The Experts below are selected from a list of 15558 Experts worldwide ranked by ideXlab platform

Haiying Shen - One of the best experts on this subject based on the ideXlab platform.

  • An Economical and SLO-Guaranteed Cloud Storage Service Across Multiple Cloud Service Providers
    2017
    Co-Authors: Haiying Shen, Haoyu Wang
    Abstract:

    It is important for Cloud Service brokers to provide a multi-Cloud Storage Service to minimize their payment cost to Cloud Service providers (CSPs) while providing Service level objective (SLO) guarantee to their customers. Many multi-Cloud Storage Services have been proposed or payment cost minimization or SLO guarantee. However, no previous works fully leverage the current Cloud pricing policies (such as resource reservation pricing) to reduce the payment cost. Also, few works achieve both cost minimization and SLO guarantee. In this paper, we propose a multi-Cloud Economical and SLO-guaranteed Storage Service (ES3), which determines data allocation and resource reservation schedules with payment cost minimization and SLO guarantee. ES3 incorporates (1) a coordinated data allocation and resource reservation method, which allocates each data item to a datacenter and determines the resource reservation amount on datacenters by leveraging all the pricing policies; (2) a genetic algorithm based data allocation adjustment method, which reduce data Get/Put rate variance in each datacenter to maximize the reservation benefit. We also propose several algorithms to enhance the cost efficient and SLO guarantee performance of ES3 including i) dynamic request redirection, ii) grouped Gets for cost reduction, iii) lazy update for cost-efficient Puts, and iv) concurrent requests for rigid Get SLO guarantee. Our trace-driven experiments on a supercomputing cluster and on real Clouds (i.e., Amazon S3, Windows Azure Storage and Google Cloud Storage) show the superior performance of ES3 in payment cost minimization and SLO guarantee in comparison with previous methods.

  • Minimum-Cost Cloud Storage Service Across Multiple Cloud Providers
    2017
    Co-Authors: Haiying Shen
    Abstract:

    Many Cloud Service providers (CSPs) provide data Storage Services with datacenters distributed worldwide. These datacenters provide different get/put latencies and unit prices for resource utilization and reservation. Thus, when selecting different CSPs' datacenters, Cloud customers of globally distributed applications (e.g., online social networks) face two challenges: 1) how to allocate data to worldwide datacenters to satisfy application Service level objective (SLO) requirements, including both data retrieval latency and availability and2) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. To handle these challenges, we first model the cost minimization problem under SLO constraints using the integer programming. Due to its NP-hardness, we then introduce our heuristic solution, including a dominant-cost-based data allocation algorithm and an optimal resource reservation algorithm. We further propose three enhancement methods to reduce the payment cost and Service latency: 1) coefficient-based data reallocation; 2) multicast-based data transferring; and 3) request redirection-based congestion control. We finally introduce an infrastructure to enable the conduction of the algorithms. Our trace-driven experiments on a supercomputing cluster and on real Clouds (i.e., Amazon S3, Windows Azure Storage, and Google Cloud Storage) show the effectiveness of our algorithms for SLO guaranteed Services and customer cost minimization.

  • Minimum-Cost Cloud Storage Service Across Multiple Cloud Providers
    2016
    Co-Authors: Haiying Shen
    Abstract:

    Many Cloud Service Providers (CSPs) provide data Storage Services with datacenters distributed worldwide. These datacenters provide different Get/Put latencies and unit prices for resource utilization and reservation. Thus, when selecting different CSPs' datacenters, Cloud customers of globally distributed applications (e.g., online social networks) face two challenges: (i) how to allocate data to worldwide datacenters to satisfy application SLO (Service level objective) requirements including both data retrieval latency and availability, and (ii) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. To handle these challenges, we first model the cost minimization problem under SLO constraints using integer programming. Due to its NP-hardness, we then introduce our heuristic solution, including a dominant-cost based data allocation algorithm and an optimal resource reservation algorithm. We finally introduce an infrastructure to enable the conduction of the algorithms. Our trace-driven experiments on a supercomputing cluster and on real Clouds (i.e., Amazon S3, Windows Azure Storage and Google Cloud Storage) show the effectiveness of our algorithms for SLO guaranteed Services and customer cost minimization.

Wenjing Lou - One of the best experts on this subject based on the ideXlab platform.

  • 1Towards Secure and Dependable Storage Services in Cloud Computing
    2016
    Co-Authors: Cong Wang, Ning Cao, Wenjing Lou, Stude Membe, Qia Wang
    Abstract:

    Abstract—Cloud Storage enables users to remotely store their data and enjoy the on-demand high quality Cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a Service is also relinquishing users’ physical possession of their outsourced data, which inevitably poses new security risks towards the correctness of the data in Cloud. In order to address this new problem and further achieve a secure and dependable Cloud Storage Service, we propose in this paper a flexible distributed Storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the Cloud Storage with very lightweight communication and computation cost. The auditing result not only ensures strong Cloud Storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the Cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks. Index Terms—Data integrity, dependable distributed Storage, error localization, data dynamics, Cloud Computing F

  • Y.T.: Lt codes-based secure and reliable Cloud Storage Service
    2016
    Co-Authors: Ning Cao, Zhenyu Yang, Wenjing Lou, Thomas Y. Hou
    Abstract:

    Abstract—With the increasing adoption of Cloud computing for data Storage, assuring data Service reliability, in terms of data correctness and availability, has been outstanding. While redundancy can be added into the data for reliability, the problem becomes challenging in the “pay-as-you-use ” Cloud paradigm where we always want to efficiently resolve it for both corruption detection and data repair. Prior distributed Storage systems based on erasure codes or network coding techniques have either high decoding computational cost for data users, or too much burden of data repair and being online for data owners. In this paper, we design a secure Cloud Storage Service which addresses the reliability issue with near-optimal overall performance. By allowing a third party to perform the public integrity verification, data owners are significantly released from the onerous work of periodically checking data integrity. To completely free the data owner from the burden of being online after data outsourcing, this paper proposes an exact repair solution so that no metadata needs to be generated on the fly for repaired data. The perfor-mance analysis and experimental results show that our designed Service has comparable Storage and communication cost, but much less computational cost during data retrieval than erasure codes-based Storage solutions. It introduces less Storage cost, much faster data retrieval, and comparable communication cost comparing to network coding-based distributed Storage systems. I

  • toward secure and dependable Storage Services in Cloud computing
    2012
    Co-Authors: Cong Wang, Ning Cao, Kui Ren, Qian Wang, Wenjing Lou
    Abstract:

    Cloud Storage enables users to remotely store their data and enjoy the on-demand high quality Cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a Service is also relinquishing users' physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in Cloud. In order to address this new problem and further achieve a secure and dependable Cloud Storage Service, we propose in this paper a flexible distributed Storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the Cloud Storage with very lightweight communication and computation cost. The auditing result not only ensures strong Cloud Storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the Cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

Joseph K Liu - One of the best experts on this subject based on the ideXlab platform.

  • privacy preserving and regular language search over encrypted Cloud data
    2016
    Co-Authors: Kaitai Liang, Xinyi Huang, Fuchun Guo, Joseph K Liu
    Abstract:

    Using Cloud-based Storage Service, users can remotely store their data to Clouds but also enjoy the high quality data retrieval Services, without the tedious and cumbersome local data Storage and maintenance. However, the sole Storage Service cannot satisfy all desirable requirements of users. Over the last decade, privacy-preserving search over encrypted Cloud data has been a meaningful and practical research topic for outsourced data security. The fact of remote Cloud Storage Service that users cannot have full physical possession of their data makes the privacy data search a formidable mission. A naive solution is to delegate a trusted party to access the stored data and fulfill a search task. This, nevertheless, does not scale well in practice as the fully data access may easily yield harm for user privacy. To securely introduce an effective solution, we should guarantee the privacy of search contents, i.e., what a user wants to search, and return results, i.e., what a server returns to the user. Furthermore, we also need to guarantee privacy for the outsourced data, and bring no additional local search burden to user. In this paper, we design a novel privacy-preserving functional encryption-based search mechanism over encrypted Cloud data. A major advantage of our new primitive compared with the existing public key based search systems is that it supports an extreme expressive search mode, regular language search. Our security and performance analysis show that the proposed system is provably secure and more efficient than some searchable systems with high expressiveness.

Kouichi Sakurai - One of the best experts on this subject based on the ideXlab platform.

  • cross group secret sharing for secure Cloud Storage Service
    2016
    Co-Authors: Hiroaki Anada, Junpei Kawamoto, Kirill Morozov, Kouichi Sakurai
    Abstract:

    With the spread of the Internet, many mobile devices are used in our daily lives, such as tablets and mobile phones. Then, personal data are often saved on data servers of the Storage providers such as Amazon, Google, Yahoo, Baidu and others. In this context, the secret sharing can be used to store personal data onto several providers, simultaneously reducing the risk of data loss, the data leakage to unauthorized parties, and data falsification. Secret sharing is one of the solutions to combine security and availability in the distributed Storage. However, few works considered servers' affiliations, and specifically, the problem that a malicious provider may recover secret data illegally through manipulation on servers that hold enough shares to recover the secret. In this paper, to resolve the problem, we propose a two-threshold secret sharing scheme in order to enforce a new type of cross-group policy. By combining t-out-of-m providers' secret sharing scheme and a k-out-of-n servers' secret sharing scheme via an one-way function or an one-time pad, we construct a scheme that forces k shares to be collected from m groups. Compared with previous work, our scheme can attain the functionalities of proactively updating shares and adding new shares with simple computation.

  • realizing fine grained and flexible access control to outsourced data with attribute based cryptosystems
    2011
    Co-Authors: Fangming Zhao, Takashi Nishide, Kouichi Sakurai
    Abstract:

    We consider the problem of constructing a secure Cloud Storage Service to which users outsource sensitive data for sharing with others where, in particular, the Service provider is not completely trusted by the customer. Cloud Storage Service denotes an architectural shift toward thin clients and conveniently centralized provision of both computing and Storage resources. When utilizing Cloud Storage for secure data sharing, one of the main motivating problems of this architecture is providing thin clients with both strong data confidentiality and flexible fine-grained access control without imposing additional cost on them (clients). To achieve this goal, we propose a novel data sharing protocol by combining and exploiting two of the latest attribute based cryptographic techniques, attribute-based encryption (ABE) and attribute-based signature (ABS). Furthermore, we also give a detailed comparison of our scheme with several latest existing schemes.

Rong Hao - One of the best experts on this subject based on the ideXlab platform.

  • enabling public auditing for shared data in Cloud Storage supporting identity privacy and traceability
    2016
    Co-Authors: Guangyang Yang, Wenting Shen, Rong Hao
    Abstract:

    Identity privacy and traceability are very important for shared Cloud data auditing.Design the framework for this problem.Construct the first scheme satisfying the designed framework.Prove the proposed scheme to be secure and justify its performance. Nowadays, Cloud Storage Service has been widely adopted by diverse organizations, through which users can conveniently share data with others. For security consideration, previous public auditing schemes for shared Cloud data concealed the identities of group members. However, the unconstrained identity anonymity will lead to a new problem, that is, a group member can maliciously modify shared data without being identified. Since uncontrolled malicious modifications may wreck the usability of the shared data, the identity traceability should also be retained in data sharing. In this paper, we propose an efficient public auditing solution that can preserve the identity privacy and the identity traceability for group members simultaneously. Specifically, we first design a new framework for data sharing in Cloud, and formalize the definition of the public auditing scheme for shared Cloud data supporting identity privacy and traceability. And then we construct such a scheme, in which a group manager is introduced to help members generate authenticators to protect the identity privacy and two lists are employed to record the members who perform the latest modification on each block to achieve the identity traceability. Besides, the scheme also achieves data privacy during authenticator generation by utilizing blind signature technique. Based on the proposed scheme, we further design an auditing system for practical scenarios. Finally, we prove the proposed scheme is secure based on several security requirements, and justify its performance by concrete implementations.