239 research outputs found
Risk-Based Privacy-Aware Access Control for Threat Detection Systems
No full textThreat detection systems collect and analyze a large amount of security data logs for detecting potential attacks. Since log data from enterprise systems may contain sensitive and personal information access should be limited to the data relevant to the task at hand as mandated by data protection regulations. To this end, data need to be pre-processed (anonymized) to eliminate or obfuscate the sensitive information that is not-strictly necessary for the task. Additional security/accountability measures may be also applied to reduce the privacy risk, such as logging the access to the personal data or imposing deletion obligations. Anonymization reduces the privacy risk, but it should be carefully applied and balanced with utility requirements of the different phases of the process: a preliminary analysis may require fewer details than an in-depth investigation on a suspect set of logs. We propose a risk-based privacy-aware access control framework for threat detection systems, where each access request is evaluated by comparing the privacy-risk and the trustworthiness of the request. When the risk is too large compared to the trust level, the framework can apply adaptive adjustment strategies to decrease the risk (e.g., by selectively obfuscating the data) or to increase the trust level to perform a given task (e.g., imposing enforceable obligations to the user). We show how the framework can simultaneously address both the privacy and the utility requirements. The experimental results presented in the paper that the framework leads to meaningful results, and real-time performance, within an industrial threat detection solution
A redescription of Tephritis zonogastra Bezzi, 1913 (Diptera: Trypetidae).
No full textDie vorliegende Arbeit enthält eine ausführliche Nachbeschreibung von Tephritis zonogastra Bezzi, ES wird vermutet, daß Bezzi\u27s Holotypus, obgleich seine Beschreibung keine Angaben über das Geschlecht enthält, ein Männchen war, so daß hiermit die Neubeschreibung des Weibchens vorgelegt werden kann.Tephritis zonogastra Bezzi is redescribed in detail. It is suggested that although Bezzi in his original description made no mention of the sex,the holotype described by him was a male. The description of the female given by the present author may, therefore, be regarded as new
Imaging Features of Non-Alcoholic Fatty Liver Disease in Children and Adolescents
No full textNon-invasive diagnosis and quantification of liver steatosis is important to overcome limits of liver biopsy, in order to follow up patients during their therapy and to establish a reference standard that can be used in clinical trials and longitudinal studies. Imaging offers several methods in this setting: ultrasound, which is the cheapest technique and easy to perform; magnetic resonance spectroscopy (MRS), which reflects the real content of triglycerides in a specific volume; and proton density fat fraction (PDFF) magnetic resonance, which is a simple method that reflects the distribution of the fat in the whole liver. Other techniques include ultrasound elastography (EUS) and magnetic resonance elastrography (MRE), which can evaluate the progression of non-alcoholic fatty liver disease (NAFLD) into non-alcoholic steato-hepatitis (NASH) and cirrhosis, by quantifying liver fibrosis
Redundancy and Synergy Arising From Pairwise Correlations In Neuronal Ensembles
No full textMultielectrode arrays allow recording of the activity of many single neurons, from which correlations can be calculated. The functional roles of correlations can be revealed by measures of the information conveyed by neuronal activity; a simple formula has been shown to discriminate the information transmitted by individual spikes from the positive or negative contributions due to correlations (Panzeri et al, Proc. Roy. Soc. B., 266: 1001-1012 (1999)). The formula quanti es the corrections to the single-unit instantaneous information rate which result from correlations in spike emission between pairs of neurons. Positive corrections imply synergy, while negative corrections indicate redundancy. Here, this analysis, previously applied to recordings from small ensembles, is developed further by considering a model of a large ensemble, in which correlations among the signal and noise components of neuronal ring are small in absolute value and entirely random in origin. Even such small random correlations are shown to lead to large possible synergy or redundancy, whenever the time window for extracting information from neuronal ring extends to the order of the mean interspike interval. In addition, a sample of recordings from rat barrel cortex illustrates the mean time window at which such `corrections' dominate when correlations are, as often in the real brain, neither random nor small. The presence of this kind of correlations for a large ensemble of cells restricts further the time of validity of the expansion
Balancing Trust and Risk in Access Control
No full textThe increasing availability of large and diverse datasets (big data) calls for increased flexibility in access control so to improve the exploitation of the data. Risk-aware access control systems offer a natural approach to the problem. We propose a novel access control framework that combines trust with risk and supports access control in dynamic contexts through trust enhancement mechanisms and risk mitigation strategies. This allows to strike a balance between the risk associated with a data request and the trustworthiness of the requester. If the risk is too large compared to the trust level, then the framework can identify adaptive strategies leading to a decrease of the risk (e.g., by removing/obfuscation part of the data through anonymization) or to increase the trust level (e.g., by asking for additional obligations to the requester). We outline a modular architecture to realize our model, and we describe how these strategies can be actually realized in a realistic use case
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