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Considering the threat from on-board eavesdropping with smartphone motion sensors, Android 12 has limited the maximum sampling rate of motion sensors to 200Hz for zero-privilege access to prevent potential wiretapping. Unfortunately, there have been some ...

Control-flow integrity (CFI) is a strong and efficient defense mechanism against memory-corruption attacks. The practical versions of CFI, which have been integrated into compilers, employ static analysis to collect all possibly valid target functions of ...

The widespread use of machine learning in location-related scenarios is propelling the rapid development of intelligent transportation. To assist users in making more informed travel plans, the demand for improving prediction accuracy is growing. Prior to ...

Internet of Vehicles (IoVs) is increasingly used as a medium to propagate critical information via establishing connections between entities such as vehicles and infrastructures. During message transmission, privacy-preserving authentication is considered ...

In the era of smart healthcare, the Internet of Medical Things (IoMT) ubiquitously collects, evaluates, monitors, and prescribes treatments for patients. Despite its significant benefits, IoMT faces substantial risks related to unauthorized access ...

In this paper, we propose BiTDB, a built-in Trusted Execution Environment (TEE) database for embedded systems, to realize higher system availability while ensuring data confidentiality. With BiTDB, dilemmas that the state-of-the-art research work on ...

Unmanned Aerial Vehicles (UAVs) are typical real-time embedded systems, which require precise locations for completing flight missions. The Global Navigation Satellite System (GNSS) plays a crucial role in navigation and positioning for UAVs. ...

Unmanned Aerial Vehicles (UAVs) have a wide range of applications in various industries. Their navigation in challenging environments like dense forests and urban areas requires a high degree of precision. However, vulnerabilities such as external ...

Recent substitute training methods have utilized the concept of Generative Adversarial Networks (GANs) to implement data-free black-box attacks. Specifically, in designing the generators, the substitute training methods use a similar structure to the ...

Price discrimination has been empirically exposed where e-commercial platforms aim to gain additional profits by charging customers with different prices for the same product/service. This situation becomes even worse in nowadays’ Big Data era, ...

The adoption of SDN/NFV opens avenues for efficient network slicing deployment and cost control. However, the dynamic cost reduction brought by deployment location optimization is not suitable for all scenarios. To further reduce the cost, we recommend a ...

Platoon refers to a group of vehicles traveling in a train-like strategy with a lean inter-vehicle gap, which can increase road capacity and reduce energy consumption. A platoon is composed of several member vehicles and one leader vehicle which ...

Large-capacity machine learning models are vulnerable to membership inference attacks that disclose the privacy of the training dataset. The privacy concerns posed by membership inference attacks have inspired many defense strategies. ...

Advanced Persistent Threats (APTs) employ sophisticated and covert tactics to infiltrate target systems, leading to increased vulnerability and an elevated risk of exposure. Consequently, it is essential for us to proactively create an extensive and ...

Notwithstanding the tremendous success of deep neural networks in a range of realms, previous studies have shown that these learning models are exposed to an inherent hazard called <italic>adversarial example</italic> &#x2014; images to which an elaborate ...

Online classification services based on machine learning have been widely used in fields such as healthcare and finance. To enhance the data privacy and avoid server collusion, companies usually deploy servers on different cloud service providers ...

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• Constant online communication rounds, efficient and robust classification service even under network delay.
• Secure redundant backup servers to enable fast system self-recovery without data re-upload.
• Client-friendly and lightweight ...

Application Program Interface (API) calls are widely used in dynamic Windows malware analysis to characterize the run-time behavior of malware. Researchers have proposed various approaches to mine semantic information from API calls to improve ...

With the explosive growth of the Industrial Internet scale, cyberattacks targeting industrial control systems also increased. The management and operation of Industrial Internet are usually performed via web servers which retain a large attack ...

• We proposed a novel graph learning-based PHP Webshell detection framework, namely GlareShell, that integrates the semantic information extracted from word embedding techniques and derived risk levels to identify the maliciousness of PHP ...

The Proactive Recovery (PR) mechanism in Software-Defined Networking (SDN) provides good failure recovery resilience for the Beyond Fifth-Generation/Sixth-Generation (B5G/6G) delay-sensitive applications. However, PR&#x2019;s fixed single backup path ...

Federated Learning (FL) suffers from low convergence and significant accuracy loss due to local biases caused by non-Independent and Identically Distributed (non-IID) data. To enhance the non-IID FL performance, a straightforward idea is to leverage the ...