Eavesdropping Prevention for Network Coding Encrypted Cloud Storage Systems

Chen, Yu-Jia; Wang, Li-Chun; Liao, Chen-Hung

doi:10.1109/tpds.2015.2486772

Cited by 20 publications

(5 citation statements)

References 37 publications

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“…Previous works have shown that network coding can provide robustness [24]- [26] and improve throughput [25], [27] as well as confidentiality [28]. More recently, network coding is employed to improve the security and reliability of distributed storage systems such as recovering lost data in multiple storage nodes [29], preventing eavesdropping over untrusted networks [30] and checking integrity of outsourced data [31].…”

Section: Objective Of This Papermentioning

confidence: 99%

Privacy Protection for Internet of Drones: A Network Coding Approach

Chen

Wang

2019

IEEE Internet Things J.

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Taking into account of both the huge computing power of intruders and the untrustedness of cloud servers, we develop an enhanced secure pseudonym scheme to protect the privacy of mobile cloud data. To face the huge computing power challenge, we develop an unconditionally secure light-weight network coding pseudonym scheme. For the privacy issue of untrusted cloud server, we further design a two-tier network coding to decouple the stored mobile cloud data from the owner's pseudonyms. Therefore, our proposed network coding based pseudonym scheme can simultaneously defend against attackers from both outside and inside. We implement our proposed twotier light-weight network coding mechanism in a group location based service (LBS) using untrusted cloud database. Compared to computationally secure Hash-based pseudonym, our proposed scheme is not only unconditionally secure, but also can reduce more than 90% of processing time as well as 10% of energy consumption.Index Terms-Privacy protection; big data and cloud computing; network coding; location based services.

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Section: Objective Of This Papermentioning

confidence: 99%

Privacy Protection for Internet of Drones: A Network Coding Approach

Chen

Wang

2019

IEEE Internet Things J.

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“…For secure storage over multiple clouds, similar to this work, the authors of [3] proposed a security protection scheme to ensure that no symbols can be decoded by an eavesdropper, which is weaker than perfect secrecy. In [23], a link eavesdropping problem in a networkcoded cloud storage system was investigated. A publicly verifiable protocol for network coded cloud storage was proposed in [24].…”

Section: B Network Coding For Data Securitymentioning

confidence: 99%

An Overflow Problem in Network Coding for Secure Cloud Storage

Chen

Wang

2019

IEEE Trans. Parallel Distrib. Syst.

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In this paper we define the overflow problem of a network coding storage system in which the encoding parameter and the storage parameter are mismatched. Through analyses and experiments, we first show the impacts of the overflow problem in a network coding scheme, which not only waste storage spaces, but also degrade coding efficiency. To avoid the overflow problem, we then develop the network coding based secure storage (NCSS) scheme. Thanks to considering both security and storage requirements in encoding procedures and distributed architectures, the NCSS can improve the performance of a cloud storage system from both the aspects of storage cost and coding processing time. We analyze the maximum allowable stored encoded data under the perfect secrecy criterion, and provide the design guidelines for the secure cloud storage system to enhance coding efficiency and achieve the minimal storage cost.

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“…For example, in the intelligent transportation system, eavesdroppers infer the path planning of vehicles by monitoring the location information, and on this basis, eavesdropping attacks will easily succeed [17,18]. In terms of existing research, data encryption is the main method to protect system privacy from eavesdropping attacks [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Allocation of Eavesdropping Attacks for Multi-System Remote State Estimation

Chang,

Peng,

Zhang

2024

Sensors

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In recent years, the problem of cyber–physical systems’ remote state estimations under eavesdropping attacks have been a source of concern. Aiming at the existence of eavesdroppers in multi-system CPSs, the optimal attack energy allocation problem based on a SINR (signal-to-noise ratio) remote state estimation is studied. Assume that there are N sensors, and these sensors use a shared wireless communication channel to send their state measurements to the remote estimator. Due to the limited power, eavesdroppers can only attack M channels out of N channels at most. Our goal is to use the Markov decision processes (MDP) method to maximize the eavesdropper’s state estimation error, so as to determine the eavesdropper’s optimal attack allocation. We propose a backward induction algorithm which uses MDP to obtain the optimal attack energy allocation strategy. Compared with the traditional induction algorithm, this algorithm has lower computational cost. Finally, the numerical simulation results verify the correctness of the theoretical analysis.

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Eavesdropping Prevention for Network Coding Encrypted Cloud Storage Systems

Cited by 20 publications

References 37 publications

Privacy Protection for Internet of Drones: A Network Coding Approach

Privacy Protection for Internet of Drones: A Network Coding Approach

An Overflow Problem in Network Coding for Secure Cloud Storage

Allocation of Eavesdropping Attacks for Multi-System Remote State Estimation

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