With the rapid digitalization of various industries, mobile crowdsensing (MCS), an intelligent data collection and processing paradigm industrial Internet Things, has provided a promising opportunity to construct powerful systems provide services. The existing unified privacy strategy for all sensing results in excessive or insufficient protection low quality services (QoCS) MCS. To tackle this issue, article we propose personalized (PERIO) framework based on game theory encryption....

Metaverse is a vast virtual environment parallel to the physical world in which users enjoy variety of services acting as an avatar. To build secure living habitat, it's vital ensure virtual-physical traceability that tracking malicious player via his avatars space. In this paper, we propose two-factor authentication framework based on biometric-based and chameleon signature. First, aiming at disguise space, design avatar's identity model verifiability identity. Second, facing efficiency...

Federated learning of deep neural networks has emerged as an evolving paradigm for distributed machine learning, gaining widespread attention due to its ability update parameters without collecting raw data from users, especially in digital healthcare applications. However, the traditional centralized architecture federated suffers several problems (e.g., single point failure, communication bottlenecks, etc.), malicious servers inferring gradients and causing gradient leakage. To tackle...

The mobile crowdsensing (MCS) technology with a large number of Internet Things (IoT) devices provides an economic and efficient solution to participation in coordinated large-scale sensing tasks. Edge computing powers MCS form the edge (MECS) framework. Privacy disclosure data multiple stages is significant challenge MECS. To tackle this issue, combining machine learning game theory, article, we propose artificial intelligence (AI)-enabled three-party (ATG) framework for guaranteed privacy...

Dynamic wireless sensor networks (DWSNs) as an important means of industrial data collection are a key part Internet Things (IIoT), where security and reliability characteristics trustworthiness. However, due to dynamics, the management is caused by nontrusted base station (BS) that easily targeted. For distribution scheme, avianized BS also causes additional heavy overhead on sensors. To tackle these issues, in this article, we propose blockchain-based secure scheme (BC-EKM). First, stake...

Edge services provide an effective and superior means of real-time transmissions rapid processing information in the Industrial Internet Things (IIoT). However, continuous increase number smart devices results privacy leakage insufficient model accuracy edge services. To tackle these challenges, this article, we propose a blockchain-based machine learning framework for (BML-ES) IIoT. Specifically, construct novel contracts to encourage multiparty participation improve efficiency data...

Federated learning breaks down data silos and promotes the intelligence of Industrial Internet Things (IIoT). However, principal–agent architecture commonly used in federated not only increases cost but also fails to take into account privacy protection trustworthiness flexible on-demand sharing. To tackle above challenges, we propose a secure trusted sharing (STFS) based on blockchain. Initially, construct an autonomous reliable extreme gradient boosting algorithm crack isolation problem,...

In the era of Web 3.0, federated learning has emerged as a crucial technical method in resolving conflicts between data security and open sharing. However, is susceptible to various malicious behaviors, including inference attacks, poisoning free-riding attacks. These adversarial activities can lead privacy breaches, unavailability global models, unfair training processes. To tackle these challenges, we propose trustworthy scheme (TWFL) that resist above Specifically, firstly novel adaptive...

Blockchain has been an emerging technology, which comprises lots of fields such as distributed systems and Internet Things (IoT). As is well known, blockchain the underlying technology bitcoin, whose initial motivation derived from economic incentives. Therefore, components (e.g., consensus mechanism) can be constructed toward view game theory. In this paper, we highlight combination theory blockchain, including rational smart contracts, theoretic attacks, mining strategies. When put...

Collaborative perception enables autonomous vehicles to exchange sensor data among each other achieve cooperative object classification, which is considered an effective means improve the accuracy of connected (CAVs). To protect information privacy in perception, we propose a lightweight, privacy-preserving classification framework that allows CAVs raw (e.g., images captured by HD camera), without leaking private information. Leveraging chaotic encryption and additive secret sharing...

The existing data sharing models have some issues such as poor transparency of transactions, without security assurance and lacking effective tracking methods. This paper proposed a brand-new scheme based on blockchain technology. Firstly, double-chain structure about was introduced, one chain used to store the original another transaction generated by transactions. separated storage Secondly, combined with proxy re-encryption technology, safe reliable were achieved. Finally, new design...

This paper introduces a novel bi-directional con-volutional framework to cope with the large-variance scale problem in scene text detection. Due lack of normalization recent CNN-based methods, instances are activated inconsistently feature maps, which makes it hard for methods accurately locate multi-size instances. Thus, we propose relationship network (R-Net) that maps multi-scale convolutional features scale-invariant space obtain consistent activation Firstly, implement an FPN-like...

Connected autonomous vehicles (CAVs) are capable of capturing high-definition images from onboard sensors, which can be used to facilitate the detection objects in vicinity. Such may, however, contain sensitive information (e.g., human faces and license plates) as well indirect location CAVs. To protect object privacy shared by CAVs, this article proposes a privacy-preserving (P2OD) framework. Specifically, we propose multiple secure computing protocols designed construct Faster...

Face and voice are two of the most popular traits used for authentication tasks in daily life, as they can be easily captured using low-cost visual audio sensors on smartphones, laptops, tablets, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">etc</i> . Many bimodal biometric schemes based these have been presented to provide higher accuracy than unimodal systems. However, inflexibility due requirement submitting simultaneously, lack template...