Due to the distributed collaboration and privacy protection features, federated learning is a promising technology perform model training in virtual twins of Digital Twin for Mobile Networks (DTMN). In order enhance reliability model, it always expected that users involved have trustworthy behaviors. Yet, available trust evaluation schemes problems considering simplex factor using coarse-grained calculation method. this paper, we propose scheme DTMN, which takes direct evidence recommended...

As an important means of obtaining information marine situation, the monitoring system relying on UAV has been paid more and attention by all countries in world, demand for tasks is growing continually. In ad hoc networks, routing protocols with immutable policies that lack flexibility are generally incapable maintaining effective performance due to complicated rapidly changing environmental situation application requirements. this paper, we propose intelligent clustering approach (ICRA)...

Vehicular networks have huge potential to improve road safety and traffic efficiency, especially in the context of large models. Cloud computing can significantly performance vehicular networks, concept cloud-assisted comes into being. Reputation management plays a crucial role since it help each vehicle evaluate trustworthiness other vehicles received messages. updating is essential reputation usually done by Trusted Authority (TA) regularly after collecting, decrypting, verifying number...

Cloud-based mobile crowd-sourcing has been an attractive solution to provide data storage and share services for resource-limited devices in a privacy-preserving manner, but how enable users issue search queries achieve fine-grained access control over ciphertexts simultaneously is still big challenge various circumstances. Although the ciphertext-policy attribute-based keyword technology combining encryption with searchable become hot research topic, it just deals equivalent attributes...

Vehicular networks have become a visible reality enabling information sharing between vehicles to enhance driving safety and provide value-added services drivers passengers. However, false might be injected into the network because of defective sensors, malicious vehicles, so on. Therefore, an efficient mechanism guarantee reliability used by is great importance in vehicular networks. To solve this problem, article proposes context-awareness trust management model evaluate trustworthiness...

With the increasing connectivity between Electronic Control Units (ECUs) and outside world, safety security have become stringent problems. The Controller Area Network (CAN) bus is most commonly used in-vehicle network protocol, which lacks mechanisms by design, so it vulnerable to various attacks. In this paper, we propose a novel intrusion detection model called CNN-LSTM with Attention (CLAM) for network, especially CAN. CLAM uses one-dimensional convolution (Conv1D) extract abstract...

Vehicular networks have tremendous potential to improve the road safety and traffic efficiency, adoption of space–air–ground-integrated network (SAGIN) architecture in vehicular can greatly performance by leveraging respective advantages space, air, ground segments on coverage, flexibility, reliability, availability, which results (SAGIVNs). Trust management is an important tool for constructing trustworthy SAGIVNs, privacy preservation also a primary concern SAGIVNs. They conflicting...

Electronic health (e-health) systems may outsource data such as patient e-health records to mobile cloud servers for efficiency gains (e.g., minimizing local storage and computation costs). However, a move result in privacy implications the presence of semi-honest servers. Searchable Encryption (SE) can potentially facilitate privacy-preserving searches based on keywords encrypted stored cloud, but most existing SE solutions do not support temporal access control (i.e., mechanism that grants...

With the rapid development of geographic location technology and explosive growth data, a large amount spatial data is outsourced to cloud server for reducing local high storage computing burdens, but at same time causes security issues. Thus, extensive privacy-preserving query schemes have been proposed. Most existing use Asymmetric Scalar-Product-Preserving Encryption (ASPE) encrypt ASPE has proven be insecure against known plaintext attack. And require users provide more information about...

Image retrieval systems help users to browse and search among extensive images in real time. With the rise of cloud computing, tasks are usually outsourced servers. However, scenario brings a daunting challenge privacy protection as servers cannot be fully trusted. To this end, image-encryption-based privacy-preserving image (PPIR) schemes have been developed, which first extract features from cipher-images, then build models based on these features. Yet, most existing PPIR approaches...

Internet of Vehicles (IoVs) is increasingly used as a medium to propagate critical information via establishing connections between entities such vehicles and infrastructures. During message transmission, privacy-preserving authentication considered the first line defence against attackers malicious information. To achieve more secure stable communication environment, ever-increasing numbers blockchain-based schemes are proposed. At glance, existing approaches provide robust architectures...

Due to the powerful representation ability and superior performance of Deep Neural Networks (DNN), Federated Learning (FL) based on DNN has attracted much attention from both academic industrial fields. However, its transmitted plaintext data causes privacy disclosure. FL Local Differential Privacy (LDP) solutions can provide protection a certain extent, but these still cannot achieve adaptive perturbation in model. In addition, this kind schemes cause high communication overheads due curse...

Autonomous vehicles (AVs) rely on controller area network (CAN), which ensures the communication between massive electronic control units (ECUs) and passenger safety. Although CAN is a lightweight reliable broadcast protocol, its vulnerability has caused to confront serious security threats. Adversaries malicious organizations can impair bus in variety of ways, such as injecting messages into bus. These directly intervene functions inside AVs. Therefore, this article proposes novel...

Vehicular ad-hoc networks (VANETs) have recently attracted considerable attention from both industry and academia for improving road safety traffic efficiency. Trust modeling plays a significant role in VANETs, however, the existing trust models cannot primely conform to characteristics of VANETs. This article proposes novel cascading-based emergency message dissemination (TCEMD) model which incorporates entity-oriented values into data-oriented evaluation an efficient manner. In proposed...

As a potential application field of the sixth-generation (6G) communication technology and promising part massive Internet Things (IoT), vehicular networks have attracted considerable attention from both academia industry in recent years, where cooperative safety applications are significant branch. It is widely acknowledged that 6G able to provide high-throughput low-latency wireless capability for networks, support interconnectivity with diverse service requirements, significantly improve...

Mobile crowdsensing (MCS) refers to a group of mobile users utilizing their sensing devices accomplish the same task. However, in vehicular networks, how evaluate reliability vehicles and achieve lightweight privacy preservation are urgent issues. Therefore, this paper proposes scheme with efficient reputation management (PPRM) for MCS networks. Specifically, we design privacy-preserving task matching algorithm which can preserve location privacy, identity data value while reducing...

Recently, federated learning has received widespread attention, which will promote the implementation of artificial intelligence technology in various fields. Privacy-preserving technologies are applied to users' local models protect privacy. Such operations make server not see true model parameters each user, opens wider door for a malicious user upload and training result converge an ineffective model. To solve this problem, article, we propose poisoning attack defense framework horizontal...

With the rapid development of Location-Based Services (LBS), a large number LBS providers outsource spatial data to cloud servers reduce their high computational and storage burdens, but meanwhile incur some security issues such as location privacy leakage. Thus, extensive privacy-preserving schemes have been proposed. However, existing solutions using Bloom filter do not take into account redundant bits that map information in filter, resulting overheads, reveal inclusion relationship...

In mobile crowdsensing (MCS), truth discovery (TD) plays an important role in sensing task completion. Most of the existing studies focus on privacy preservation users, and reliability users is evaluated by their weights which are calculated based submitted data. However, if unreliable, data also may influence accuracy ground truths tasks. Therefore, this article proposes a privacy-preserving reputation-based framework named PRTD can generate tasks with high while preserving privacy....