An Efficient Public Auditing Protocol With Novel Dynamic Structure for Cloud Data

Shen, Jian; Shen, Jun; Chen, Xiaofeng; Huang, Xinyi; Susilo, Willy

doi:10.1109/tifs.2017.2705620

Cited by 337 publications

(140 citation statements)

References 39 publications

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“…Reference [16] suggested learning the overall experiences in recommending services, environmental factors, and user input data. Reference [17] designed an efficient public auditing protocol with novel dynamic structure for cloud data that could effectively improve the qualities of cloud service recommendation. Reference [20] proposed a novel K + -isomorphism method to achieve K-anonymization state among subgraphs or detected communities in a given social network.…”

Section: Related Workmentioning

confidence: 99%

Trusted Service Scheduling and Optimization Strategy Design of Service Recommendation

Xia

Zhang

et al. 2017

Security and Communication Networks

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More and more Web services raise the demands of personalized service recommendation; there exist some recommendation technologies, which improve the qualities of service recommendation by using service ranking and collaborative filtering. However, privacy and security are also important issues in service scheduling process; social relationships have been the key factors of interpersonal communication; service selection based on user preferences has become an inevitable trend. Starting from user demand preferences, this paper analyzes social topology and service demand information and obtains trusted social relationships; then we construct the fusion model of service historical preferences and potential ones; according to social service recommendation demands, TSRSR algorithm has completed designing. Through experiments, TSRSR algorithm is much better than the others, which can effectively improve potential preferences' learning. Furthermore, the research results of this paper have more significance to study the security and privacy of service recommendation.

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Section: Related Workmentioning

confidence: 99%

Trusted Service Scheduling and Optimization Strategy Design of Service Recommendation

Xia

Zhang

et al. 2017

Security and Communication Networks

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“…Therefore, the research of privacy protection in cloud computing has attracted considerable attention in recent years [13][14][15]. Among these studies, encrypted-imagebased reversible data hiding (EIRDH) provides the possibility that the image owner can encrypt the image before uploading it to the service provider, and then the service provider can embed some additional message into the incomprehensible encrypted image for steganography or authentication.…”

Section: Introductionmentioning

confidence: 99%

Improved Encrypted-Signals-Based Reversible Data Hiding Using Code Division Multiplexing and Value Expansion

Chen

Zhong

Xiong

et al. 2018

Security and Communication Networks

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Compared to the encrypted-image-based reversible data hiding (EIRDH) method, the encrypted-signals-based reversible data hiding (ESRDH) technique is a novel way to achieve a greater embedding rate and better quality of the decrypted signals. Motivated by ESRDH using signal energy transfer, we propose an improved ESRDH method using code division multiplexing and value expansion. At the beginning, each pixel of the original image is divided into several parts containing a little signal and multiple equal signals. Next, all signals are encrypted by Paillier encryption. And then a large number of secret bits are embedded into the encrypted signals using code division multiplexing and value expansion. Since the sum of elements in any spreading sequence is equal to 0, lossless quality of directly decrypted signals can be achieved using code division multiplexing on the encrypted equal signals. Although the visual quality is reduced, high-capacity data hiding can be accomplished by conducting value expansion on the encrypted little signal. The experimental results show that our method is better than other methods in terms of the embedding rate and average PSNR.

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“…Cloud computing is an Internet-based computing service that can provide task allocation [2] and secure data services [3] to IoT devices on demand [4]. This has led IoT to be a global technology used in many fields, such as ubiquitous cities [5].…”

Section: Introductionmentioning

confidence: 99%

VSMURF: A Novel Sliding Window Cleaning Algorithm for RFID Networks

Shen

Sgandurra

et al. 2017

Journal of Sensors

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Radio Frequency Identification (RFID) is one of the key technologies of the Internet of Things (IoT) and is used in many areas, such as mobile payments, public transportation, smart lock, and environment protection. However, the performance of RFID equipment can be easily affected by the surrounding environment, such as electronic productions and metal appliances. These can impose an impact on the RF signal, which makes the collection of RFID data unreliable. Usually, the unreliability of RFID source data includes three aspects: false negatives, false positives, and dirty data. False negatives are the key problem, as the probability of false positives and dirty data occurrence is relatively small. This paper proposes a novel sliding window cleaning algorithm called VSMURF, which is based on the traditional SMURF algorithm which combines the dynamic change of tags and the value analysis of confidence. Experimental results show that VSMURF algorithm performs better in most conditions and when the tag's speed is low or high. In particular, if the velocity parameter is set to 2 m/epoch, our proposed VSMURF algorithm performs better than SMURF. The results also show that VSMURF algorithm has better performance than other algorithms in solving the problem of false negatives for RFID networks.

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An Efficient Public Auditing Protocol With Novel Dynamic Structure for Cloud Data

Cited by 337 publications

References 39 publications

Trusted Service Scheduling and Optimization Strategy Design of Service Recommendation

Trusted Service Scheduling and Optimization Strategy Design of Service Recommendation

Improved Encrypted-Signals-Based Reversible Data Hiding Using Code Division Multiplexing and Value Expansion

VSMURF: A Novel Sliding Window Cleaning Algorithm for RFID Networks

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