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Register a new userSecure Consistency Verification for Untrusted Cloud Storage by Public Blockchains
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Added by
Kai Li
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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This work presents ContractChecker, a Blockchain-based security protocol for verifying the storage consistency between the mutually distrusting cloud provider and clients. Unlike existing protocols, the ContractChecker uniquely delegates log auditing to the Blockchain, and has the advantages in reducing client cost and lowering requirements on client availability, lending itself to modern scenarios with mobile and web clients. The ContractChecker collects the logs from both clients and the cloud server, and verifies the consistency by cross-checking the logs. By this means, it does not only detects the attacks from malicious clients and server forging their logs, but also is able to mitigate those attacks and recover the system from them. In addition, we design new attacks against ContractChecker exploiting various limits in real Blockchain systems (e.g., write unavailability, Blockchain forks, contract race conditions). We analyze and harden the security of ContractChecker protocols against the proposed new attacks. For evaluating the cost, we build a functional prototype of the ContractChecker on Ethereum/Solidity. By experiments on private and public Ethereum testnets, we extensively evaluate the cost of the ContractChecker in comparison with that of existing client-based log auditing works. The result shows the ContractChecker can scale to hundreds of clients and save client costs by more than one order of magnitude.
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Full nodes, which synchronize the entire blockchain history and independently validate all the blocks, form the backbone of any blockchain network by playing a vital role in ensuring security properties. On the other hand, a user running a full node needs to pay a heavy price in terms of storage costs. E.g., the Bitcoin blockchain size has grown over 215GB, in spite of its low throughput. The ledger size for a high throughput blockchain Ripple has already reached 9TB, and it is growing at an astonishing rate of 12GB per day! In this paper, we propose an architecture based on fountain codes, a class of erasure codes, that enables any full node to encode validated blocks into a small number of coded blocks, thereby reducing its storage costs by orders of magnitude. In particular, our proposed Secure Fountain (SeF) architecture can achieve a near-optimal trade-off between the storage savings per node and the bootstrap cost in terms of the number of (honest) storage-constrained nodes a new node needs to contact to recover the blockchain. A key technical innovation in SeF codes is to make fountain codes secure against adversarial nodes that can provide maliciously formed coded blocks. Our idea is to use the header-chain as a side-information to check whether a coded block is maliciously formed while it is getting decoded. Further, the rateless property of fountain codes helps in achieving high decentralization and scalability. Our experiments demonstrate that SeF codes tuned to achieve 1000x storage savings enable full nodes to encode the 191GB Bitcoin blockchain into 195MB on average. A new node can recover the blockchain from an arbitrary set of storage-constrained nodes as long as the set contains ~1100 honest nodes on average. Note that for a 1000x storage savings, the fundamental bound on the number of honest nodes to contact is 1000: we need about 10% more in practice.
We present a new and practical framework for security verification of secure architectures. Specifically, we break the verification task into external verification and internal verification. External verification considers the external protocols, i.e. interactions between users, compute servers, network entities, etc. Meanwhile, internal verification considers the interactions between hardware and software components within each server. This verification framework is general-purpose and can be applied to a stand-alone server, or a large-scale distributed system. We evaluate our verification method on the CloudMonatt and HyperWall architectures as examples.
Nowadays companies are increasingly adopting the technology ofcloud computing. This technology is subject to a lot of research and continuousadvances are made. The use of cloud computing in the companies advantagessuch as: reducing costs, sharing and exchange of information between institutions,but the data in the Cloud computing are susceptible to be compromisedand the companies are exposing to see their data loss. In this study, we addressthe subject of security in cloud computing; we expose and discuss someresearches that had been proposed to secure the data stored in the cloud. Andthen we will present our new frameworks that ensure confidentiality of datastorage in the cloud environment
The blockchain data structure maintained via the longest-chain rule---popularized by Bitcoin---is a powerful algorithmic tool for consensus algorithms. Such algorithms achieve consistency for blocks in the chain as a function of their depth from the end of the chain. While the analysis of Bitcoin guarantees consistency with error $2^{-k}$ for blocks of depth $O(k)$, the state-of-the-art of proof-of-stake (PoS) blockchains suffers from a quadratic dependence on $k$: these protocols, exemplified by Ouroboros (Crypto 2017), Ouroboros Praos (Eurocrypt 2018) and Sleepy Consensus (Asiacrypt 2017), can only establish that depth $Theta(k^2)$ is sufficient. Whether this quadratic gap is an intrinsic limitation of PoS---due to issues such as the nothing-at-stake problem---has been an urgent open question, as deployed PoS blockchains further rely on consistency for protocol correctness. We give an axiomatic theory of blockchain dynamics that permits rigorous reasoning about the longest-chain rule and achieve, in broad generality, $Theta(k)$ dependence on depth in order to achieve consistency error $2^{-k}$. In particular, for the first time, we show that PoS protocols can match proof-of-work protocols for linear consistency. We analyze the associated stochastic process, give a recursive relation for the critical functionals of this process, and derive tail bounds in both i.i.d. and martingale settings via associated generating functions.
With the rapidly changing technological realm, there is an urgent need to provide and protect the confidentiality of confidential images when stored in a cloud environment. To overcome the security risks associated with single cloud, multiple clouds offered by unrelated cloud providers have to be used. This paper outlines an integrated encryption scheme for the secure storage of confidential images on multiple clouds based on DNA sequences.
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