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Toward Secure and Dependable Storage Services in Cloud
                                  Computing
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.

Reasons for the proposal :

Moving data into the cloud offers great convenience to users since they don’t have
to care about the complexities of direct hardware management. While these
internet-based online services eliminate the responsibility of local machines for
data maintenance at the same time. As a result, users are at the mercy of their cloud
service providers (CSP) for the availability and integrity of their data .

To increase the profit margin by reducing cost, it is possible for CSP to discard
rarely accessed data without being detected in a timely fashion. Similarly, CSP
may even attempt to hide data loss incidents so as to maintain a reputation. In order
to achieve the assurances of cloud data integrity and availability and enforce the
quality of cloud storage service, efficient methods that enable on-demand data
correctness verification on behalf of cloud users have to be designed.

Existing system & Demerits:

Recently, the importance of ensuring the remote data integrity has been highlighted
by the following research works under different system and security models. These
techniques, while can be useful to ensure the storage correctness without having
users possessing local data, are all focusing on single server scenario. They may be
useful for quality-of-service testing ,but does not guarantee the data availability in
case of server failures. Although direct applying these techniques to distributed
storage (multiple servers) could be straightforward, the resulted storage
verification overhead would be linear to the number of servers. As an
complementary approach, researchers have also proposed distributed protocols for
ensuring storage correctness across multiple servers or peers.

However, while providing efficient cross server storage verification and data
availability insurance, these schemes are all focusing on static or archival data. As
a result, their capabilities of handling dynamic data remains unclear,which
inevitably limits their full applicability in cloud storage scenarios.

Proposed system :
In this paper, we propose an effective and flexible distributed storage verification
scheme with explicit dynamic data support to ensure the correctness and
availability of users’ data in the cloud. We rely on erasure correcting code in the
file distribution preparation to provide redundancies and guarantee the data
dependability against Byzantine servers , where a storage server may fail in
arbitrary ways. This construction drastically reduces the communication and
storage overhead as compared to the traditional replication-based file distribution
techniques. By utilizing the homomorphic token with distributed verification of
erasure-coded data, our scheme achieves the storage correctness insurance as well
as data error localization: whenever data corruption has been detected during the
storage correctness verification, our scheme can almost guarantee the simultaneous
localization of data errors, i.e., the identification of the misbehaving server(s). In
order to save the time, computation resources, and even the related online burden
of users, we also provide the extension of the proposed main scheme to support
third-party auditing, where users can safely delegate the integrity checking tasks to
third-party auditors (TPA) and be worry-free to use the cloud storage services.

Our contribution can be summarized as the following three aspects:

1) Compared to many of its predecessors, which only provide binary results about
the storage status across the distributed servers, the proposed scheme achieves the
integration of storage correctness insurance and data error localization, i.e., the
identification of misbehaving server(s).

2) Unlike most prior works for ensuring remote data integrity, the new scheme
further supports secure and efficient dynamic operations on data blocks, including:
update, delete, and append.
Architecture diagram :

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Toward secure and dependable

  • 1. Toward Secure and Dependable Storage Services in Cloud Computing 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. Reasons for the proposal : Moving data into the cloud offers great convenience to users since they don’t have to care about the complexities of direct hardware management. While these internet-based online services eliminate the responsibility of local machines for
  • 2. data maintenance at the same time. As a result, users are at the mercy of their cloud service providers (CSP) for the availability and integrity of their data . To increase the profit margin by reducing cost, it is possible for CSP to discard rarely accessed data without being detected in a timely fashion. Similarly, CSP may even attempt to hide data loss incidents so as to maintain a reputation. In order to achieve the assurances of cloud data integrity and availability and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. Existing system & Demerits: Recently, the importance of ensuring the remote data integrity has been highlighted by the following research works under different system and security models. These techniques, while can be useful to ensure the storage correctness without having users possessing local data, are all focusing on single server scenario. They may be useful for quality-of-service testing ,but does not guarantee the data availability in case of server failures. Although direct applying these techniques to distributed storage (multiple servers) could be straightforward, the resulted storage verification overhead would be linear to the number of servers. As an complementary approach, researchers have also proposed distributed protocols for ensuring storage correctness across multiple servers or peers. However, while providing efficient cross server storage verification and data availability insurance, these schemes are all focusing on static or archival data. As a result, their capabilities of handling dynamic data remains unclear,which inevitably limits their full applicability in cloud storage scenarios. Proposed system :
  • 3. In this paper, we propose an effective and flexible distributed storage verification scheme with explicit dynamic data support to ensure the correctness and availability of users’ data in the cloud. We rely on erasure correcting code in the file distribution preparation to provide redundancies and guarantee the data dependability against Byzantine servers , where a storage server may fail in arbitrary ways. This construction drastically reduces the communication and storage overhead as compared to the traditional replication-based file distribution techniques. By utilizing the homomorphic token with distributed verification of erasure-coded data, our scheme achieves the storage correctness insurance as well as data error localization: whenever data corruption has been detected during the storage correctness verification, our scheme can almost guarantee the simultaneous localization of data errors, i.e., the identification of the misbehaving server(s). In order to save the time, computation resources, and even the related online burden of users, we also provide the extension of the proposed main scheme to support third-party auditing, where users can safely delegate the integrity checking tasks to third-party auditors (TPA) and be worry-free to use the cloud storage services. Our contribution can be summarized as the following three aspects: 1) Compared to many of its predecessors, which only provide binary results about the storage status across the distributed servers, the proposed scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). 2) Unlike most prior works for ensuring remote data integrity, the new scheme further supports secure and efficient dynamic operations on data blocks, including: update, delete, and append.