Public cloud data auditing with practical key update and zero knowledge privacy

Data integrity is extremely important for cloud based storage services, where cloud users no longer have physical possession of their outsourced files. A number of data auditing mechanisms have been proposed to solve this problem. However, how to update a cloud user\u27s private auditing key (as well as the authenticators those keys are associated with) without the user\u27s re-possession of the data remains an open problem. In this paper, we propose a key-updating and authenticator-evolving mechanism with zero-knowledge privacy of the stored files for secure cloud data auditing, which incorporates zero knowledge proof systems, proxy re-signatures and homomorphic linear authenticators. We instantiate our proposal with the state-of-the-art Shacham-Waters auditing scheme. When the cloud user needs to update his key, instead of downloading the entire file and re-generating all the authenticators, the user can just download and update the authenticators. This approach dramatically reduces the communication and computation cost while maintaining the desirable security. We formalize the security model of zero knowledge data privacy for auditing schemes in the key-updating context and prove the soundness and zero-knowledge privacy of the proposed construction. Finally, we analyze the complexity of communication, computation and storage costs of the improved protocol which demonstrates the practicality of the proposal

Parallel improved Schnorr-Euchner enumeration SE++ on shared and distributed memory systems, with and without extreme pruning

The security of lattice-based cryptography relies on the hardness of problems based on lattices, such as the Shortest Vector Problem (SVP) and the Closest Vector Problem (CVP). This paper presents two parallel implementations for the SE++ with and without extreme pruning. The SE++ is an enumeration-based CVP-solver, which can be easily adapted to solve the SVP. We improved the SVP version of the SE++ with an optimization that avoids symmetric branches, improving its performance by a factor of ≈ 50%, and applied the extreme pruning technique to this improved version. The extreme pruning technique is the fastest way to compute the SVP with enumeration known to date. It solves the SVP for lattices in much higher dimensions in less time than implementations without extreme pruning. Our parallel implementation of the SE++ with extreme pruning targets distributed memory multi-core CPU systems, while our SE++ without extreme pruning is designed for shared memory multi-core CPU systems. These implementations address load balancing problems for optimal performance, with a master-slave mechanism on the distributed memory implementation, and specific bounds for task creation on the shared memory implementation. The parallel implementation for the SE++ without extreme pruning scales linearly for up to 8 threads and almost linearly for 16 threads. In addition, it also achieves super-linear speedups on some instances, as the workload may be shortened, since some threads may find shorter vectors at earlier points in time, compared to the sequential implementation. Tests with our Improved SE++ implementation showed that it outperforms the state of the art implementation by a factor of between 35% and 60%, while maintaining a scalability similar to the SE++ implementation. Our parallel implementation of the SE++ with extreme pruning achieves linear speedups for up to 8 (working) processes and speedups of up to 13x for 16 (working) processes(undefined)info:eu-repo/semantics/publishedVersio

Public Auditing for Ensuring Cloud Data Storage Security With Zero Knowledge Privacy

In cloud storage service, clients upload their data together with authentication information to cloud storage server. To ensure the availability and integrity of clients\u27 stored data, cloud server(CS) must prove to a verifier that he is actually storing all of the client\u27s data unchanged. And, enabling public auditability for cloud storage is of critical importance to users with constrained computing resources, who can resort to a third party auditor (TPA) to check the integrity of outsourced data. However, most of the existing proofs of retrievability schemes or proof of data possession schemes do not consider data privacy problem. Zero knowledge privacy requires TPA or the adversary can not deduce any information of the file data from auditing system. In this paper, after giving a new construction of a recently proposed cryptographic primitive named aggregatable signature based broadcast (ASBB) encryption scheme, we present an efficient public auditing scheme with zero knowledge privacy. The new scheme is as efficient as the scheme presented by Shacham and Waters without considering privacy and is secure in the random oracle model

Fair signature exchange via delegation on ubiquitous networks

This paper addresses the issue of autonomous fair signature exchange in emerging ubiquitous (u-) commerce systems, which require that the exchange task be delegated to authorised devices for its autonomous and secure execution. Relevant existing work is either inefficient or ineffective in dealing with such delegated exchange. To rectify this situation, this paper aims to propose an effective, efficient and secure solution to the delegated exchange to support the important autonomy feature offered by u-commerce systems. The proposed work includes a novel approach to symmetric-key based verifiable proxy encryption to make the exchange delegation flexible, efficient and simple to implement on resource-limited devices commonly used in u-commerce systems. This approach is then applied to design a new exchange protocol. An analysis of the protocol is also provided to confirm its security and fairness. Moreover, a comparison with related work is presented to demonstrate its much better efficiency and simplicity

Flush+Reload: a High Resolution, Low Noise, L3 Cache Side-Channel Attack

Sharing memory pages between non-trusting processes is a common method of reducing the memory footprint of multi-tenanted systems. In this paper we demonstrate that, due to a weakness in the Intel X86 processors, page sharing exposes processes to information leaks. We present FLUSH+RELOAD, a cache side-channel attack technique that exploits this weakness to monitor access to memory lines in shared pages. Unlike previous cache side-channel attacks, FLUSH+RELOAD targets the Last- Level Cache (i.e. L3 on processors with three cache levels). Consequently, the attack program and the victim do not need to share the execution core. We demonstrate the efficacy of the FLUSH+RELOAD attack by using it to extract the private encryption keys from a victim program running GnuPG 1.4.13. We tested the attack both between two unrelated processes in a single operating system and between processes running in separate virtual machines. On average, the attack is able to recover 96.7% of the bits of the secret key by observing a single signature or decryption round

DupLESS: Server-Aided Encryption for Deduplicated Storage

Cloud storage service providers such as Dropbox, Mozy, and others perform deduplication to save space by only storing one copy of each file uploaded. Should clients conventionally encrypt their files, however, savings are lost. Message-locked encryption (the most prominent manifestation of which is convergent encryption) resolves this tension. However it is inherently subject to brute-force attacks that can recover files falling into a known set. We propose an architecture that provides secure deduplicated storage resisting brute-force attacks, and realize it in a system called DupLESS. In DupLESS, clients encrypt under message-based keys obtained from a key-server via an oblivious PRF protocol. It enables clients to store encrypted data with an existing service, have the service perform deduplication on their behalf, and yet achieves strong confidentiality guarantees. We show that encryption for deduplicated storage can achieve performance and space savings close to that of using the storage service with plaintext data

Anonymous Point Collection - Improved Models and Security Definitions

This work is a comprehensive, formal treatment of anonymous point collection. The proposed definition does not only provide a strong notion of security and privacy, but also covers features which are important for practical use. An efficient realization is presented and proven to fulfill the proposed definition. The resulting building block is the first one that allows for anonymous two-way transactions, has semi-offline capabilities, yields constant storage size, and is provably secure

Anonymous Point Collection - Improved Models and Security Definitions

This work is a comprehensive, formal treatment of anonymous point collection. The proposed definition does not only provide a strong notion of security and privacy, but also covers features which are important for practical use. An efficient realization is presented and proven to fulfill the proposed definition. The resulting building block is the first one that allows for anonymous two-way transactions, has semi-offline capabilities, yields constant storage size, and is provably secure