Isabelle Modelchecking for insider threats

The Isabelle Insider framework formalises the technique of social explanation for modeling and analysing Insider threats in infrastructures including physical and logical aspects. However, the abstract Isabelle models need some refinement to provide sufficient detail to explore attacks constructively and understand how the attacker proceeds. The introduction of mutable states into the model leads us to use the concepts of Modelchecking within Isabelle. Isabelle can simply accommodate classical CTL type Modelchecking. We integrate CTL Modelchecking into the Isabelle Insider framework. A running example of an IoT attack on privacy motivates the method throughout and illustrates how the enhanced framework fully supports realistic modeling and analysis of IoT Insiders

Holographic c-theorems in arbitrary dimensions

We re-examine holographic versions of the c-theorem and entanglement entropy in the context of higher curvature gravity and the AdS/CFT correspondence. We select the gravity theories by tuning the gravitational couplings to eliminate non-unitary operators in the boundary theory and demonstrate that all of these theories obey a holographic c-theorem. In cases where the dual CFT is even-dimensional, we show that the quantity that flows is the central charge associated with the A-type trace anomaly. Here, unlike in conventional holographic constructions with Einstein gravity, we are able to distinguish this quantity from other central charges or the leading coefficient in the entropy density of a thermal bath. In general, we are also able to identify this quantity with the coefficient of a universal contribution to the entanglement entropy in a particular construction. Our results suggest that these coefficients appearing in entanglement entropy play the role of central charges in odd-dimensional CFT's. We conjecture a new c-theorem on the space of odd-dimensional field theories, which extends Cardy's proposal for even dimensions. Beyond holography, we were able to show that for any even-dimensional CFT, the universal coefficient appearing the entanglement entropy which we calculate is precisely the A-type central charge.Comment: 62 pages, 4 figures, few typo's correcte

Value of multidetector computed tomography image segmentation for preoperative planning in general surgery

Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery.In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology.The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach.The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems

Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages

This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments

Quantum Fluctuations and the Unruh Effect in Strongly-Coupled Conformal Field Theories

Through the AdS/CFT correspondence, we study a uniformly accelerated quark in the vacuum of strongly-coupled conformal field theories in various dimensions, and determine the resulting stochastic fluctuations of the quark trajectory. From the perspective of an inertial observer, these are quantum fluctuations induced by the gluonic radiation emitted by the accelerated quark. From the point of view of the quark itself, they originate from the thermal medium predicted by the Unruh effect. We scrutinize the relation between these two descriptions in the gravity side of the correspondence, and show in particular that upon transforming the conformal field theory from Rindler space to the open Einstein universe, the acceleration horizon disappears from the boundary theory but is preserved in the bulk. This transformation allows us to directly connect our calculation of radiation-induced fluctuations in vacuum with the analysis by de Boer et al. of the Brownian motion of a quark that is on average static within a thermal medium. Combining this same bulk transformation with previous results of Emparan, we are also able to compute the stress-energy tensor of the Unruh thermal medium.Comment: 1+31 pages; v2: reference adde

Data Stream Clustering for Real-Time Anomaly Detection: An Application to Insider Threats

Insider threat detection is an emergent concern for academia, industries, and governments due to the growing number of insider incidents in recent years. The continuous streaming of unbounded data coming from various sources in an organisation, typically in a high velocity, leads to a typical Big Data computational problem. The malicious insider threat refers to anomalous behaviour(s) (outliers) that deviate from the normal baseline of a data stream. The absence of previously logged activities executed by users shapes the insider threat detection mechanism into an unsupervised anomaly detection approach over a data stream. A common shortcoming in the existing data mining approaches to detect insider threats is the high number of false alarms/positives (FPs). To handle the Big Data issue and to address the shortcoming, we propose a streaming anomaly detection approach, namely Ensemble of Random subspace Anomaly detectors In Data Streams (E-RAIDS), for insider threat detection. E-RAIDS learns an ensemble of p established outlier detection techniques [Micro-cluster-based Continuous Outlier Detection (MCOD) or Anytime Outlier Detection (AnyOut)] which employ clustering over continuous data streams. Each model of the p models learns from a random feature subspace to detect local outliers, which might not be detected over the whole feature space. E-RAIDS introduces an aggregate component that combines the results from the p feature subspaces, in order to confirm whether to generate an alarm at each window iteration. The merit of E-RAIDS is that it defines a survival factor and a vote factor to address the shortcoming of high number of FPs. Experiments on E-RAIDS-MCOD and E-RAIDS-AnyOut are carried out, on synthetic data sets including malicious insider threat scenarios generated at Carnegie Mellon University, to test the effectiveness of voting feature subspaces, and the capability to detect (more than one)-behaviour-all-threat in real-time. The results show that E-RAIDS-MCOD reports the highest F1 measure and less number of false alarm = 0 compared to E-RAIDS-AnyOut, as well as it attains to detect approximately all the insider threats in real-time

Older employees' declining attitudes over 20 years and across classes

British employers, under increasing competitive pressures, and applying new technology and work organization, have sought to reduce labour costs, resulting in work intensification and precarity. Older employees as a result are exposed to work demands that conflict with expectations of favourable treatment in late career. National survey data for Britain in the years 1992, 2001, 2006 and 2012 demonstrate a decline in overall job attitude among older employees following the changed conditions of the 1990s and across the major recession that began in 2008. To assess whether this decline is unequally distributed, decomposition by socio-economic class is carried out. This shows that older employees in the ‘service class’ of managerial and professional employees are affected at least as much as older employees in intermediate and less-skilled classes, thus underlining the age effect and showing that ‘service-class’ employees are not invulnerable to a changing economic environment

On Renormalization Group Flows in Four Dimensions

We discuss some general aspects of renormalization group flows in four dimensions. Every such flow can be reinterpreted in terms of a spontaneously broken conformal symmetry. We analyze in detail the consequences of trace anomalies for the effective action of the Nambu-Goldstone boson of broken conformal symmetry. While the c-anomaly is algebraically trivial, the a-anomaly is "non-Abelian," and leads to a positive-definite universal contribution to the S-matrix of 2->2 dilaton scattering. Unitarity of the S-matrix results in a monotonically decreasing function that interpolates between the Euler anomalies in the ultraviolet and the infrared, thereby establishing the a-theorem.Comment: 24 pages, 4 figures. v2: references added and minor correction