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    25 March 2018, Volume 39 Issue 3
    Special Issue on Internet of Things and Its Security
    Survey on data security and privacy-preserving for the research of edge computing
    Jiale ZHANG,Yanchao ZHAO,Bing CHEN,Feng HU,Kun ZHU
    2018, 39(3):  1-21.  doi:10.11959/j.issn.1000-436x.2018037
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    With the rapid development and extensive application of the Internet of things (IoT),big data and 5G network architecture,the massive data generated by the edge equipment of the network and the real-time service requirements are far beyond the capacity if the traditional cloud computing.To solve such dilemma,the edge computing which deploys the cloud services in the edge network has envisioned to be the dominant cloud service paradigm in the era of IoT.Meanwhile,the unique features of edge computing,such as content perception,real-time computing,parallel processing and etc.,has also introduced new security problems especially the data security and privacy issues.Firstly,the background and challenges of data security and privacy-preserving in edge computing were described,and then the research architecture of data security and privacy-preserving was presented.Secondly,the key technologies of data security,access control,identity authentication and privacy-preserving were summarized.Thirdly,the recent research advancements on the data security and privacy issues that may be applied to edge computing were described in detail.Finally,some potential research points of edge computing data security and privacy-preserving were given,and the direction of future research work was pointed out.

    Survey of the Internet of things operating system security
    Anni PENG,Wei ZHOU,Yan JIA,Yuqing ZHANG
    2018, 39(3):  22-34.  doi:10.11959/j.issn.1000-436x.2018040
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    With the rapid popularization and wide application of the Internet of things (IoT),the security problems of IoT operating system,which is the essential part,become more and more urgent.Firstly,the famous IoT operating systems and their different features were introduced,then it was compared with present embedded systems.Secondly,On the basis of the survey of research related to IoT operating system,the research was discussed and analyzed from the view of building a comprehensive security system,then security challenges and opportunities which the IoT system faced were pointed out,and the research status of the security of the IoT operating system was summarized.Finally,the promising future study directions in the IoT operating system security field were discussed based on the drawbacks of the existing researches,particularly,the IoT system survival technology as a new research direction was pointed out.

    Research progress of sensor-cloud security
    Tian WANG,Yang LI,Weijia JIA,Guojun WANG,Shaoliang PENG
    2018, 39(3):  35-52.  doi:10.11959/j.issn.1000-436x.2018035
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    Through consulting lots of domestic and international literatures about sensor-cloud security,a series of security problems are found,such as reputation problem of service provider,the coupling problem of physical nodes,the leak of authority management,et al,which seriously hinders the further development of sensor-cloud.The secure problems occurring in sensor-cloud were analyzed,the current secure technologies were contrasted ,similarities and differences of various types solutions were discussed and summarized.After that,several future challenges of sensor-cloud security were concluded.Finally,a fog-based structure was proposed to solve the security problems,which would bring new ideas to the sensor-cloud security research.

    Low-latency algorithm for improving data persistence in mobile low-duty-cycle wireless sensor network
    Chan JIANG,Taoshen LI,Junbin LIANG
    2018, 39(3):  53-62.  doi:10.11959/j.issn.1000-436x.2018041
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    Mobile low-duty-cycle wireless sensor network (MLDC-WSN) are a kind of new ad hoc networks that are appeared in recent years.In MLDC-WSN,the nodes only have limited storage spaces.Moreover,the nodes would move or sleep from time to time.Therefore,these networks have some problems such as connectivity is hard to be maintained and data are hard to be transmitted to their destinations for storage in time.As a result,data persistence (i.e.,the probability that all data can be recovered after some nodes die in the networks) is low.A distributed algorithm named LT-MDS for improving data persistence in MLDC-WSN was proposed.The algorithm used a new infectious data dissemination method to transmit the data,which enabled the data to be received by almost all the mobile nodes in a network with low latency and improved the reliability of the network.When a node receives the data,it would use LT (Luby transform) codes to encode and save them.By this way,the nodes with limited storage spaces can save more data information.Theoretical analyses and simulations show that LT-MDS can complete the process of data dissemination and preservation with low latency,and it can achieve high data persistence.

    Modeling and verifying based on timed automata of Internet of things gateway security system
    Guoqing WANG,Lei ZHUANG,Ruimin WANG,Yu SONG,Kunli ZHANG
    2018, 39(3):  63-75.  doi:10.11959/j.issn.1000-436x.2018042
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    The Internet of things (IoT) is a multiple heterogeneous network,and its perception layer is often faced with various security threats.As the bridge between the perception layer and the network layer,the IoT gateway should have the security management function to prevent the security issue from spreading to the upper layer.According to the current security deficiencies in IoT gateway,a universal IoT gateway security system was proposed based on the IoT gateway middleware technology.Various security protocols or algorithms can be embedded in IoT gateway security system,and the modeling and analysis can help the design and implementation of IoT gateway.The formal modeling and verification of the IoT gateway security system was performed by timed automata.The results show that the IoT gateway security system satisfies the security properties of confidentiality,availability,authenticity,robustness,integrity and freshness.

    Dynamic Mix-zone scheme with joint-entropy based metric for privacy-perserving in IoV
    Xia FENG,Yawei LIU
    2018, 39(3):  76-85.  doi:10.11959/j.issn.1000-436x.2018038
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    Aiming at the weak flexibility and lack of users’ transparency existing in the current Mix-zone schemes for Internet of vehicle (IoV),a dynamic was proposed for Mix-zone construction with traffic adaption,which could construct a Mix-zone for the vehicles dynamically according to the traffic conditions for changing pseudonym at anytime and anywhere.This kind of Mix-zone could achieve privacy-preserving based on the identity and location.In addition,a novel traffic-adaptive metric was presented for classifying the privacy leveled in Mix-zone,which applied the normalization quantitation to measure the degree of Mix-zone’s privacy demanding by the current region.It was verified that the joint entropy-based privacy measuring model and the Mix-zone construction scheme by utilizing the trajectory data of taxis in certain district in Shenzhen city.The experimental shows that the proposed combination entropy-based model could depict the proportional relationship between the traffic scene parameters and the privacy-preserving degrees.The scheme is better in performance over the related methods,and strikes a good balance between location privacy and service usability.

    Cooperative secret key generation for multi-hop relaying systems in Internet of things
    Shuaifang XIAO,Yunfei GUO,Kaizhi HUANG,Liang JIN
    2018, 39(3):  86-94.  doi:10.11959/j.issn.1000-436x.2018036
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    The achievable key rate of secret key generation method in multi-hop relaying systems was relative low in Internet of things.A cooperative secret key generation algorithm based on network coding was proposed to improve the achievable key rate.Firstly,all the nodes send training sequences in turn to estimate the channels.After that the relays employ secure network coding technique to assist the two legitimate users to obtain the correlative observations of the same wireless channel,with nothing leakage about the channel information to the eavesdropper.Finally,the two legitimate users agreed on a common secret key directly over the public channel.Theoretical and simulation results validate the performance of the proposed secret key generation algorithm,and obtain that increasing the wireless transmission paths,selecting the transmission path with less hops and larger variance channels can further improve the achievable secret key rate.

    Coverage optimization algorithm based on VF-CS in mobile sensor network
    Guanghui LI,Shihong HU
    2018, 39(3):  95-107.  doi:10.11959/j.issn.1000-436x.2018039
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    A random placement of large-scale sensor network in the outdoor environment often causes low coverage.An area coverage optimization algorithm of mobile sensor network (MSN) based on virtual force perturbation and Cuckoo search (VF-CS) was proposed.Firstly,the virtual force of the sensor nodes within the Thiessen polygon was analyzed based on the partitioning of Voronoi diagram of the monitoring area.Secondly,the force of polygon vertices and neighbor nodes was taken as the perturbation factor for updating the node’s location of the Cuckoo search (CS).Finally,the VF-CS guided the node to move so as to achieve the optimal coverage.The simulation results demonstrate that the proposed algorithm has higher coverage and shorter average moving distance of nodes than the Voronoi diagram based algorithms in literatures.

    Papers
    Driving behavior recognition and prediction based on Bayesian model
    Xinsheng WANG,Zhen BIAN
    2018, 39(3):  108-117.  doi:10.11959/j.issn.1000-436x.2018043
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    Since the existing intelligent driving systems are lack of efficiency and accuracy when processing huge number of driving data,a brand new approach of processing driving data was developed to identify and predicate human driving behavior based on Bayesian model.The approach was proposed to take two steps to deduce the specific driving behavior from driving data correspondingly without any supervision,the first step being using Bayesian model segmentation algorithm to divide driving data that inertial sensor collected into near-linear segments with the help of Bayesian model segmentation algorithm,and the second step being using extended LDA model to aggregate those linear segments into specific driving behavior (such as braking,turning,acceleration and coasting).Both offline and online experiments are conducted to verify this approach and it turns out that approach has higher efficiency and recognition accuracy when dealing with numerous driving data.

    Reversible digital watermarking-based protocol for data integrity in wireless sensor network
    Wenxian JIANG,Zhenxing ZHANG,Jingjing WU
    2018, 39(3):  118-127.  doi:10.11959/j.issn.1000-436x.2018046
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    For the contradiction between high energy consumption of WSN privacy protection algorithm and constrained resources of sensor network,a recoverable data fusion protocol that ensures data integrity and confidentiality based on reversible digital watermarking and homomorphic encryption technology was proposed.On the one hand,the data from the sensor was embedded by the difference expansion method by using the reversible digital watermarking technique,and original data could be recovered by using a reversible watermark to ensure the integrity check of the fusion data when the fusion data were destroyed.On the other hand,elliptic curve homomorphic encryption encrypted data to prevent sensor data from being perceived during data transmission.Security results show that the proposed protocol performs well against cluster head node compromise as well as tampering from an attack.Performance analysis shows that the protocol has significant advantages over other algorithms in terms of computation,communication overhead and propagation delay.The experimental results show that the protocol has a low resource overhead and improves network performance.

    Privacy-preserving attribute-based encryption scheme on ideal lattices
    Xixi YAN,Yuan LIU,Zichen LI,Yongli TANG,Qing YE
    2018, 39(3):  128-135.  doi:10.11959/j.issn.1000-436x.2018048
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    Based on the small key size and high encryption efficiency on ideal lattices,a privacy-preserving attribute-based encryption scheme on ideal lattices was proposed,which could support flexible access policies and privacy protection for the users.In the scheme,a semi-hidden policy was introduced to protect the users’ privacy.Thus,the sensitive values of user’s attributes are hidden to prevent from revealing to any third parties.In addition,the extended Shamir secret-sharing schemes was used to construct the access tree structure which can support “and” “or” and “threshold” operations of attributes with a high flexibility.Besides,the scheme was proved to be secure against chosen plaintext attack under the standard mode.Compared to the existing related schemes,the scheme can yield significant performance benefits,especially the size of system public/secret keys,users’ secret key and ciphertext.It is more effective in the large scale distributed environment.

    MAXGDDP:decision data release with differential privacy
    Jibin FU,Xiaojian ZHANG,Liping DING
    2018, 39(3):  136-146.  doi:10.11959/j.issn.1000-436x.2018049
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    Specialization-based private decision data release has attracted considerable research attention in recent years.The relation among hierarchical node,taxonomy tree,and budget allocation directly constrains the accuracy of data release and classification.Most existing methods based on hierarchical specialization cannot efficiently address the above problems.An effective method was proposed,called MAXGDDP to publish decision data with specialization.MAXGDDP employed MAX index attribute selection algorithm to select the highlight concept for furthering specialization in each hierarchy.Besides,for making more rational use of privacy budget,MAXGDDP relied on geometric strategy to allocate the privacy budget in each hierarchy.Compared with existing methods such as DiffGen on the real datasets,MAXGDDP outperforms its competitors,achieves data privacy and the better result of classification simultaneously.

    User recommendation based on cross-platform online social networks
    Jian PENG,Tuntun WANG,Yu CHEN,Tang LIU,Wenzheng XU
    2018, 39(3):  147-158.  doi:10.11959/j.issn.1000-436x.2018044
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    In the field of online social networks on user recommendation,researchers extract users’ behaviors as much as possible to model the users.However,users may have different likes and dislikes in different social networks.To tackle this problem,a cross-platform user recommendation model was proposed,users would be modeled all-sided.In this study,the Sina micro blog and the Zhihu were investigated in the proposed model,the experimental results show that the proposed model is competitive.Based on the proposed model and the experimental results,it can be known that modeling users in cross-platform online social networks can describe the user more comprehensively and leads to a better recommendation.

    SPRD:fast application repackaging detection approach in Android based on application’s UI and program dependency graph
    Run WANG,Li’na WANG,Benxiao TANG,Lei ZHAO
    2018, 39(3):  159-171.  doi:10.11959/j.issn.1000-436x.2018045
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    A two stage detection approach which combine application’s UI and program code based on the observation that repackaging applications merely modify the structure of their user interface was proposed.Firstly,a fast hash similarity detection technique based on an abstracted representation of UI to identify the potential visual-similar repackaging applications was designed.Secondly,program dependency graph is used to represent as the feature of app to achieve fine-grained and precise code clone detection.A prototype system,SPRD,was implemented based on the proposed approach.Experimental results show that the proposed approach achieves a good performance in both scalability and accuracy,and can be effectively applied in millions of applications and billions of code detection.

    Game theory based forwarding control method for social network
    Fangfang SHAN,Hui LI,Hui ZHU
    2018, 39(3):  172-180.  doi:10.11959/j.issn.1000-436x.2018051
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    With the rapid development of mobile communication and internet technology,the social network has become one of the mainstream social means used in people’s daily social life.To maintain and strengthen relationships with friends,users may share personal behavior and feelings through social networks.Forwarding these contents may result in privacy leakage.To help publishers make proper data forwarding decision,the benefits of both sides of the forwarding operation were analyzed,and a game theory based forwarding control method for social network was proposed which could effectively prevent dishonest data forwarding operation.By analyzing the benefits of both sides of forwarding operation and considering historical information,the probability of dishonest data forwarding operation was calculated and it was compared with the threshold set by publisher to make the forwarding decision.The procedure and framework of the game theory based forwarding control method was introduced.The benefits of both sides were defined and analyzed.The game play scenario was presented.Some results of experiments are shown to support that the method is effective and it can protect the security of content in social network.

    Locality-guided based optimization method for bounded model checker
    Shun WANG,Ye DU,Zhen HAN,Jiqiang LIU
    2018, 39(3):  181-190.  doi:10.11959/j.issn.1000-436x.2018050
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    For software model checking,approaches that combine with different kind of verification methods are now under research.The key to improve scale and complexity of verifiable software is handling the method for abstraction widening and strengthening wisely and precisely.To archive that,using extra knowledge that extracted from programming pattern or learned through verifying procedure to help eliminate the redundant state has been proved effective.Definition of program locality was given.It took the important role in accelerating software verification,then the strategy was raised and an algorithm was implemented to take advantage of program locality.This method exploits the features of modern BMC (bounded model checker) and scales up the capability of its power in large scale and comprehensive software modules.

    Joint channel and impulsive noise estimation method for OFDM systems
    Xinrong LYU,Youming LI,Mingchen YU
    2018, 39(3):  191-198.  doi:10.11959/j.issn.1000-436x.2018047
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    Aiming at the impulsive noise occurring in OFDM systems,an impulsive noise mitigation algorithm based on compressed sensing theory was proposed.The proposed algorithm firstly treated the channel impulse response and the impulsive noise as a joint sparse vector by exploiting the sparsity of both them.Then the sparse Bayesian learning framework was adopted to jointly estimate the channel impulse response,the impulsive noise and the data symbols,in which the data symbols were regarded as unknown parameters.Compared with the existing impulsive noise mitigation methods,the proposed algorithm not only utilized all subcarriers but also did not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed algorithm achieves significant improvement on the channel estimation and bit error rate performance.

Copyright Information
Authorized by: China Association for Science and Technology
Sponsored by: China Institute of Communications
Editor-in-Chief: Zhang Ping
Associate Editor-in-Chief:
Zhang Yanchuan, Ma Jianfeng, Yang Zhen, Shen Lianfeng, Tao Xiaofeng, Liu Hualu
Editorial Director: Wu Nada, Zhao Li
Address: F2, Beiyang Chenguang Building, Shunbatiao No.1 Courtyard, Fengtai District, Beijing, China
Post: 100079
Tel: 010-53933889、53878169、
53859522、010-53878236
Email: xuebao@ptpress.com.cn
Email: txxb@bjxintong.com.cn
ISSN 1000-436X
CN 11-2102/TN
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