional transformation (BX) is an approach to automatically synchronizing these models. However,...

Sketches are useful for network measurement thanks to their low resource overheads and theoretically bounded accuracy. However, their network-wide deployment suffers from the trade-off between optimality and scalability: (1) Most solutions rely on mixed ...

Numerous studies have underscored the significant privacy risks associated with various leakage patterns in encrypted data stores. While many solutions have been proposed to mitigate these leakages, they either (1) incur substantial overheads, (2) focus ...

Privacy regulations like GDPR and CCPA have greatly affected online advertising and tracking strategies. To comply with the regulations, websites need to display consent management UIs (i.e., cookie banners) implemented under the corresponding technical ...

Top-k frequent items detection is a fundamental task in data stream mining. Many promising solutions are proposed to improve memory efficiency while still maintaining high accuracy for detecting the Top-k items. Despite the memory efficiency concern, the ...

Recent years have witnessed a dramatic growing trend of Virtual YouTubers (VTubers) as a new business on social media, such as YouTube, Twitch, and TikTok. However, a significant challenge arises when VTuber voice actors face health issues or retire, ...

The Shapley value provides a unique approach to equitably gauge each player's contribution within a coalition and has extensive applications with various utility functions. In data valuation for machine learning, particularly for classification tasks, ...

Rust programming language is gaining popularity rapidly in building reliable and secure systems due to its security guarantees and outstanding performance. To provide extra functionalities, the Rust compiler introduces Rust unstable features (RUF) to ...

Causal discovery is a powerful technique for identifying causal relationships among variables in data. It has been widely used in various applications in software engineering. Causal discovery extensively involves conditional independence (CI) tests. ...

Cryptocurrencies such as Bitcoin and Ethereum are gaining popularity thanks to their prominent advantages compared to legacy financial transaction systems. However, they require all participants to reach a consensus on the order of transactions, which ...

Cache side-channel attacks remain a stubborn source of cross-core secret leakage. Such attacks exploit the timing difference between cache hits and misses. Most defenses thus choose to prevent cache evictions. Given that two possible types of evictions&#...

Despite their prevalence and indispensability in the perception modules of autonomous vehicles, cameras have shown susceptibility to numerous attacks. Among them, the phantom spoofing attack is of significant concern. In such attacks, malefactors employ ...

As one of the most representative applications built on deep learning, audio systems, including keyword spotting, automatic speech recognition, and speaker identification, have recently been demonstrated to be vulnerable to adversarial examples, which ...

We study the problem of (ε, δ)-certified machine unlearning for minimax models. Most of the existing works focus on unlearning from standard statistical learning models that have a single variable and their unlearning steps hinge on the direct Hessian-...

A privacy policy serves as an online internet protocol crafted by service providers, which details how service providers collect, process, store, manage, and use personal information when users engage with applications. However, these privacy policies ...

Physically unclonable hardware fingerprints can be used for device authentication. The photo-response non-uniformity (PRNU) is the most reliable hardware fingerprint of digital cameras and can be conveniently extracted from images. However, we find image ...

Deep learning classifiers achieve state-of-the-art performance in various risk detection applications. They explore rich semantic representations and are supposed to automatically discover risk behaviors. However, due to the lack of transparency, the ...

One of the most serious factors compromising driving safety is when people in drivers' non-line-of-sight areas rush out suddenly. Existing studies on non-line-of-sight imaging rely on expensive equipment or are limited to severe laboratory conditions (...

Fingerprint recognition has been a vital security guard for various applications whose vulnerability has been explored by different works. However, previous works on spoofing fingerprint recognition rely on prior knowledge (e.g., photos and minutiae) of ...

The template-based approach to invariant generation is a parametric and relatively complete methodology for inferring loop invariants. The relative completeness ensures the generated invariants' accuracy up to the template's form and the inductive ...