S-ORAM: A Segmentation-based Oblivious RAM

As outsourcing data to remote storage servers gets popular, protecting user’s pattern in accessing these data has become a big concern. ORAM constructions are promising solutions to this issue, but their application in practice has been impeded by the high communication and storage overheads incurred. Towards addressing this challenge, this paper proposes a segmentation-based ORAM (S-ORAM). It adopts two segment-based techniques, namely, piece-wise shuffling and segment-based query, to improve the performance of shuffling and query by factoring block size into design. Extensive security analysis shows that S-ORAM is a provably highly secure solution with a negligible failure probability of O(NlogN).In terms of communication and storage overheads, S-ORAM out-performs the Balanced ORAM (B-ORAM) and the Path ORAM (P-ORAM), which are the state-of-the-art hash and index based ORAMs respectively, in both practical and theoretical evaluations. Particularly under practical settings, the communication overhead of S-ORAM is 12 to 23 times less than B-ORAM when they have the same constant-size user-side storage, and S-ORAM consumes 80% less server-side storage and around 60% to 72% less bandwidth than P-ORAM when they have the similar logarithmic-size user-side storage

A Multi-user Oblivious RAM for Outsourced Data

Outsourcing data to remote storage servers has become more and more popular, but the related security and privacy concerns have also been raised. To protect the pattern in which a user accesses the outsourced data, various oblivious RAM (ORAM) systems have been proposed. However, existing ORAM designs assume a single user or a group of mutually-trusted users to access a remote storage, which makes them inapplicable to many practical scenarios where multiple users share data but may not trust each other. Even if the data-sharing users do trust each other, such systems are vulnerable to the compromise of even a single user. To study the feasibility and costs for overcoming the limitation of existing ORAMs in multi-user scenarios, this paper proposes a new type of ORAM system called Multi-user ORAM (M-ORAM). The key idea is to introduce a new component, i.e., a chain of anonymizers, to act as a common proxy between users and the storage server. M-ORAM can protect the data access pattern of each individual user from others as long as not all anonymizers are compromised. Extensive security and overhead analysis has been conducted to quantify the strength of the scheme in protecting an individual user’s access pattern and the costs incurred to provide the protection

An Accountability Scheme for Oblivious RAMs

In outsourced data services, revealing users’ data access pattern may lead to the exposure of a wide range of sensitive information even if data is encrypted. Oblivious RAM has been a well-studied provable solution to access pattern preservation. However, it is not resilient to attacks towards data integrity from the users or the server. In this paper, we study the problem of protecting access pattern privacy and data integrity together in outsourced data services, and propose a scheme that introduces accountability support into a hash-based ORAM design. The proposed scheme can detect misconduct committed by malicious users or server, and identify the attacker, while not interfering with the access pattern preservation mechanisms inherent from the underlying ORAM. This is accomplished at the cost of slightly increased computational, storage, and communication overheads compared with the original ORAM

Privacy-Preserving Accountable Cloud Storage

In cloud storage services, a wide range of sensitive information may be leaked to the host server via the exposure of access pattern albeit data is encrypted. Many security-provable schemes have been proposed to preserve the access pattern privacy; however, they may be vulnerable to attacks towards data integrity or availability from malicious users. This is due to the fact that, preserving access pattern privacy requires data to be frequently re-encrypted and re-positioned at the storage server, which can easily conceal the traces that are needed for account- ability support to detect misbehaviors and identify attackers. To address this issue, this paper proposes a scheme that integrates accountability support into hash-based ORAMs. Security analysis shows that the proposed scheme can detect misconduct committed by malicious users and identify the attackers, while preserving the access pattern privacy. Overhead analysis shows that the proposed accountability support incurs only slightly increased storage, communication, and computational overheads

MU-ORAM: Dealing with Stealthy Privacy Attacks in Multi-User Data Outsourcing Services

Outsourcing data to remote storage servers has become more and more popular, but the related security and privacy concerns have also been raised. To protect the pattern in which a user accesses the outsourced data, various oblivious RAM (ORAM) constructions have been designed. However, when existing ORAM designs are extended to support multi-user scenarios, they become vulnerable to stealthy privacy attacks targeted at revealing the data access patterns of innocent users, even if only one curious or compromised user colludes with the storage server. To study the feasibility and costs of overcoming the above limitation, this paper proposes a new ORAM construction called Multi-User ORAM (MU-ORAM), which is resilient to stealthy privacy attacks. The key ideas in the design are (i) introduce a chain of proxies to act as a common interface between users and the storage server, (ii) distribute the shares of the system secrets delicately to the proxies and users, and (iii) enable a user and/or the proxies to collaboratively query and shuffle data. Through extensive security analysis, we quantify the strength of MU-ORAM in protecting the data access patterns of innocent users from attacks, under the assumption that the server, users, and some but not all proxies can be curious but honest, compromised and colluding. Cost analysis has been conducted to quantify the extra overhead incurred by the MU-ORAM design

SE-ORAM: A Storage-Efficient Oblivious RAM for Privacy-Preserving Access to Cloud Storage

Oblivious RAM (ORAM) is a security-provable approach for protecting clients\u27 access patterns to remote cloud storage. Recently, numerous ORAM constructions have been proposed to improve the communication efficiency of the ORAM model, but little attention has been paid to the storage efficiency. The state-of-the-art ORAM constructions have the storage overhead of $O(N)$ or $O(N\log N)$ blocks at the server, when $N$ data blocks are hosted. To fill the blank, this paper proposes a storage-efficient ORAM (SE-ORAM) construction with configurable security parameter $\lambda$ and zero storage overhead at the server. Extensive analysis has also been conducted and the results show that, SE-ORAM achieves the configured level of security, introduces zero storage overhead to the storage server (i.e., the storage server only storages $N$ data blocks), and incurs $O(\log N)$ blocks storage overhead at the client, as long as $\lambda\geq 2$ and each node on the storage tree stores $4\log N$ or more data blocks

Differential microRNA expression between shoots and rhizomes in Oryza longistaminata using high-throughput RNA sequencing

AbstractPlant microRNAs (miRNAs) play important roles in biological processes such as development and stress responses. Although the diverse functions of miRNAs in model organisms have been well studied, their function in wild rice is poorly understood. In this study, high-throughput small RNA sequencing was performed to characterize tissue-specific transcriptomes in Oryza longistaminata. A total of 603 miRNAs, 380 known rice miRNAs, 72 conserved plant miRNAs, and 151 predicted novel miRNAs were identified as being expressed in aerial shoots and rhizomes. Additionally, 99 and 79 miRNAs were expressed exclusively or differentially, respectively, in the two tissues, and 144 potential targets were predicted for the differentially expressed miRNAs in the rhizomes. Functional annotation of these targets suggested that transcription factors, including squamosa promoter binding proteins and auxin response factors, function in rhizome growth and development. The expression levels of several miRNAs and target genes in the rhizomes were quantified by RT-PCR, and the results indicated the existence of complex regulatory mechanisms between the miRNAs and their targets. Eight target cleavage sites were verified by RNA ligase-mediated rapid 5′ end amplification. These results provide valuable information on the composition, expression and function of miRNAs in O. longistaminata, and will aid in understanding the molecular mechanisms of rhizome development

Targeting suicidal ideation in major depressive disorder with MRI-navigated Stanford accelerated intelligent neuromodulation therapy

High suicide risk represents a serious problem in patients with major depressive disorder (MDD), yet treatment options that could safely and rapidly ameliorate suicidal ideation remain elusive. Here, we tested the feasibility and preliminary efficacy of the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT) in reducing suicidal ideation in patients with MDD. Thirty-two MDD patients with moderate to severe suicidal ideation participated in the current study. Suicidal ideation and depression symptoms were assessed before and after 5 days of open-label SAINT. The neural pathways supporting rapid-acting antidepressant and suicide prevention effects were identified with dynamic causal modelling based on resting-state functional magnetic resonance imaging. We found that 5 days of SAINT effectively alleviated suicidal ideation in patients with MDD with a high response rate of 65.63%. Moreover, the response rates achieved 78.13% and 90.63% with 2 weeks and 4 weeks after SAINT, respectively. In addition, we found that the suicide prevention effects of SAINT were associated with the effective connectivity involving the insula and hippocampus, while the antidepressant effects were related to connections of the subgenual anterior cingulate cortex (sgACC). These results show that SAINT is a rapid-acting and effective way to reduce suicidal ideation. Our findings further suggest that distinct neural mechanisms may contribute to the rapid-acting effects on the relief of suicidal ideation and depression, respectively