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Wu Yang
Information Security Research Center, Haerbin Engineering University, 12428 Harbin, Heilongjiang, China, 150001

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Journal article
Published: 18 August 2021 in IEEE Transactions on Industrial Informatics
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Energy harvesting (EH) is a promising and critical technology to mitigate the dilemma between the limited battery capacity and the increasing energy consumption in the Internet of everything. However, the current EH system suffers from energy-information cross threats, facing the overlapping vulnerability of energy deprivation and private information leakage. Although some existing works touch on the security of energy and information in EH, they treat these two issues independently, without collaborative and intelligent protection cross the energy side and information side. To address the above challenge, this paper proposes a joint protection framework of energy security and information privacy for EH with an incentive federated learning approach. First, we design a federated learning-based malicious energy user detection method according to energy status and behaviors to provide energy security protection. Secondly, a differential privacy-empowered information preservation scheme is devised, where sensitive information is perturbed and protected by the customized demand-based noise. Thirdly, a non-cooperative game-enabled incentive mechanism is established to encourage EH nodes to participate in the joint energy-information protection system. The proposed incentive mechanism derives the optimal energy-information security strategy for EH nodes and achieve a tradeoff between the protection of energy security and information privacy. Evaluation results have verified the effectiveness of our proposed joint protection mechanism.

ACS Style

Qianqian Pan; Jun Wu; A. K. Bashir; Jianhua Li; Wu Yang; Yasser D. Al-Otaibi. Joint Protection of Energy Security and Information Privacy for Energy Harvesting: An Incentive Federated Learning Approach. IEEE Transactions on Industrial Informatics 2021, PP, 1 -1.

AMA Style

Qianqian Pan, Jun Wu, A. K. Bashir, Jianhua Li, Wu Yang, Yasser D. Al-Otaibi. Joint Protection of Energy Security and Information Privacy for Energy Harvesting: An Incentive Federated Learning Approach. IEEE Transactions on Industrial Informatics. 2021; PP (99):1-1.

Chicago/Turabian Style

Qianqian Pan; Jun Wu; A. K. Bashir; Jianhua Li; Wu Yang; Yasser D. Al-Otaibi. 2021. "Joint Protection of Energy Security and Information Privacy for Energy Harvesting: An Incentive Federated Learning Approach." IEEE Transactions on Industrial Informatics PP, no. 99: 1-1.

Journal article
Published: 24 June 2021 in Computer Communications
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The Internet of things (IoT) is a new network concept. Based on the Internet, the idea of connecting everything is proposed, which is likely to become the development direction of computer and communication in the future. Meanwhile, as a disruptive new communication network model, Information-Centric Network (ICN) has become a hot spot in the field of future network architecture research in recent years. ICN is information-centric, and uses the name of the information to implement data identification, retrieval, and routing and forwarding. The information centric network uses the cache as a built-in structure, and nodes store all the data that flows by default, so that subsequent requests can be responded to as soon as possible. In the actual network, the spread and trend of an information constantly change with time, and the popularity of the information is different in different time periods. However, the existing ICN native caching mechanism ignores the correlation between contents, and the existing relevant research makes insufficient use of content relevance. In this paper may exist a certain correlation between nodes have access to the content of the facts, we design a path cache method based on the correlation content, by discovering target content and the correlation between nodes store content, at the same time considering the node position in the path, make caching decisions, make the cache memory more efficient. The feasibility and effectiveness of the proposed method are verified by simulation experiments under different parameters.

ACS Style

Dapeng Man; Qi Lu; Hanbo Wang; Jiafei Guo; Wu Yang; Jiguang Lv. On-path caching based on content relevance in Information-Centric Networking. Computer Communications 2021, 176, 272 -281.

AMA Style

Dapeng Man, Qi Lu, Hanbo Wang, Jiafei Guo, Wu Yang, Jiguang Lv. On-path caching based on content relevance in Information-Centric Networking. Computer Communications. 2021; 176 ():272-281.

Chicago/Turabian Style

Dapeng Man; Qi Lu; Hanbo Wang; Jiafei Guo; Wu Yang; Jiguang Lv. 2021. "On-path caching based on content relevance in Information-Centric Networking." Computer Communications 176, no. : 272-281.

Journal article
Published: 22 February 2021 in IEEE Consumer Electronics Magazine
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In large scale emergency scenarios, massive content for searching, asking for help, and rescue will be generated and transmitted in Intelligent Internet of Vehicular Things (IIoVT). However, IP-networks based emergency systems make rescue decisions on remote emergency centers, leading to in-efficient content dissemination and a high-latency response. Moreover, a few previous works address trust issues in the emergency systems, resulting in fake content and malicious emergency services. To address above challenges, we propose an emergent semantic-based information-centric fog system, which realizes trustworthy and intelligent emergency analysis and management. First, we design an efficient emergency content dissemination network for aggregating and analyzing emergency information. Besides, we propose a semantic-based trustworthy routing scheme that filters fake content from malicious entities. Moreover, we implement a real testbed and a simulator to evaluate the benefit and performance of the proposed system. The results show that the proposed system achieves a short average semantic analyzing time and a low failure rate of emergency services.

ACS Style

Qiaolun Zhang; Jun Wu; Michele Zanella; Wu Yang; Ali Kashif Bashir; William Fornaciari. Sema-IIoVT: Emergent Semantic-Based Trustworthy Information-Centric Fog System and Testbed for Intelligent Internet of Vehicles. IEEE Consumer Electronics Magazine 2021, PP, 1 -1.

AMA Style

Qiaolun Zhang, Jun Wu, Michele Zanella, Wu Yang, Ali Kashif Bashir, William Fornaciari. Sema-IIoVT: Emergent Semantic-Based Trustworthy Information-Centric Fog System and Testbed for Intelligent Internet of Vehicles. IEEE Consumer Electronics Magazine. 2021; PP (99):1-1.

Chicago/Turabian Style

Qiaolun Zhang; Jun Wu; Michele Zanella; Wu Yang; Ali Kashif Bashir; William Fornaciari. 2021. "Sema-IIoVT: Emergent Semantic-Based Trustworthy Information-Centric Fog System and Testbed for Intelligent Internet of Vehicles." IEEE Consumer Electronics Magazine PP, no. 99: 1-1.

Special issue article
Published: 10 June 2020 in Transactions on Emerging Telecommunications Technologies
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The explosive growth of data in the network has brought huge burdens and challenges to traditional centralized cloud computing data processing. To solve this problem, edge computing technology came into being. Because the edge is closer to the user, processing part of the data at the edge can also bring a faster response to the user and improve their experience. However, the existing edge computing platforms have problems such as data storage security and multiparty data mutual trust. Blockchain technology has become an important means to solve the above data storage and sharing problems due to its excellent characteristics. The core of blockchain technology is consensus, and its speed and security will directly affect the efficiency and stability of the blockchain system. Therefore, this study uses the consensus mechanism as an entry point to reduce the resource consumption of the edge computing blockchain system and improve its security. In order to reduce the resource consumption of traditional consensus algorithms, improve their adaptability in the edge computing environment, and solve the security problem caused by the concentration of node rights, a prestige‐based edge computing blockchain security consensus model (ECBCM) is proposed. ECBCM is a general model based on prestige rewards and penalties. It also introduces a node replacement mechanism to ensure the fault tolerance of the consensus process. According to the results of multiple sets of performance comparison experiments and security verification experiments after embedding the existing consensus algorithm, the validity of the consensus model is confirmed.

ACS Style

Shichang Xuan; Zhiyu Chen; Ilyong Chung; Haowen Tan; Dapeng Man; Xiaojiang Du; Wu Yang; Mohsen Guizani. ECBCM: A prestige‐based edge computing blockchain security consensus model. Transactions on Emerging Telecommunications Technologies 2020, 32, 1 .

AMA Style

Shichang Xuan, Zhiyu Chen, Ilyong Chung, Haowen Tan, Dapeng Man, Xiaojiang Du, Wu Yang, Mohsen Guizani. ECBCM: A prestige‐based edge computing blockchain security consensus model. Transactions on Emerging Telecommunications Technologies. 2020; 32 (6):1.

Chicago/Turabian Style

Shichang Xuan; Zhiyu Chen; Ilyong Chung; Haowen Tan; Dapeng Man; Xiaojiang Du; Wu Yang; Mohsen Guizani. 2020. "ECBCM: A prestige‐based edge computing blockchain security consensus model." Transactions on Emerging Telecommunications Technologies 32, no. 6: 1.

Original article
Published: 06 April 2020 in Personal and Ubiquitous Computing
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Wireless device-free human sensing is an emerging technique of Internet of Things, which holds great potential for ubiquitous location-based services and human-interaction applications. Although existing studies can detect human appearance, they still neglect to further identify whether a user is approaching a sensor or not, which is critical for fine-grained recognition of human behaviors. In this paper, we first conduct comprehensive experiments to measure relationships between signal fading and human positions. The experimental results show that signal fading stepwise changes with different distances of the human to a sensor. Moreover, the signal fading is worse when the human is located closer to an antenna of the sensor. Motivated by these observations, we propose NSee, a novel system for device-free near-field human sensing without site-survey fingerprints. Specifically, we cluster signal fading features of different antennas by a Gaussian mixture model, and further propose a cluster identification algorithm to identify clusters in correspondence to different near-field subareas of human appearance. Based on cluster characteristics, NSee can recognize near-field human presence with online sensing. We implement a prototype of NSee system based on a commercial WiFi card with multiple antennas. Extensive experimental results illustrate that the proposed system can achieve an averaged accuracy of 90% in device-free near-field human recognition.

ACS Style

Liangyi Gong; Chaocan Xiang; Xiaochen Fan; Tao Wu; Chao Chen; Miao Yu; Wu Yang. Device-free near-field human sensing using WiFi signals. Personal and Ubiquitous Computing 2020, 1 -14.

AMA Style

Liangyi Gong, Chaocan Xiang, Xiaochen Fan, Tao Wu, Chao Chen, Miao Yu, Wu Yang. Device-free near-field human sensing using WiFi signals. Personal and Ubiquitous Computing. 2020; ():1-14.

Chicago/Turabian Style

Liangyi Gong; Chaocan Xiang; Xiaochen Fan; Tao Wu; Chao Chen; Miao Yu; Wu Yang. 2020. "Device-free near-field human sensing using WiFi signals." Personal and Ubiquitous Computing , no. : 1-14.

Journal article
Published: 20 February 2020 in Computers & Electrical Engineering
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Data sharing techniques have progressively drawn increasing attention as a means of significantly reducing repetitive work. However, in the process of data sharing, the challenges regarding formation of mutual-trust relationships and increasing the level of user participation are yet to be solved. The existing solution is to use a third party as a trust organization for data sharing, but there is no dynamic incentive mechanism for data sharing with a large number of users. Blockchain 2.0 with smart contract has the natural advantage of being able to enable trust and automated transactions between a large number of users. This paper proposes a data sharing incentive model based on evolutionary game theory using blockchain with smart contract. The smart contract mechanism can dynamically control the excitation parameters and continuously encourages users to participate in data sharing.

ACS Style

Shichang Xuan; Li Zheng; Ilyong Chung; Wei Wang; Dapeng Man; Xiaojiang Du; Wu Yang; Mohsen Guizani. An incentive mechanism for data sharing based on blockchain with smart contracts. Computers & Electrical Engineering 2020, 83, 106587 .

AMA Style

Shichang Xuan, Li Zheng, Ilyong Chung, Wei Wang, Dapeng Man, Xiaojiang Du, Wu Yang, Mohsen Guizani. An incentive mechanism for data sharing based on blockchain with smart contracts. Computers & Electrical Engineering. 2020; 83 ():106587.

Chicago/Turabian Style

Shichang Xuan; Li Zheng; Ilyong Chung; Wei Wang; Dapeng Man; Xiaojiang Du; Wu Yang; Mohsen Guizani. 2020. "An incentive mechanism for data sharing based on blockchain with smart contracts." Computers & Electrical Engineering 83, no. : 106587.

Journal article
Published: 30 January 2020 in Computer Communications
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In Information-Centric Networking (ICN), transmission does not depend on the ends of communication, but on the content itself. In-network cache plays an important role in ICN, it empowers nodes in ICN better mobility. It also shortens serving path, lightens load of server, reduces traffic and time delay, its efficiency seriously affects performance of entire network, and thus cache management in ICN draws much attention of researchers recently. Although there are a lot approaches have been proposed, a cache management scheme with better adaptability and less cost remains to be studied. To this end, we propose State-value-and-Cache-rate-Method (SCMethod) to manage cache resources in ICN, which comprises cache deployment policy and cache replacement policy. In cache level, we add pre-filter queues in front of cache queue to filter out popular content to store in cache. In the perspective of node, according to factors that node’s state and relative location on data forwarding path, we define node state and cache rate to select nodes with maximum of state value or minimum cache rate to cache content, and effectively mitigate data redundancy. In order to increase dynamics and adaptive of system for mobility of nodes, we employ cache hit ratio as feedback to dynamically adjust the number of pre-filter queues in every node. With pre-filter queues, we improve Least Recently Used (LRU) cache replacement method. We conduct extensive experiments in simulator Icarus (Saino et al., 2014) with both tree topology and realistic internet topologies, define four metrics to quantitatively evaluate performance of SCMethod and verify its efficacy of reducing latency and load. Simulation results demonstrate that SCMethod we proposed outperform several classic cache schemes of ICN.

ACS Style

Dapeng Man; Qi Lu; Yao Wang; Yang Wu; Xiaojiang Du; Mohsen Guizani. An adaptive cache management approach in ICN with pre-filter queues. Computer Communications 2020, 153, 250 -263.

AMA Style

Dapeng Man, Qi Lu, Yao Wang, Yang Wu, Xiaojiang Du, Mohsen Guizani. An adaptive cache management approach in ICN with pre-filter queues. Computer Communications. 2020; 153 ():250-263.

Chicago/Turabian Style

Dapeng Man; Qi Lu; Yao Wang; Yang Wu; Xiaojiang Du; Mohsen Guizani. 2020. "An adaptive cache management approach in ICN with pre-filter queues." Computer Communications 153, no. : 250-263.

Journal article
Published: 28 November 2019 in Applied Sciences
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With the arrival of the Internet of Things (IoT) era and the rise of Big Data, cloud computing, and similar technologies, data resources are becoming increasingly valuable. Organizations and users can perform all kinds of processing and analysis on the basis of massive IoT data, thus adding to their value. However, this is based on data-sharing transactions, and most existing work focuses on one aspect of data transactions, such as convenience, privacy protection, and auditing. In this paper, a data-sharing-transaction application based on blockchain technology is proposed, which comprehensively considers various types of performance, provides an efficient consistency mechanism, improves transaction verification, realizes high-performance concurrency, and has tamperproof functions. Experiments were designed to analyze the functions and storage of the proposed system.

ACS Style

Shichang Xuan; Yibo Zhang; Hao Tang; Ilyong Chung; Wei Wang; Wu Yang. Hierarchically Authorized Transactions for Massive Internet-of-Things Data Sharing Based on Multilayer Blockchain. Applied Sciences 2019, 9, 5159 .

AMA Style

Shichang Xuan, Yibo Zhang, Hao Tang, Ilyong Chung, Wei Wang, Wu Yang. Hierarchically Authorized Transactions for Massive Internet-of-Things Data Sharing Based on Multilayer Blockchain. Applied Sciences. 2019; 9 (23):5159.

Chicago/Turabian Style

Shichang Xuan; Yibo Zhang; Hao Tang; Ilyong Chung; Wei Wang; Wu Yang. 2019. "Hierarchically Authorized Transactions for Massive Internet-of-Things Data Sharing Based on Multilayer Blockchain." Applied Sciences 9, no. 23: 5159.

Journal article
Published: 25 July 2019 in Future Internet
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Wireless Mesh Networks (WMNs), have a potential offering relatively stable Internet broadband access. The rapid development and growth of WMNs attract ISPs to support users’ coverage anywhere anytime. To achieve this goal network architecture must be addressed carefully. Software Defined Networking (SDN) proposes new network architecture for wired and wireless networks. Software Defined Wireless Networking (SDWN) has a great potential to increase efficiency, ease the complexity of control and management, and accelerate technology innovation rate of wireless networking. An SDN controller is the core component of an SDN network. It needs to have updated reports of the network status change, as in network topology and quality of service (QoS) in order to effectively configure and manage the network it controls. In this paper, we propose Flat Distributed Software Defined Wireless Mesh Network architecture where the controller aggregates entire topology discovery and monitors QoS properties of extended WMN nodes using Link Layer Discovery Protocol (LLDP) protocol, which is not possible in multi-hop ordinary architectures. The proposed architecture has been implemented on top of POX controller and Advanced Message Queuing Protocol (AMQP) protocol. The experiments were conducted in a Mininet-wifi emulator, the results present the architecture control plane consistency and two application cases: topology discovery and QoS monitoring. The current results push us to study QoS-routing for video streaming over WMN.

ACS Style

Hisham Elzain; Yang Wu. Software Defined Wireless Mesh Network Flat Distribution Control Plane. Future Internet 2019, 11, 166 .

AMA Style

Hisham Elzain, Yang Wu. Software Defined Wireless Mesh Network Flat Distribution Control Plane. Future Internet. 2019; 11 (8):166.

Chicago/Turabian Style

Hisham Elzain; Yang Wu. 2019. "Software Defined Wireless Mesh Network Flat Distribution Control Plane." Future Internet 11, no. 8: 166.

Journal article
Published: 12 May 2019 in Future Internet
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Words have different meanings (i.e., senses) depending on the context. Disambiguating the correct sense is important and a challenging task for natural language processing. An intuitive way is to select the highest similarity between the context and sense definitions provided by a large lexical database of English, WordNet. In this database, nouns, verbs, adjectives, and adverbs are grouped into sets of cognitive synonyms interlinked through conceptual semantics and lexicon relations. Traditional unsupervised approaches compute similarity by counting overlapping words between the context and sense definitions which must match exactly. Similarity should compute based on how words are related rather than overlapping by representing the context and sense definitions on a vector space model and analyzing distributional semantic relationships among them using latent semantic analysis (LSA). When a corpus of text becomes more massive, LSA consumes much more memory and is not flexible to train a huge corpus of text. A word-embedding approach has an advantage in this issue. Word2vec is a popular word-embedding approach that represents words on a fix-sized vector space model through either the skip-gram or continuous bag-of-words (CBOW) model. Word2vec is also effectively capturing semantic and syntactic word similarities from a huge corpus of text better than LSA. Our method used Word2vec to construct a context sentence vector, and sense definition vectors then give each word sense a score using cosine similarity to compute the similarity between those sentence vectors. The sense definition also expanded with sense relations retrieved from WordNet. If the score is not higher than a specific threshold, the score will be combined with the probability of that sense distribution learned from a large sense-tagged corpus, SEMCOR. The possible answer senses can be obtained from high scores. Our method shows that the result (50.9% or 48.7% without the probability of sense distribution) is higher than the baselines (i.e., original, simplified, adapted and LSA Lesk) and outperforms many unsupervised systems participating in the SENSEVAL-3 English lexical sample task.

ACS Style

Korawit Orkphol; Wu Yang. Word Sense Disambiguation Using Cosine Similarity Collaborates with Word2vec and WordNet. Future Internet 2019, 11, 114 .

AMA Style

Korawit Orkphol, Wu Yang. Word Sense Disambiguation Using Cosine Similarity Collaborates with Word2vec and WordNet. Future Internet. 2019; 11 (5):114.

Chicago/Turabian Style

Korawit Orkphol; Wu Yang. 2019. "Word Sense Disambiguation Using Cosine Similarity Collaborates with Word2vec and WordNet." Future Internet 11, no. 5: 114.

Journal article
Published: 05 January 2019 in Applied Sciences
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WiFi infrastructures are widely deployed in both public and private buildings. They make the connection to the internet more convenient. Recently, researchers find that WiFi signals have the ability to sense the changes in the environment that can detect human motion and even identify human activities and his identity in a device-free manner, and has many potential security applications in a smart home. Previous human detection systems can only detect human motion of regular moving patterns. However, they may have a significant detection performance degradation when used in intrusion detection. In this study, we propose Robust Device-Free Intrusion Detection (RDFID) system leveraging fine-grained Channel State Information (CSI). The noises in the signals are removed by a Principle Component Analysis (PCA) and a low pass filter. We extract a robust feature of frequency domain utilizing Continuous Wavelet Transform (CWT) from all subcarriers. RDFID captures the changes from the whole wireless channel, and a threshold is obtained self-adaptively, which is calibration-free in different environments, and can be deployed in smart home scenarios. We implement RDFID using commodity WiFi devices and evaluate it in three typical office rooms with different moving patterns. The results show that our system can accurately detect intrusion of different moving patterns and different environments without re-calibration.

ACS Style

Jiguang Lv; Dapeng Man; Wu Yang; Liangyi Gong; Xiaojiang Du; Miao Yu. Robust Device-Free Intrusion Detection Using Physical Layer Information of WiFi Signals. Applied Sciences 2019, 9, 175 .

AMA Style

Jiguang Lv, Dapeng Man, Wu Yang, Liangyi Gong, Xiaojiang Du, Miao Yu. Robust Device-Free Intrusion Detection Using Physical Layer Information of WiFi Signals. Applied Sciences. 2019; 9 (1):175.

Chicago/Turabian Style

Jiguang Lv; Dapeng Man; Wu Yang; Liangyi Gong; Xiaojiang Du; Miao Yu. 2019. "Robust Device-Free Intrusion Detection Using Physical Layer Information of WiFi Signals." Applied Sciences 9, no. 1: 175.

Journal article
Published: 02 November 2017 in Sensors
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Device-free passive identity identification attracts much attention in recent years, and it is a representative application in sensorless sensing. It can be used in many applications such as intrusion detection and smart building. Previous studies show the sensing potential of WiFi signals in a device-free passive manner. It is confirmed that human’s gait is unique from each other similar to fingerprint and iris. However, the identification accuracy of existing approaches is not satisfactory in practice. In this paper, we present Wii, a device-free WiFi-based Identity Identification approach utilizing human’s gait based on Channel State Information (CSI) of WiFi signals. Principle Component Analysis (PCA) and low pass filter are applied to remove the noises in the signals. We then extract several entities’ gait features from both time and frequency domain, and select the most effective features according to information gain. Based on these features, Wii realizes stranger recognition through Gaussian Mixture Model (GMM) and identity identification through a Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. It is implemented using commercial WiFi devices and evaluated on a dataset with more than 1500 gait instances collected from eight subjects walking in a room. The results indicate that Wii can effectively recognize strangers and can achieves high identification accuracy with low computational cost. As a result, Wii has the potential to work in typical home security systems.

ACS Style

Jiguang Lv; Wu Yang; Dapeng Man. Device-Free Passive Identity Identification via WiFi Signals. Sensors 2017, 17, 2520 .

AMA Style

Jiguang Lv, Wu Yang, Dapeng Man. Device-Free Passive Identity Identification via WiFi Signals. Sensors. 2017; 17 (11):2520.

Chicago/Turabian Style

Jiguang Lv; Wu Yang; Dapeng Man. 2017. "Device-Free Passive Identity Identification via WiFi Signals." Sensors 17, no. 11: 2520.

Evaluation study
Published: 28 November 2016 in PLOS ONE
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Application layer firewalls protect the trusted area network against information security risks. However, firewall performance may affect user experience. Therefore, performance analysis plays a significant role in the evaluation of application layer firewalls. This paper presents an analytic model of the application layer firewall, based on a system analysis to evaluate the capability of the firewall. In order to enable users to improve the performance of the application layer firewall with limited resources, resource allocation was evaluated to obtain the optimal resource allocation scheme in terms of throughput, delay, and packet loss rate. The proposed model employs the Erlangian queuing model to analyze the performance parameters of the system with regard to the three layers (network, transport, and application layers). Then, the analysis results of all the layers are combined to obtain the overall system performance indicators. A discrete event simulation method was used to evaluate the proposed model. Finally, limited service desk resources were allocated to obtain the values of the performance indicators under different resource allocation scenarios in order to determine the optimal allocation scheme. Under limited resource allocation, this scheme enables users to maximize the performance of the application layer firewall.

ACS Style

Shichang Xuan; Wu Yang; Hui Dong; Jiangchuan Zhang. Performance Evaluation Model for Application Layer Firewalls. PLOS ONE 2016, 11, e0167280 .

AMA Style

Shichang Xuan, Wu Yang, Hui Dong, Jiangchuan Zhang. Performance Evaluation Model for Application Layer Firewalls. PLOS ONE. 2016; 11 (11):e0167280.

Chicago/Turabian Style

Shichang Xuan; Wu Yang; Hui Dong; Jiangchuan Zhang. 2016. "Performance Evaluation Model for Application Layer Firewalls." PLOS ONE 11, no. 11: e0167280.

Book chapter
Published: 02 November 2016 in Artificial Intelligence: Foundations, Theory, and Algorithms
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The rapid spread of microblog messages and sensitivity of unexpected events make microblog become the center of public opinion. Because of the large amount of microblog message stream and irregular language of microblog message, it is important to detect events of public opinion in microblog. In this paper, we propose DEPO, a system for Detecting Events of Public Opinion in microblog. In DEPO, abnormal messages detection algorithm is used to detect abnormal messages in the real-time microblog message stream. Combined with EPO (Events of Public Opinion) features, each abnormal message can be formalized as EPO features using microblog-oriented keywords extraction method. An online incremental clustering algorithm is proposed to cluster abnormal messages and detect EPO.

ACS Style

Guozhong Dong; Wu Yang; Wei Wang. DEPO: Detecting Events of Public Opinion in Microblog. Artificial Intelligence: Foundations, Theory, and Algorithms 2016, 81 -88.

AMA Style

Guozhong Dong, Wu Yang, Wei Wang. DEPO: Detecting Events of Public Opinion in Microblog. Artificial Intelligence: Foundations, Theory, and Algorithms. 2016; ():81-88.

Chicago/Turabian Style

Guozhong Dong; Wu Yang; Wei Wang. 2016. "DEPO: Detecting Events of Public Opinion in Microblog." Artificial Intelligence: Foundations, Theory, and Algorithms , no. : 81-88.

Conference paper
Published: 17 September 2016 in Transactions on Petri Nets and Other Models of Concurrency XV
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Twitter has become one of largest social networks for users to broadcast burst topics. Influential users usually have a large number of followers and play an important role in the diffusion of burst topic. There have been many studies on how to detect influential users. However, traditional influential users detection approaches have largely ignored influential users in user community. In this paper, we investigate the problem of detecting community pacemakers. Community pacemakers are defined as the influential users that promote early diffusion in the user community of burst topic. To solve this problem, we present DCPBT, a framework that can detect community pacemakers in burst topics. In DCPBT, a burst topic user graph model is proposed, which can represent the topology structure of burst topic propagation across a large number of Twitter users. Based on the model, a user community detection algorithm based on random walk is applied to discover user community. For large-scale user community, we propose a ranking method to detect community pacemakers in each large-scale user community. To test our framework, we conduct the framework over Twitter burst topic detection system. Experimental results show that our method is more effective to detect the users that influence other users and promote early diffusion in the early stages of burst topic.

ACS Style

Guozhong Dong; Wu Yang; Feida Zhu; Wei Wang. Detecting Community Pacemakers of Burst Topic in Twitter. Transactions on Petri Nets and Other Models of Concurrency XV 2016, 245 -255.

AMA Style

Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang. Detecting Community Pacemakers of Burst Topic in Twitter. Transactions on Petri Nets and Other Models of Concurrency XV. 2016; ():245-255.

Chicago/Turabian Style

Guozhong Dong; Wu Yang; Feida Zhu; Wei Wang. 2016. "Detecting Community Pacemakers of Burst Topic in Twitter." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 245-255.

Article
Published: 01 March 2016 in Chinese Journal of Electronics
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We study a new influence maximization problem about how to find a seed set which can maximize the influence spread to a targeted user group in microblogging. To solve this problem, we propose a threestage User group greedy algorithm (UGGreedy) based on user attributes. To reduce network scale, we delete useless user nodes, and rank the rest of users based on user attributes to form a seed candidate set. We employ the seed candidate set to construct a simplified microblogging network graph. We propose a novel influence greedy algorithm based on influence accumulation spread to find the seed set. Experimental results show that UGGreedy can achieve remarkable efficiency on the influence maximization problem for user group in real microblogging networks.

ACS Style

Miao Yu; Wu Yang; Wei Wang; Guowei Shen; Guozhong Dong; Liangyi Gong. UGGreedy: Influence Maximization for User Group in Microblogging. Chinese Journal of Electronics 2016, 25, 241 -248.

AMA Style

Miao Yu, Wu Yang, Wei Wang, Guowei Shen, Guozhong Dong, Liangyi Gong. UGGreedy: Influence Maximization for User Group in Microblogging. Chinese Journal of Electronics. 2016; 25 (2):241-248.

Chicago/Turabian Style

Miao Yu; Wu Yang; Wei Wang; Guowei Shen; Guozhong Dong; Liangyi Gong. 2016. "UGGreedy: Influence Maximization for User Group in Microblogging." Chinese Journal of Electronics 25, no. 2: 241-248.

Conference paper
Published: 24 December 2015 in Communications in Computer and Information Science
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Microblog has been an important medium for providing the rapid communications of public opinion and can quickly publicize a burst topic for discussion when unexpected incidents happen. Abnormal messages are usually the source of burst topics and are important for the diffusion of burst topics. It is necessary to detect abnormal messages from microblog real-time message stream. In this paper, we propose SAMD, a System for Abnormal Messages Detection. In SAMD, sliding time window model is applied to divide the microblog data stream into different shards. Only that the participation of messages exceed initial threshold can be indexed and stored in two-level hash table. An efficient abnormal messages detection model is used to detect abnormal messages in a given time window. The case study on the collected data set can show that SAMD is effective to detect and demonstrate abnormal messages from large-scale microblog message stream.

ACS Style

Guozhong Dong; Bo Wang; Wu Yang; Wei Wang; Rui Sun. SAMD: A System for Abnormal Messages Detection Oriented Microblog Message Stream. Communications in Computer and Information Science 2015, 562, 113 -124.

AMA Style

Guozhong Dong, Bo Wang, Wu Yang, Wei Wang, Rui Sun. SAMD: A System for Abnormal Messages Detection Oriented Microblog Message Stream. Communications in Computer and Information Science. 2015; 562 ():113-124.

Chicago/Turabian Style

Guozhong Dong; Bo Wang; Wu Yang; Wei Wang; Rui Sun. 2015. "SAMD: A System for Abnormal Messages Detection Oriented Microblog Message Stream." Communications in Computer and Information Science 562, no. : 113-124.

Journal article
Published: 21 December 2015 in Sensors
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With the rapid development of WLAN technology, wireless device-free passive human detection becomes a newly-developing technique and holds more potential to worldwide and ubiquitous smart applications. Recently, indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Previous wireless device-free passive human detection systems either rely on deploying specialized systems with dense transmitter-receiver links or elaborate off-line training process, which blocks rapid deployment and weakens system robustness. In the paper, we explore to research a novel fine-grained real-time calibration-free device-free passive human motion via physical layer information, which is independent of indoor scenarios and needs no prior-calibration and normal profile. We investigate sensitivities of amplitude and phase to human motion, and discover that phase feature is more sensitive to human motion, especially to slow human motion. Aiming at lightweight and robust device-free passive human motion detection, we develop two novel and practical schemes: short-term averaged variance ratio (SVR) and long-term averaged variance ratio (LVR). We realize system design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve a high detection rate and low false positive rate.

ACS Style

Liangyi Gong; Wu Yang; Dapeng Man; Guozhong Dong; Miao Yu; Jiguang Lv. WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection. Sensors 2015, 15, 32213 -32229.

AMA Style

Liangyi Gong, Wu Yang, Dapeng Man, Guozhong Dong, Miao Yu, Jiguang Lv. WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection. Sensors. 2015; 15 (12):32213-32229.

Chicago/Turabian Style

Liangyi Gong; Wu Yang; Dapeng Man; Guozhong Dong; Miao Yu; Jiguang Lv. 2015. "WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection." Sensors 15, no. 12: 32213-32229.

Book chapter
Published: 01 January 2014 in Communications in Computer and Information Science
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Along with the widely using of microblog, third party services such as follower markets sell bots to customers to build fake influence and reputation. However, the bots and the customers that have large numbers of followers usually post spam messages such as promoted messages, messages containing malicious links. In this paper, we propose an effective approach for bots detection based on interaction graph model and BP neural network. We build an interaction graph model based on user interaction and design robust interaction-based features. We conduct a comprehensive set of experiments to evaluate the proposed features using different machine learning classifiers. The results of our evaluation experiments show that BP neural network classifier using our proposed features can be effectively used to detect bots compared to other existing state-of-the-art approaches.

ACS Style

Wu Yang; Guozhong Dong; Wei Wang; Guowei Shen; Liangyi Gong; Miao Yu; Jiguang Lv; Yaxue Hu. Detecting Bots in Follower Markets. Communications in Computer and Information Science 2014, 525 -530.

AMA Style

Wu Yang, Guozhong Dong, Wei Wang, Guowei Shen, Liangyi Gong, Miao Yu, Jiguang Lv, Yaxue Hu. Detecting Bots in Follower Markets. Communications in Computer and Information Science. 2014; ():525-530.

Chicago/Turabian Style

Wu Yang; Guozhong Dong; Wei Wang; Guowei Shen; Liangyi Gong; Miao Yu; Jiguang Lv; Yaxue Hu. 2014. "Detecting Bots in Follower Markets." Communications in Computer and Information Science , no. : 525-530.

Book chapter
Published: 01 January 2014 in Advances in Intelligent Systems and Computing
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Recently, co-clustering algorithms are widely used in heterogeneous information networks mining, and the distance metric is still a challenging problem. Bregman divergence is used to measure the distance in traditional co-clustering algorithms, but the hierarchical structure and the feature of the entity itself are not considered. In this paper, an agglomerative hierarchical co-clustering algorithm based on Bregman divergence is proposed to learn hierarchical structure of multiple entities simultaneously. In the aggregation process, the cost of merging two co-clusters is measured by a monotonic Bregman function, integrating heterogeneous relations and features of entities. The robustness of algorithms based on different divergences is tested on synthetic data sets. Experiments on the DBLP data sets show that our algorithm improves the accuracy over existing co-clustering algorithms.

ACS Style

Guowei Shen; Wu Yang; Wei Wang; Miao Yu; Guozhong Dong. Agglomerative Hierarchical Co-clustering Based on Bregman Divergence. Advances in Intelligent Systems and Computing 2014, 389 -398.

AMA Style

Guowei Shen, Wu Yang, Wei Wang, Miao Yu, Guozhong Dong. Agglomerative Hierarchical Co-clustering Based on Bregman Divergence. Advances in Intelligent Systems and Computing. 2014; ():389-398.

Chicago/Turabian Style

Guowei Shen; Wu Yang; Wei Wang; Miao Yu; Guozhong Dong. 2014. "Agglomerative Hierarchical Co-clustering Based on Bregman Divergence." Advances in Intelligent Systems and Computing , no. : 389-398.