119 research outputs found

    Pseudonymization and its Application to Cloud-based eHealth Systems

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    Responding to the security and privacy issues of information systems, we propose a novel pseudonym solution. This pseudonym solution has provable security to protect the identities of users by employing user-generated pseudonyms. It also provides an encryption scheme to protect the security of the users’ data stored in the public network. Moreover, the pseudonym solution also provides the authentication of pseudonyms without disclosing the users’ identity information. Thus the dependences on powerful trusted third parties and on the trustworthiness of system administrators may be appreciably alleviated. Electronic healthcare systems (eHealth systems), as one kind of everyday information system, with the ability to store and share patients’ health data efficiently, have to manage in-formation of an extremely personal nature. As a consequence of known cases of abuse and attacks, the security of the health data and the privacy of patients are a great concern for many people and thus becoming obstacles to the acceptance and spread of eHealth systems. In this thesis, we survey current eHealth systems in both research and practice, analyzing potential threats to the security and privacy. Cloud-based eHealth systems, in particular, enable applications with many new features in data storing and sharing. We analyze the new issues on security and privacy when cloud technology is introduced into eHealth systems. We demonstrate that our proposed pseudonym solution can be successfully applied to cloud-based eHealth systems. Firstly, we utilize the pseudonym scheme and encryption scheme for storing and retrieving the electronic health records (EHR) in the cloud. The identities of patients and the confidentiality of EHR contents are provably guaranteed by advanced cryptographic algorithms. Secondly, we utilize the pseudonym solution to protect the privacy of patients from the health insurance companies. Only necessary information about patients is disclosed to the health insurance companies, without interrupting the cur-rent normal business processes of health insurance. At last, based on the pseudonym solution, we propose a new procedure for the secondary use of the health data. The new procedure protects the privacy of patients properly and enables patients’ full control and clear consent over their health data to be secondarily used. A prototypical application of a cloud-based eHealth system implementing our proposed solution is presented in order to exhibit the practicability of the solution and to provide intuitive experiences. Some performance estimations of the proposed solution based on the implementation are also provided.Um gewisse Sicherheits- und Datenschutzdefizite heutiger Informationssysteme zu beheben, stellen wir eine neuartige Pseudonymisierungslösung vor, die benutzergenerierte Pseudonyme verwendet und die Identitäten der Pseudonyminhaber nachweisbar wirksam schützt. Sie beinhaltet neben der Pseudonymisierung auch ein Verschlüsselungsverfahren für den Schutz der Vertraulichkeit der Benutzerdaten, wenn diese öffentlich gespeichert werden. Weiterhin bietet sie ein Verfahren zur Authentisierung von Pseudonymen, das ohne die Offenbarung von Benutzeridentitäten auskommt. Dadurch können Abhängigkeiten von vertrauenswürdigen dritten Stellen (trusted third parties) oder von vertrauenswürdigen Systemadministratoren deutlich verringert werden. Elektronische Gesundheitssysteme (eHealth-Systeme) sind darauf ausgelegt, Patientendaten effizient zu speichern und bereitzustellen. Solche Daten haben ein extrem hohes Schutzbedürfnis, und bekannte Fälle von Angriffen auf die Vertraulichkeit der Daten durch Privilegienmissbrauch und externe Attacken haben dazu geführt, dass die Sorge um den Schutz von Gesundheitsdaten und Patientenidentitäten zu einem großen Hindernis für die Verbreitung und Akzeptanz von eHealth-Systemen geworden ist. In dieser Dissertation betrachten wir gegenwärtige eHealth-Systeme in Forschung und Praxis hinsichtlich möglicher Bedrohungen für Sicherheit und Vertraulichkeit der gespeicherten Daten. Besondere Beachtung finden cloudbasierte eHealth-Systeme, die Anwendungen mit neuartigen Konzepten zur Datenspeicherung und -bereitstellung ermöglichen. Wir analysieren Sicherheits- und Vertraulichkeitsproblematiken, die sich beim Einsatz von Cloud-Technologie in eHealth-Systemen ergeben. Wir zeigen, dass unsere Pseudonymisierungslösung erfolgreich auf cloudbasierte eHealth-Systeme angewendet werden kann. Dabei werden zunächst das Pseudonymisierungs- und das Verschlüsselungsverfahren bei der Speicherung und beim Abruf von elektronischen Gesundheitsdatensätzen (electronic health records, EHR) in der Cloud eingesetzt. Die Vertraulichkeit von Patientenidentitäten und EHR-Inhalten werden dabei durch den Einsatz moderner kryptografischer Algorithmen nachweisbar garantiert. Weiterhin setzen wir die Pseudonymisierungslösung zum Schutz der Privatsphäre der Patienten gegenüber Krankenversicherungsunternehmen ein. Letzteren werden lediglich genau diejenigen Patienteninformationen offenbart, die für den störungsfreien Ablauf ihrer Geschäftsprozesse nötig sind. Schließen schlagen wir eine neuartige Vorgehensweise für die Zweitverwertung der im eHealth-System gespeicherten Daten vor, die die Pseudonymisierungslösung verwendet. Diese Vorgehensweise bietet den Patienten angemessenen Schutz für ihre Privatsphäre und volle Kontrolle darüber, welche Daten für eine Zweitverwertung (z.B. für Forschungszwecke) freigegeben werden. Es wird ein prototypisches, cloudbasiertes eHealth-System vorgestellt, das die Pseudonymisierungslösung implementiert, um deren Praktikabilität zu demonstrieren und intuitive Erfahrungen zu vermitteln. Weiterhin werden, basierend auf der Implementierung, einige Abschätzungen der Performanz der Pseudonymisierungslösung angegeben

    Semi-free start collision attack on Blender

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    Blender is a cryptographic hash function submitted to NIST\u27s SHA3 competition. We have found a semi-free start collision attack on Blender with trivial complexity. One pair of semi-free start collision messages with zero initial values is presented

    Attacks on Round-Reduced BLAKE

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    BLAKE is a new hash family proposed for SHA-3. The core of compression function reuses the core function of ChaCha. A round-dependent permutation is used as message schedule. BLAKE is claimed to achieve full diffusion after 2 rounds. However, message words can be controlled on the first several founds. By exploiting properties of message permutation, we can attack 2.5 reduced rounds. The results do not threat the security claimed in the specification

    Collision attack on NaSHA-512

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    The hash function NaSHA is a new algorithm proposed for SHA-3. It follows the wide-pipe structure and compression function adopts quasigroup transformations. These properties of operation in quasigroup raise obstacles to analysis. However, The high probability difference to cause inner collision can be found in the quasigroup transformations. We propose a collision attack to NaSHA-512 with the complexity is 2^{192}, which is lower than the complexity of birthday attack to NaSHA-512. Using the similar method, we can find free-start collision on all versions with negligible complexity

    Vitexin alleviates neuropathic pain in a mouse chronic constriction injury model by inactivation of NF-κB

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    Purpose: To investigate the therapeutic effect of vitexin on neuropathic pain (NP) in a mouse model of chronic constriction injury (CCI).Methods: The CCI model was established by four chronic ligatures in the sciatic nerve. Vitexin was intraperitoneally administered (10 mg/kg, once daily) for 21 days. Mechanical withdrawal threshold (MWT) and paw withdrawal latency (PWL) were determined before and after the establishment of CCI model. The spinal cords were collected to measure mRNA levels by reverse-transcriptase polymerase chain reaction (RT-PCR) enzyme-linked immunosorbent assay (ELISA). Western blot was used to examine protein expression levels.Results: Vitexin reversed the CCI-induced reduction in MWT and PWL values, indicating that it lowered mechanical hypersensitivity response and hyperalgesia caused thermal stimulation (p < 0.05). The elevated levels of IL-6, IL-1β, and TNFα observed in CCI-treated mice were also inhibited by vitexin, suggesting that it suppressed pro-inflammatory cytokines. Moreover, vitexin attenuated CCI-induced activation of NF-κB signaling in CCI-treated mice (p < 0.05).Conclusion: Vitexin alleviates NP by inhibiting pro-inflammatory cytokines and NF-κB signaling in CCItreated mice. Thus, it is a potential target for NP treatment. Keywords: Vitexin, Neuropathic pain, Chronic constriction injury, Mechanical hypersensitivity, Hyperalgesia, NF-κ

    QoE-driven resource allocation for D2D underlaying NOMA cellular networks

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    Device-to-device (D2D) communication can significantly improve network coverage and spectral efficiency. Meanwhile, non-orthogonal multiple access (NOMA) has recently been integrated with D2D communication to further improve connection density and satisfy explosive data rate requirements of end users. Considering quality of experience (QoE) has become an important indicator from the user perspective, in this paper, we study the QoE-driven resource allocation problem in a device-to-device (D2D) underlaying NOMA cellular network coexisting with D2D pairs and NOMA-based cellular users (CUs). Our target is to maximize the sum mean opinion scores (MOSs) of all users while guaranteeing the minimum QoE requirement of each CU and D2D pair, by jointly optimizing subchannel assignment and power allocation at CUs and D2D pairs. Since this problem is mixed-integer and non-convex, we first transform it into an equivalent yet more tractable form. Then, a two-stage iterative algorithm based on the alternating optimization framework and constrained concave-convex procedure technique is proposed to optimize subchannel assignment and power allocation alternately. Simulation results show that the proposed scheme outperforms the orthogonal multiple access solution and three NOMA based benchmark schemes in terms of QoE performance.acceptedVersionPeer reviewe

    Measuring Quantum Entanglement from Local Information by Machine Learning

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    Entanglement is a key property in the development of quantum technologies and in the study of quantum many-body simulations. However, entanglement measurement typically requires quantum full-state tomography (FST). Here we present a neural network-assisted protocol for measuring entanglement in equilibrium and non-equilibrium states of local Hamiltonians. Instead of FST, it can learn comprehensive entanglement quantities from single-qubit or two-qubit Pauli measurements, such as R\'enyi entropy, partially-transposed (PT) moments, and coherence. It is also exciting that our neural network is able to learn the future entanglement dynamics using only single-qubit traces from the previous time. In addition, we perform experiments using a nuclear spin quantum processor and train an adoptive neural network to study entanglement in the ground and dynamical states of a one-dimensional spin chain. Quantum phase transitions (QPT) are revealed by measuring static entanglement in ground states, and the entanglement dynamics beyond measurement time is accurately estimated in dynamical states. These precise results validate our neural network. Our work will have a wide range of applications in quantum many-body systems, from quantum phase transitions to intriguing non-equilibrium phenomena such as quantum thermalization.Comment: 5 pages, 4 figures. All comments are welcom

    Arginine Alters miRNA Expression Involved in Development and Proliferation of Rat Mammary Tissue

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    This study was designed to determine the effects of dietary arginine on development and proliferation in rat mammary tissue through changes in miRNA profiles. Twelve pregnant Wistar rats were allocated randomly to two groups. A basal diet containing arginine or the control diet containing glutamate on an equal nitrogen basis as the arginine supplemented diet were used. The experiment included a pre-experimental period of four days before parturition and an experimental period of 17 days after parturition. Mammary tissue was collected for histology, RNA extraction and high-throughput sequencing analysis. The greater mammary acinar area indicated that arginine supplementation enhanced mammary tissue development (p < 0.01). MicroRNA profiling indicated that seven miRNA (miR-206-3p, miR-133a-5p, miR-133b-3p, miR-1-3p, miR-133a-3p, miR-1b and miR-486) were differentially expressed in response to Arginine when compared with the glutamate-based control group. In silico gene ontology enrichment and KEGG pathway analysis revealed between 240 and 535 putative target genes among the miRNA. Further verification by qPCR revealed concordance with the differential expression from the sequencing results: 17 of 28 target genes were differentially expressed (15 were highly expressed in arginine and 2 in control) and 11 target genes did not have significant difference in expression. In conclusion, our study suggests that arginine may potentially regulate the development of rat mammary glands through regulating miRNAs
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