Ligang Zheng^1,*, Chao Song²

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 529-539, 2018, DOI:10.3970/cmc.2018.03780

Abstract There is a steep increase in data encoded as symmetric positive definite (SPD) matrix in the past decade. The set of SPD matrices forms a Riemannian manifold that constitutes a half convex cone in the vector space of matrices, which we sometimes call SPD manifold. One of the fundamental problems in the application of SPD manifold is to find the nearest neighbor of a queried SPD matrix. Hashing is a popular method that can be used for the nearest neighbor search. However, hashing cannot be directly applied to SPD manifold due to its non-Euclidean intrinsic More >

En Zhang^1,2, Xintao Duan^1,2, Siuming Yiu³, Junbin Fang⁴, Zoe L. Jiang^5,*, Tsz HonYuen⁶, Jie Peng¹

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 401-414, 2018, DOI:10.3970/cmc.2018.03733

Abstract In the setting of (t, n) threshold secret sharing, at least t parties can reconstruct the secret, and fewer than t parties learn nothing about the secret. However, to achieve fairness, the existing secret sharing schemes either assume a trusted party exists or require running multi-round, which is not practical in a real application. In addition, the cost of verification grows dramatically with the number of participants and the communication complexity is O(t), if there is not a trusted combiner in the reconstruction phase. In this work, we propose a fair server-aided multi-secret sharing scheme for weak… More >

Suzhen Wang¹, Yanpiao Zhang¹, Lu Zhang¹, Ning Cao^{2, *}, Chaoyi Pang³

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 415-431, 2018, DOI:10.3970/cmc.2018.03716

Abstract Spark is a fast unified analysis engine for big data and machine learning, in which the memory is a crucial resource. Resilient Distribution Datasets (RDDs) are parallel data structures that allow users explicitly persist intermediate results in memory or on disk, and each one can be divided into several partitions. During task execution, Spark automatically monitors cache usage on each node. And when there is a RDD that needs to be stored in the cache where the space is insufficient, the system would drop out old data partitions in a least recently used (LRU) fashion… More >

Yanzhong Wang¹, Xiangyu Wu^1,*

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 353-363, 2018, DOI:10.3970/cmc.2018.03714

Abstract To investigate the effects of configuration parameters and operation condition on the thermal behavior of novel conical friction plate, a three-dimensional finite element model of conical friction plate is established for numerical simulation. The conical surface configuration and friction heat generation of novel conical friction surfaces are discussed. The results indicate that the thermal behavior of the conical friction plate during continuously sliding period is influenced by the conical surface configuration. Maximum temperature occurs in the conical friction plate with cone angle of 24°. The maximum temperature value of friction plate is increased 7.4°C, when More >

Daofeng Li^1,3,*, Mingxing Luo², Bowen Zhao^1,3, Xiangdong Che⁴

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 447-465, 2018, DOI:10.3970/cmc.2018.03692

Abstract The secure issues of APK are very important in Android applications. In order to solve potential secure problems and copyrights issues in redevelopment of APK files, in this paper we propose a new APK redevelopment mechanism (APK-SAN). By exploring sanitizable signature technology, APK-SAN allows the original developer to authorize specified modifier who can redevelop the designated source code of APK files. Our scheme does not require interactions between the developer and modifiers. It can reduce the communication overhead and computational overhead for developers. Especially, the signature of redeveloped APK files is valid and maintains the More >

Zhiqiang Ruan^1,*, Haibo Luo¹, Wenzhong Lin¹, Jie Wang²

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 483-499, 2018, DOI:10.3970/cmc.2018.03687

Abstract Content caching is a core component in Named Data Networking (NDN), where content is cached in routers and served for future requests. However, the adversary can launch verification attack by placing poisoned data into the network with a legitimate name and allow the routers in the delivery path to frequently identify the content. Since NDN employs digital signature on each piece of content, verifying all content will exhaust routers’ computational resources due to the massive data in the network. In this paper, we propose a selective verification scheme upon the contents that are hit in More >

Bo Xiao¹, Zhen Wang², Qi Liu^3,*, Xiaodong Liu³

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 365-379, 2018, DOI:10.3970/cmc.2018.01830

Abstract In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also come along with it. Therefore, more research work has been devoted to the problem of outlier detection in big data. However, the existing available methods have high computation time, the improved algorithm of outlier detection is presented, which has higher performance to detect outlier. In this paper, an improved algorithm is proposed. The SMK-means More >

Jixian Zhang¹, Ning Xie¹, Xuejie Zhang¹, Kun Yue¹, Weidong Li^2,*, Deepesh Kumar³

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 123-135, 2018, DOI:10.3970/cmc.2018.03728

Abstract Resource allocation in auctions is a challenging problem for cloud computing. However, the resource allocation problem is NP-hard and cannot be solved in polynomial time. The existing studies mainly use approximate algorithms such as PTAS or heuristic algorithms to determine a feasible solution; however, these algorithms have the disadvantages of low computational efficiency or low allocate accuracy. In this paper, we use the classification of machine learning to model and analyze the multi-dimensional cloud resource allocation problem and propose two resource allocation prediction algorithms based on linear and logistic regressions. By learning a small-scale training More >

Zhen Yang^1,2, Yongfeng Huang^1,2,*, Xing Li^1,2, Wenyu Wang³

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 1-17, 2018, DOI:10.3970/cmc.2018.03697

Abstract To cope with privacy leakage caused by multimedia outsourcing and sharing, data provenance is used to analyze leaked multimedia and provide reactive accountability. Existing schemes of multimedia provenance are based on watermarking protocols. In an outsourcing scenario, existing schemes face two severe challenges: 1) when data leakage occurs, there exists a probability that data provenance results can be repudiated, in which case data provenance tracking fails; and 2) when outsourced data are shared, data encryption transfer causes key management burden outside the schemes, and privacy leakage threatens users. In this paper, we propose a novel More >

Faguo Wu^1,2, Xiao Zhang^1,2, Wang Yao^1,2, Zhiming Zheng^1,2, Lipeng Xiang³, Wanpeng Li⁴

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 19-34, 2018, DOI:10.3970/cmc.2018.02664

Abstract Signature, widely used in cloud environment, describes the work as readily identifying its creator. The existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum algorithm. In this paper, we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring (ETRUS) which ensures our signature scheme proceed in a lattice with higher density. We proved that ETRUS highly improve the performance of traditional lattice signature schemes. Moreover, the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution More >