Encrypted Shared Data Spaces

The deployment of Share Data Spaces in open, possibly hostile, environments arises the need of protecting the confidentiality of the data space content. Existing approaches focus on access control mechanisms that protect the data space from untrusted agents. The basic assumption is that the hosts (and their administrators) where the data space is deployed have to be trusted. Encryption schemes can be used to protect the data space content from malicious hosts. However, these schemes do not allow searching on encrypted data. In this paper we present a novel encryption scheme that allows tuple matching on completely encrypted tuples. Since the data space does not need to decrypt tuples to perform the search, tuple confidentiality can be guaranteed even when the data space is deployed on malicious hosts (or an adversary gains access to the host). Our scheme does not require authorised agents to share keys for inserting and retrieving tuples. Each authorised agent can encrypt, decrypt, and search encrypted tuples without having to know other agents’ keys. This is beneficial inasmuch as it simplifies the task of key management. An implementation of an encrypted data space based on this scheme is described and some preliminary performance results are given

Security and Efficiency Analysis of the Hamming Distance Computation Protocol Based on Oblivious Transfer

open access articleBringer et al. proposed two cryptographic protocols for the computation of Hamming distance. Their first scheme uses Oblivious Transfer and provides security in the semi-honest model. The other scheme uses Committed Oblivious Transfer and is claimed to provide full security in the malicious case. The proposed protocols have direct implications to biometric authentication schemes between a prover and a verifier where the verifier has biometric data of the users in plain form. In this paper, we show that their protocol is not actually fully secure against malicious adversaries. More precisely, our attack breaks the soundness property of their protocol where a malicious user can compute a Hamming distance which is different from the actual value. For biometric authentication systems, this attack allows a malicious adversary to pass the authentication without knowledge of the honest user's input with at most $O(n)$ complexity instead of $O(2^n)$, where $n$ is the input length. We propose an enhanced version of their protocol where this attack is eliminated. The security of our modified protocol is proven using the simulation-based paradigm. Furthermore, as for efficiency concerns, the modified protocol utilizes Verifiable Oblivious Transfer which does not require the commitments to outputs which improves its efficiency significantly

Update on hepatorenal Syndrome: Definition, Pathogenesis, and management

Hepatorenal syndrome (HRS) is acute kidney injury (AKI) that occurs without evidence of structural abnormalities in the kidneys in patients with liver disease. It is thought to be due to splanchnic vasculature dilatation that is associated with intense increase of renal arteries’ tone, leading to renal cortex ischemia and AKI. Nitric oxide, endotoxins, neurohormonal changes, bacterial infection, high serum bilirubin and bile acids are examples for factors contributing to HRS development. Nevertheless, other unknown factors may have role in HRS pathophysiology. Hence, further discussion and research are needed to clearly understand HRS. Plasma volume restoration and vasoconstrictors are the cornerstone of HRS treatment. Others such as octreotide, noradrenaline, infection control, systemic inflammatory response prevention, shunting, and renal replacement therapy are currently used to manage HRS. Liver or combined liver and kidney transplantation is currently the ultimate cure for HRS. This review was written to help in better understanding the pathogenesis, diagnosis, and treatment options for HRS

Threshold password-authenticated key exchange

Abstract. In most password-authenticated key exchange systems there is a single server storing password verification data. To provide some resilience against server compromise, this data typically takes the form of a one-way function of the password (and possibly a salt, or other public values), rather than the password itself. However, if the server is compromised, this password verification data can be used to perform an offline dictionary attack on the user’s password. In this paper we propose an efficient password-authenticated key exchange system involving a set of servers, in which a certain threshold of servers must participate in the authentication of a user, and in which the compromise of any fewer than that threshold of servers does not allow an attacker to perform an offline dictionary attack. We prove our system is secure in the random oracle model under the Decision Diffie-Hellman assumption against an attacker that may eavesdrop on, insert, delete, or modify messages between the user and servers, and that compromises fewer than that threshold of servers.

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

Structure-Preserving Smooth Projective Hashing

International audienceSmooth projective hashing has proven to be an extremely useful primitive, in particular when used in conjunction with commitments to provide implicit decommitment. This has lead to applications proven secure in the UC framework, even in presence of an adversary which can do adaptive corruptions, like for example Password Authenticated Key Exchange (PAKE), and 1-out-of-m Oblivious Transfer (OT). However such solutions still lack in efficiency, since they heavily scale on the underlying message length. Structure-preserving cryptography aims at providing elegant and efficient schemes based on classical assumptions and standard group operations on group elements. Recent trend focuses on constructions of structure- preserving signatures, which require message, signature and verification keys to lie in the base group, while the verification equations only consist of pairing-product equations. Classical constructions of Smooth Projective Hash Function suffer from the same limitation as classical signatures: at least one part of the computation (messages for signature, witnesses for SPHF) is a scalar. In this work, we introduce and instantiate the concept of Structure- Preserving Smooth Projective Hash Function, and give as applications more efficient instantiations for one-round PAKE and three-round OT, and information retrieval thanks to Anonymous Credentials, all UC- secure against adaptive adversaries

Homomorphic Secret Sharing for Low Degree Polynomials

Homomorphic secret sharing (HSS) allows $n$ clients to secret-share data to $m$ servers, who can then homomorphically evaluate public functions over the shares. A natural application is outsourced computation over private data. In this work, we present the first plain-model homomorphic secret sharing scheme that supports the evaluation of polynomials with degree higher than 2. Our construction relies on any degree-$k$ (multi-key) homomorphic encryption scheme and can evaluate degree-$\left( (k+1)m -1 \right)$ polynomials, for any polynomial number of inputs $n$ and any sub-logarithmic (in the security parameter) number of servers $m$. At the heart of our work is a series of combinatorial arguments on how a polynomial can be split into several low-degree polynomials over the shares of the inputs, which we believe is of independent interest