Dynamic Control of Fraud Information Spreading in Mobile Social Networks

Lin, Yaguang; Wang, Xiaoming; Hao, Fei; Jiang, Yichuan; Wu, Yulei; Min, Geyong; He, Daojing; Zhu, Sencun; Zhao, Wei

doi:10.1109/tsmc.2019.2930908

Cited by 60 publications

(29 citation statements)

References 44 publications

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“…indicates the weight of a tree is 1 in the DP model owing to only covering one keyword node [27]. Formula (2) indicates that T Pmin (v, K ′ ) is obtained by using the following two operations: tree growth operation (i.e., formulas (3) and 4) and tree merging operation (i.e., formulas (5) and 6). In Figure 6(a), tree growth operation generates new T Pmin (v, K ′ ) by adding new node u (i.e., one of v's neighbors) to T Pmin (v, K ′ ).…”

Section: Pr Keyword+pop Approachmentioning

confidence: 99%

“…e second phase is paper discovery [3]; the recommender system automatically identifies diverse sets of candidate papers. e third phase is paper selection [4,5]; the recommender system recommends candidate papers containing query keywords to users. Frankly, the returned papers may fail to satisfy users' requirements on deep and continuous research on a certain content or topic as these papers may belong to the variety of research domains.…”

Section: Introductionmentioning

confidence: 99%

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Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph

Kou

Yan

2020

Complexity

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Nowadays, scholar recommender systems often recommend academic papers based on users’ personalized retrieval demands. Typically, a recommender system analyzes the keywords typed by a user and then returns his or her preferred papers, in an efficient and economic manner. In practice, one paper often contains partial keywords that a user is interested in. Therefore, the recommender system needs to return the user a set of papers that collectively covers all the queried keywords. However, existing recommender systems only use the exact keyword matching technique for recommendation decisions, while neglecting the correlation relationships among different papers. As a consequence, it may output a set of papers from multiple disciplines that are different from the user’s real research field. In view of this shortcoming, we propose a keyword-driven and popularity-aware paper recommendation approach based on an undirected paper citation graph, named PRkeyword+pop. At last, we conduct large-scale experiments on the real-life Hep-Th dataset to further demonstrate the usefulness and feasibility of PRkeyword+pop. Experimental results prove the advantages of PRkeyword+pop in searching for a set of satisfactory papers compared with other competitive approaches.

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Section: Pr Keyword+pop Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph

Kou

Yan

2020

Complexity

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“…It selects neighboring mobile devices dynamically as neighbor nodes to construct a communication path based on the "storage-save-forward" mechanism [12]. The widespread use of opportunistic networks and the rapid increase in information requires us to pay attention to the control of Fraud Information [13,14] and the spread of negative news [15].…”

Section: Introductionmentioning

confidence: 99%

Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Liu

Luo

et al. 2021

IEEE Access

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With the continuous development of 5G network technology, the amount of data has surged. Network data transmission technology needs improvement. To ensure the reliable transmission of data, reduce network congestion and network energy consumption, the paper proposed an effective edge cache collaboration routing strategy of opportunistic social networks in the trust community, namely the edge collaboration cache trust community routing algorithm (ECTC). The algorithm proposes that the nodes are used to carry information through the cache. Based on the node trust degree, the efficient trust relay node is identified. Build a trusted network based on the trust degree of nodes. Divide local trust community modules into clusters to realize efficient community retrieval. Under the concept of edge nodes, trust nodes are found in the trust community. Edge caches cooperate to share transmitted data, reducing backbone network congestion. The data update efficiency is greatly improved. Through edge nodes in trust community cooperation and communication, efficient data packet delivery is realized, thereby improving the community trust network's routing performance. The simulation experiment results show that the edge collaboration cache trust community routing algorithm (ECTC) can significantly improve delivery effectiveness and reduce network overhead. INDEX TERMScommunity routing; trust community; edge node; cache collaboration X. Wu et al: Efficient edge cache collaboration transmission strategy of opportunistic social network in trust community (March 2021) X. Wu et al: Efficient edge cache collaboration transmission strategy of opportunistic social network in trust community (March 2021) X. Wu et al: Efficient edge cache collaboration transmission strategy of opportunistic social network in trust community (March 2021

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“…The non-forwarding method means that the node does not directly accept any node message. Resource issues, security issues, and fraud of malicious nodes [18] in the network are the main causes of selfish behavior [19].…”

Section: Introductionmentioning

confidence: 99%

GIR: An Opportunistic Network Routing Algorithm Based on Game Theory

Wang

Liu

et al. 2020

IEEE Access

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A large number of routing algorithms in Opportunistic Networks are based on the assumption that nodes are free to help other nodes forward messages. However, when the Opportunistic Network is applied to an urban environment, the nodes will have certain social attributes. In many cases, a node can decide whether to execute the routing policy or not. Due to the limited resources and poor social relationships, nodes may be unwilling to forward messages from other nodes and have strong motivation to implement selfish policies. As a result, increased network latency reduces message delivery rates and affects the overall network performance. In order to solve this problem, we propose a perceptual routing protocol to promote node cooperation from the perspective of game theory. Specifically, We introduce the concept of virtual currency and construct a price function, and nodes can obtain a certain virtual currency through cooperation. In the process of message forwarding, we consider the change of link degree and energy of node (the energy exists in the form of electricity in this paper), and use them as factors of the trading node quotation. The trading node finally makes it through the multiple rounds of bargaining games, so that the proposed game between both sides reaches the Nash equilibrium. Experiments show that the algorithm outperforms Epidemic, EPSR, MINEIRO and ICRP algorithms in terms of delivery rate, average latency and energy consumption. According to the simulation experiments, the average delivery ratio of GIR algorithm is 0.68, which is 13% higher than that of the epidemic algorithm. In terms of average delay, 7% is better than ICRP algorithm. INDEX TERMS Cooperation, Routing algorithm, Nash equilibrium, Selfish.

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Dynamic Control of Fraud Information Spreading in Mobile Social Networks

Abstract: He was the Founding Director of the Texas A&M Center for Information Security and Assurance. As an elected IEEE fellow, he has made significant contributions in distributed computing, realtime systems, computer networks, cyber security, and cyberphysical systems.

Cited by 60 publications

References 44 publications

Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph

Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph

Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

GIR: An Opportunistic Network Routing Algorithm Based on Game Theory

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