The vehicular announcement network is one of the most promising utilities in communications smart vehicles and transportation systems. In general, there are two major issues building an effective network. First, it difficult to forward reliable announcements without revealing users' identities. Second, users usually lack motivation announcements. this paper, we endeavor resolve these through proposing called CreditCoin, a novel privacy-preserving incentive based on Blockchain via efficient...

Android has been a major target of malicious applications (malapps). How to detect and keep the malapps out app markets is an ongoing challenge. One central design points security mechanism permission control that restricts access apps core facilities devices. However, it imparts significant responsibility developers with regard accurately specifying requested permissions users fully understanding risk granting certain combinations permissions. by depict app's behavioral patterns. In order...

Train delay prediction is a key technology for intelligent train scheduling and passenger services. We propose model that takes into account the asynchrony of events, dynamics operations, diversity influencing factors. Firstly, we consider operations as discrete sequences events arrival neural temporal point process (TANTPP) framework focused on predicting delays explicitly models events. Secondly, introduce multi-source dynamic spatiotemporal embedding method feature encoder in TANTPP...

While much effort has been made to detect and measure the privacy leakage caused by advertising (ad) libraries integrated in mobile applications, analytics libraries, which are also widely used apps have not systematically studied for their risks. Different from ad main function of is collect users' in-app actions. Hence, design more likely leak private information. In this work, we study what information collected popular Android apps. We implement a framework called "Alde". Given an app,...

Android platform has dominated the operating system of mobile devices. However, dramatic increase malicious applications (malapps) caused serious software failures to and posed a great threat users. The effective detection malapps thus become an emerging yet crucial issue. Characterizing behaviors (apps) is essential detecting malapps. Most existing works on were mainly based string static features, such as permissions API usage extracted from apps. There also exists work with structural...

Reinforcement learning is a core technology for modern artificial intelligence, and it has become workhorse AI applications ranging from Atrai Game to Connected Automated Vehicle System (CAV). Therefore, reliable RL system the foundation security critical in AI, which attracted concern that more than ever. However, recent studies discover interesting attack mode adversarial also be effective when targeting neural network policies context of reinforcement learning, inspired innovative...

Vulnerability detection is an import issue in information system security. In this work, we propose the deep learning method for vulnerability detection. We present three models, namely, convolution neural network (CNN), long short term memory (LSTM) and - (CNN-LSTM). order to test performance of our approach, collected 9872 sequences function calls as features represent patterns binary programs during their execution. apply models predict vulnerabilities these based on data. The...

Assisting traffic control is one of the most important applications on Internet Vehicles (IoVs). Traffic information provided by vehicles desired since drivers or vehicle sensors are sensitive in perceiving detecting nuances roads. However, availability and privacy preservation this critical while conflicted with each other vehicular communication. In paper, we propose a semicentralized mode attribute-based blockchain IoVs to balance tradeoff between preservation. mode, method...

Ferulic acid (FA) has antioxidative and anti-inflammatory effects, is a promising drug to treat sepsis.To study the therapeutic effect of FA in sepsis-induced acute lung injury (ALI) its underlying mechanisms.The caecal ligation puncture (CLP) manoeuvre was applied establish murine model ALI, female BALB/c mice (6 per group) were subjected 100 mg/kg or 0.8 ferrostatin-1 (Fer-1, ferroptosis inhibitor) treatment clarify role preserving alveolar epithelial barrier function inhibiting...

The blockchain cross-chain is a significant technology for inter-chain interconnection and value transfer among different networks. Cross-chain overcomes the "information island" problem of closed network increasingly applied to multiple critical areas such as finance internet things (IoT). Blockchain can be divided into three main categories networks: public blockchains, private consortium blockchains. However, there are differences in block structures, consensus mechanisms, complex working...

Are Federated Learning (FL) systems free from backdoor poisoning with the arsenal of various defense strategies deployed? This is an intriguing problem significant practical implications regarding utility FL services. Despite recent flourish poisoning-resilient methods, our study shows that carefully tuning collusion between malicious participants can minimize trigger-induced bias poisoned local model poison-free one, which plays key role in delivering stealthy attacks and circumventing a...

Heterogeneous networks, as a critical component of modern communication technology, have experienced rapid development in recent years [...]

Android platform has become the main target of malware developers in past few years. One Android's defense mechanisms against malicious apps is a permission-based access control mechanism. It feasible approach to detect potential application based on permissions it requested. In this paper, we proposed two-layered permission detection scheme for detecting applications. Comparing with previous researches, consider requested pairs as additional condition, and also used improve accuracy. The...

Since big data becomes a main impetus to the next generation of IT industry, privacy has received considerable attention in recent years. To deal with challenges, differential been widely discussed and related private mechanisms are proposed as privacy-enhancing techniques. However, today’s techniques, it is difficult generate sanitized dataset that can suit every machine learning task. In order adapt various tasks budgets, different kinds have be implemented, which inevitably incur...

Deep Neural Networks (DNNs) have been gaining state-of-the-art achievement compared with many traditional Machine Learning (ML) models in diverse fields. However, adversarial examples challenge the further deployment and application of DNNs. Analysis has carried out for studying reasons DNNs' vulnerability to perturbation focused on model architecture. No research done investigating impact optimization algorithms (namely, optimizers DNNs) employed training DNN models' sensitivity examples....

Meeting the demand for efficient photosensitizers in photodynamic therapy (PDT), a series of iridium(III) complexes decorated with silicane-modified rhodamine (Si-rhodamine) was meticulously designed and synthesized. These demonstrate exceptional PDT potential owing to their strong absorption near-infrared (NIR) spectrum, particularly responsive 808 nm laser stimulation. This feature is pivotal, enabling deep-penetration excitation overcoming depth-related challenges clinical applications....

Pedestrian detection plays a crucial role in autonomous driving by identifying the position, size, orientation, and dynamic features of pedestrians images or videos, assisting vehicles making better decisions controls. It's worth noting that performance pedestrian models largely depends on quality diversity available training data. Current datasets for have limitations terms diversity, scale, quality. In recent years, numerous studies proposed use data augmentation strategies to expand...