1,326 research outputs found
SoK: A Practical Cost Comparison Among Provable Data Possession Schemes
Provable Data Possession (PDP) schemes provide users with the ability to efficiently audit and verify the integrity of data stored with potentially unreliable third-parties, such as cloud storage service providers. While dozens of PDP schemes have been developed, no PDP schemes have been practically implemented with an existing cloud service. This work attempts to provide a starting point for the integration of PDP schemes with cloud storage service providers by providing a cost analysis of PDP schemes. This cost analysis is performed by implementing and analyzing five PDP schemes representative of the dozens of various PDP approaches. This paper provides analysis of the overhead and performance of each of these schemes to generate a comparable cost for each scheme using real-world cloud pricing models. Results show that the total cost of each scheme is comparable for smaller file sizes, but for larger files this cost can vary across schemes by an order of magnitude. Ultimately, the difference in cost between the simple MAC-based PDP scheme and the most efficient PDP scheme is negligible. While the MAC-PDP scheme may not be the most efficient, no other scheme improving upon it\u27s complexity can be implemented without the use of additional services or APIs leading to the conclusion that the simplest, storage only PDP scheme is the most practical to implement. Furthermore, the findings in this paper suggest that, in general, PDP schemes optimize on an inaccurate cost model and that future schemes should consider the existing economic realities of cloud services
Data storage security and privacy in cloud computing: A comprehensive survey
Cloud Computing is a form of distributed computing wherein
resources and application platforms are distributed over the
Internet through on demand and pay on utilization basis. Data
Storage is main feature that cloud data centres are provided to
the companies/organizations to preserve huge data. But still
few organizations are not ready to use cloud technology due
to lack of security. This paper describes the different
techniques along with few security challenges, advantages and
also disadvantages. It also provides the analysis of data
security issues and privacy protection affairs related to cloud
computing by preventing data access from unauthorized users,
managing sensitive data, providing accuracy and consistency
of data store
Auditable and performant Byzantine consensus for permissioned ledgers
Permissioned ledgers allow users to execute transactions against a data store, and retain proof of their execution in a replicated ledger. Each replica verifies the transactions’ execution and ensures that, in perpetuity, a committed transaction cannot be removed from the ledger. Unfortunately, this is not guaranteed by today’s permissioned ledgers, which can be re-written if an arbitrary number of replicas collude. In addition, the transaction throughput of permissioned ledgers is low, hampering real-world deployments, by not taking advantage of multi-core CPUs and hardware accelerators.
This thesis explores how permissioned ledgers and their consensus protocols can be made auditable in perpetuity; even when all replicas collude and re-write the ledger. It also addresses how Byzantine consensus protocols can be changed to increase the execution throughput of complex transactions. This thesis makes the following contributions:
1. Always auditable Byzantine consensus protocols. We present a permissioned ledger system that can assign blame to individual replicas regardless of how many of them misbehave. This is achieved by signing and storing consensus protocol messages in the ledger and providing clients with signed, universally-verifiable receipts.
2. Performant transaction execution with hardware accelerators. Next, we describe a cloud-based ML inference service that provides strong integrity guarantees, while staying compatible with current inference APIs. We change the Byzantine consensus protocol to execute machine learning (ML) inference computation on GPUs to optimize throughput and latency of ML inference computation.
3. Parallel transactions execution on multi-core CPUs. Finally, we introduce a permissioned ledger that executes transactions, in parallel, on multi-core CPUs. We separate the execution of transactions between the primary and secondary replicas. The primary replica executes transactions on multiple CPU cores and creates a dependency graph of the transactions that the backup replicas utilize to execute transactions in parallel.Open Acces
IA-CCF: Individual accountability for permissioned ledgers
Permissioned ledger systems allow a consortium of members that do not trust one another to execute transactions safely on a set of replicas. Such systems typically use Byzantine fault tolerance (BFT) protocols to distribute trust, which only ensures safety when fewer than 1/3 of the replicas misbehave. Providing guarantees beyond this threshold is a challenge: current systems assume that the ledger is corrupt and fail to identify misbehaving replicas or hold the members that operate them accountable—instead all members share the blame. We describe IA-CCF, a new permissioned ledger system that provides individual accountability. It can assign blame to the individual members that operate misbehaving replicas regardless of the number of misbehaving replicas or members. IA-CCF achieves this by signing and logging BFT protocol messages in the ledger, and by using Merkle trees to provide clients with succinct, universally-verifiable receipts as evidence of successful transaction execution. Anyone can audit the ledger against a set of receipts to discover inconsistencies and identify replicas that signed contradictory statements. IACCF also supports changes to consortium membership and replicas by tracking signing keys using a sub-ledger of governance transactions. IA-CCF provides strong disincentives to misbehavior with low overhead: it executes 47,000 tx/s while providing clients with receipts in two network round trips
Secure, Reliable and Efficient Data Integrity Auditing (DIA) Solution for Public Cloud Storage (PCS)
Light-Weight Accountable Privacy Preserving Protocol in Cloud Computing Based on a Third-Party Auditor
Cloud computing is emerging as the next disruptive utility paradigm [1]. It provides extensive storage capabilities and an environment for application developers through virtual machines. It is also the home of software and databases that are accessible, on-demand. Cloud computing has drastically transformed the way organizations, and individual consumers access and interact with Information Technology. Despite significant advancements in this technology, concerns about security are holding back businesses from fully adopting this promising information technology trend. Third-party auditors (TPAs) are becoming more common in cloud computing implementations. Hence, involving auditors comes with its issues such as trust and processing overhead. To achieve productive auditing, we need to (1) accomplish efficient auditing without requesting the data location or introducing processing overhead to the cloud client; (2) avoid introducing new security vulnerabilities during the auditing process. There are various security models for safeguarding the CCs (Cloud Client) data in the cloud. The TPA systematically examines the evidence of compliance with established security criteria in the connection between the CC and the Cloud Service Provider (CSP). The CSP provides the clients with cloud storage, access to a database coupled with services. Many security models have been elaborated to make the TPA more reliable so that the clients can trust the third-party auditor with their data. Our study shows that involving a TPA might come with its shortcomings, such as trust concerns, extra overhead, security, and data manipulation breaches; as well as additional processing, which leads to the conclusion that a lightweight and secure protocol is paramount to the solution. As defined in [2] privacy-preserving is making sure that the three cloud stakeholders are not involved in any malicious activities coming from insiders at the CSP level, making sure to remediate to TPA vulnerabilities and that the CC is not deceitfully affecting other clients. In our survey phase, we have put into perspective the privacy-preserving solutions as they fit the lightweight requirements in terms of processing and communication costs, ending up by choosing the most prominent ones to compare with them our simulation results. In this dissertation, we introduce a novel method that can detect a dishonest TPA: The Light-weight Accountable Privacy-Preserving (LAPP) Protocol. The lightweight characteristic has been proven simulations as the minor impact of our protocol in terms of processing and communication costs. This protocol determines the malicious behavior of the TPA. To validate our proposed protocol’s effectiveness, we have conducted simulation experiments by using the GreenCloud simulator. Based on our simulation results, we confirm that our proposed model provides better outcomes as compared to the other known contending methods
Secure data storage and retrieval in cloud computing
Nowadays cloud computing has been widely recognised as one of the most inuential information technologies because of its unprecedented advantages. In spite of its widely recognised social and economic benefits, in cloud computing customers lose the direct control of their data and completely rely on the cloud to manage their data and computation, which raises significant security and privacy concerns and is one of the major barriers to the adoption of public cloud by many organisations and individuals. Therefore, it is desirable to apply practical security approaches to address the security risks for the wide adoption of cloud computing
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