As the rapid development of 5G and Internet Things (IoT) techniques, more mobile devices with specific sensing capabilities access to network large amounts data. The traditional architecture cloud computing cannot satisfy requirements, such as low latency, fast data for IoT applications. Mobile edge (MEC) can solve these problems, improve execution efficiency system. In this paper, we propose a privacy preserving aggregation scheme MEC assisted our model, there are three participants, i.e.,...

The booming Internet of Things makes smart healthcare a reality, while cloud-based medical storage systems solve the problems large-scale and real-time access data. integrity data outsourced in has become crucial since only complete can make correct diagnosis, public auditing protocol is key technique to this problem. To guarantee reduce burden owner, we propose an efficient privacy-preserving for systems, which supports functions batch dynamic update Detailed security analysis shows that...

Purpose With the increasing number of mobile applications, efficiently recommending applications to users has become a challenging problem. Although existing application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook diffusion patterns interdependencies topic-specific among groups. This paper aims capture To achieve this, topic-aware neural network-based method, referred as TN-MR, is proposed. Design/methodology/approach In...

With the development of Internet Things (IoT)-enabled Maritime Transportation Systems (MTS), massive data generated in system not only requires to be stored reliably and cheaply, but also needs analyzed timely. The Cloud-based (CMTS) allow users upload without worrying about price, capacity, location so on. However, CMTS brings some security issues, where integrity protection outsourced is one most important issues since it crucial for safety, reliability efficiency sea lanes. To solve this...

Purpose With the exponential growth of mobile applications, recommending suitable applications to users becomes a critical challenge. Although existing methods have made achievements in application recommendation by leveraging graph convolutional networks (GCNs), they suffer from two limitations: reliance on singular acquisition path leads signal sparsity, and neighborhood aggregation method exacerbates adverse impact noisy interactions. This paper aims propose SMAR, self-supervised approach...

In this paper, we discuss a security weakness of Shen <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> 's public auditing protocol for cloud data [IEEE Transactions on Information Forensics and Security, 12(10): 2402-2415, 2017.]. Specifically, point out their is vulnerable to privacy breach attack, xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , an adversary, once he compromises the third-party auditor latently, can also...

In this article, we point out the security weakness of Shang <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> 's identity-based dynamic data auditing protocol for big storage. Specifically, identify that their is vulnerable to a secret key reveal attack, i.e., service provider (SP) can owner (DO) from stored data. Further, SP also generate proof pass challenge TPA (third party auditor) even if all block and tag pairs have been...

With the emergence of more and Web services, finding suitable services becomes a difficult problem. Service link prediction is employed to disclose relationships among which facilitates further development service composition, selection, recommendation. But existing approaches simply utilize structural features network. In reality, rich text content in node description documents also carries latent but fine-grained semantics generated by multifaceted topic-aware factors, yet few efforts are...

Summary Web service recommendation as an emerging topic attracts increasing attention due to its important practical significance. As the number of available services continues grow, users face challenge searching most suitable that meet their specific needs. Quality (QoS)‐based becomes a popular approach address this issue. However, existing QoS‐based methods are inability effectively capture valuable content and structural information from services. These often rely solely on low‐order...

With the prosperity of mobile Internet, abundance data makes it difficult for users to choose their favorite app. Thus, app recommendation as an emerging topic attracts lots attention. However, existing methods rarely consider accuracy under privacy representation user preferences. To address this problem, we propose a privacy-aware package method named APP-Rec. Specifically, in method: 1) treat and its associated heterogeneous entities (APP-Rec considers not only apps themselves but also...

With the increasing number of Web services, service discovery becomes a significant challenge, and classification methods based on Graph Neural Network (GNN) are considered to be an efficient way for discovery. However, these rarely exploit structure-based feature-based prior knowledge services. To address this problem, paper proposes method graph neural network distillation. In method, firstly, it employs Word2Vec extract semantic feature vector from descriptions, then builds relationship...

In today’s society, Global Mobile Networks (GLOMONETs) have become an important network infrastructure that provides seamless roaming service for mobile users when they leave their home network. Authentication is essential mechanism secure communication among the user, network, and foreign in GLOMONET. Recently, Madhusudhan Shashidhara presented a lightweight authentication protocol application However, we found not only has design flaws, but also vulnerable to many attacks. To address these...