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Cyberspace Security Using Adversarial Learning and Conformal Prediction

Intelligent Information Management 2015年第4期7卷 195-222页

作者： harry wechsler Department of Computer Science George Mason University Fairfax VA USA

This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactical offensive threats. Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted?self-managing defensive shield to detect, disrupt, and deny intrusive attacks, hostile and malicious behavior, and subterfuge. Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns and messages as friend or foe and to respond to them accordingly. The solutions proffered throughout are built around active learning, meta-reasoning, randomness, distributed semantics and stratification, and most important and above all around adaptive Oracles. The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric methods characteristic of principled demarcation using cohorts and sensitivity analysis to hedge on the prediction outcomes including negative selection, on one side, and providing credibility and confidence indices that assist meta-reasoning and information fusion.

关键词： Active Learning Adversarial Learning Anomaly Detection Change Detection Conformal Prediction Cyber Security Data Mining Denial and Deception Human Factors Insider Threats Intrusion Detection Meta-Reasoning Moving Target Defense Performance Evaluation Randomness Semi-Supervised Learning Sequence Analysis Statistical Learning Transduction

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Intelligent Biometric Information Management

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Intelligent Information Management 2010年第9期2卷 499-511页

作者： harry wechsler 不详

We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation, and functionality, and robustness refers to the ability to handle incomplete and/or corrupt adversarial information, on one side, and image and or device variability, on the other side. The proposed methodology is model-free and non-parametric. It draws support from discriminative methods using likelihood ratios to link at the conceptual level biometrics and forensics. It further links, at the modeling and implementation level, the Bayesian framework, statistical learning theory (SLT) using transduction and semi-supervised lea- rning, and Information Theory (IY) using mutual information. The key concepts supporting the proposed methodology are a) local estimation to facilitate learning and prediction using both labeled and unlabeled data;b) similarity metrics using regularity of patterns, randomness deficiency, and Kolmogorov complexity (similar to MDL) using strangeness/typicality and ranking p-values;and c) the Cover – Hart theorem on the asymptotical performance of k-nearest neighbors approaching the optimal Bayes error. Several topics on biometric inference and prediction related to 1) multi-level and multi-layer data fusion including quality and multi-modal biometrics;2) score normalization and revision theory;3) face selection and tracking;and 4) identity management, are described here using an integrated approach that includes transduction and boosting for ranking and sequential fusion/aggregation, respectively, on one side, and active learning and change/ outlier/intrusion detection realized using information gain and martingale, respectively, on the other side. The methodology proposed can be mapped to additional types of information beyond biometrics.

关键词： Authentication Biometrics Boosting Change Detection Complexity Cross-Matching Data Fusion Ensemble Methods Forensics Identity Management Imposters Inference Intelligent Information Management Margin gain MDL Multi-Sensory Integration Outlier Detection P-Values Quality Randomness Ranking Score Normalization Semi-Supervised Learning Spectral Clustering Strangeness Surveillance Tracking Typicality Transduction

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Face Recognition across Time Lapse Using Convolutional Neural Networks

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Journal of Information Security 2016年第3期7卷 141-151页

作者： Hachim El Khiyari harry wechsler Department of Computer Science George Mason University Fairfax VA USA

Time lapse, characteristic of aging, is a complex process that affects the reliability and security of biometric face recognition systems. This paper reports the novel use and effectiveness of deep learning, in general, and convolutional neural networks (CNN), in particular, for automatic rather than hand-crafted feature extraction for robust face recognition across time lapse. A CNN architecture using the VGG-Face deep (neural network) learning is found to produce highly discriminative and interoperable features that are robust to aging variations even across a mix of biometric datasets. The features extracted show high inter-class and low intra-class variability leading to low generalization errors on aging datasets using ensembles of subspace discriminant classifiers. The classification results for the all-encompassing authentication methods proposed on the challenging FG-NET and MORPH datasets are competitive with state-of-the-art methods including commercial face recognition engines and are richer in functionality and interoperability than existing methods as it handles mixed biometric datasets, e.g., FG-NET and MORPH.

关键词： Aging Authentication Biometrics Convolutional Neural Networks (CNN) Deep Learning Ensemble Methods Face Recognition Interoperability Security

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Intelligent Evidence-Based Management for Data Collection and Decision-Making Using Algorithmic Randomness and Active Learning

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Intelligent Information Management 2011年第4期3卷 142-159页

作者： harry wechsler Shen-Shyang Ho 不详

We describe here a comprehensive framework for intelligent information management (IIM) of data collection and decision-making actions for reliable and robust event processing and recognition. This is driven by algorithmic information theory (AIT), in general, and algorithmic randomness and Kolmogorov complexity (KC), in particular. The processing and recognition tasks addressed include data discrimination and multilayer open set data categorization, change detection, data aggregation, clustering and data segmentation, data selection and link analysis, data cleaning and data revision, and prediction and identification of critical states. The unifying theme throughout the paper is that of “compression entails comprehension”, which is realized using the interrelated concepts of randomness vs. regularity and Kolmogorov complexity. The constructive and all encompassing active learning (AL) methodology, which mediates and supports the above theme, is context-driven and takes advantage of statistical learning, in general, and semi-supervised learning and transduction, in particular. Active learning employs explore and exploit actions characteristic of closed-loop control for evidence accumulation in order to revise its prediction models and to reduce uncertainty. The set-based similarity scores, driven by algorithmic randomness and Kolmogorov complexity, employ strangeness / typicality and p-values. We propose the application of the IIM framework to critical states prediction for complex physical systems;in particular, the prediction of cyclone genesis and intensification.

关键词： Active Learning Algorithmic Information Theory Algorithmic Randomness Evidence-Based Management Kolmogorov Complexity P-Values Transduction Critical States Prediction

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Age Invariant Face Recognition Using Convolutional Neural Networks and Set Distances

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Journal of Information Security 2017年第3期8卷 174-185页

作者： Hachim El Khiyari harry wechsler Department of Computer Science George Mason University Fairfax VA USA

Biometric security systems based on facial characteristics face a challenging task due to variability in the intrapersonal facial appearance of subjects traced to factors such as pose, illumination, expression and aging. This paper innovates as it proposes a deep learning and set-based approach to face recognition subject to aging. The images for each subject taken at various times are treated as a single set, which is then compared to sets of images belonging to other subjects. Facial features are extracted using a convolutional neural network characteristic of deep learning. Our experimental results show that set-based recognition performs better than the singleton-based approach for both face identification and face verification. We also find that by using set-based recognition, it is easier to recognize older subjects from younger ones rather than younger subjects from older ones.

关键词： Aging Biometrics Convolutional Neural Networks (CNN) Deep Learning Image Set-Based Face Recognition (ISFR) Transfer Learning

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Real-Time Timing Channel Detection in a Software-Defined Networking Virtual Environment

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Intelligent Information Management 2015年第6期7卷 283-302页

作者： Anyi Liu Jim X. Chen harry wechsler Department of Computer Science Indiana University—Purdue University Fort Wayne Fort Wayne USA Department of Computer Science George Mason University Fairfax USA

Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection approaches use either signature-based approaches to detect known TCs or anomaly-based approach by modeling the legitimate network traffic in order to detect unknown TCs. Un-fortunately, in a software-defined networking (SDN) environment, most existing TC detection approaches would fail due to factors such as volatile network traffic, imprecise timekeeping mechanisms, and dynamic network topology. Furthermore, stealthy TCs can be designed to mimic the legitimate traffic pattern and thus evade anomalous TC detection. In this paper, we overcome the above challenges by presenting a novel framework that harnesses the advantages of elastic re-sources in the cloud. In particular, our framework dynamically configures SDN to enable/disable differential analysis against outbound network flows of different virtual machines (VMs). Our framework is tightly coupled with a new metric that first decomposes the timing data of network flows into a number of using the discrete wavelet-based multi-resolution transform (DWMT). It then applies the Kullback-Leibler divergence (KLD) to measure the variance among flow pairs. The appealing feature of our approach is that, compared with the existing anomaly detection approaches, it can detect most existing and some new stealthy TCs without legitimate traffic for modeling, even with the presence of noise and imprecise timekeeping mechanism in an SDN virtual environment. We implement our framework as a prototype system, OBSERVER, which can be dynamically deployed in an SDN environment. Empirical evaluation shows that our approach can efficiently detect TCs with a higher detection rate, lower latency, and negligible performance overhead compared to existing approaches.

关键词： Covert Channel Timing Channel Intrusion Detection Virtualization Software-Defined Network

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Gut microbiota in cancer initiation,development and therapy

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Science China Life Sciences 2025年

作者： Ruyi Zhang Xiang Zhang harry Cheuk Hay Lau Jun Yu Institute of Digestive Disease and Department of Medicine and Therapeutics State Key Laboratory of Digestive DiseaseLi Ka Shing Institute of Health SciencesCUHK Shenzhen Research InstituteThe Chinese University of Hong Kong

Cancer has long been associated with genetic and environmental factors,but recent studies reveal the important role of gut microbiota in its initiation and *** 13%of cancers are linked to infectious agents,highlighting the need to identify the specific microorganisms *** microbiota can either promote or inhibit cancer growth by influencing oncogenic signaling pathways and altering immune *** can lead to cancer,while certain probiotics and their metabolites may help reestablish microecological balance and improve anti-tumor immune *** into targeted approaches that enhance therapy with probiotics is ***,the effects of probiotics in humans are complex and not yet fully ***,methods to counteract harmful bacteria are still in *** clinical trials also indicate that modifying gut microbiota may help manage side effects of cancer *** research is crucial to understand better how gut microbiota can be used to improve cancer prevention and treatment outcomes.

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Significance of using isolated footing technique for resi- dential construction on expansive soils

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Frontiers of Structural and Civil Engineering 2017年第1期11卷 123-129页

作者： harry FAR Deacon FLINT Centre for Built Infrastructure Research School of Civil and Environmental Engineering University of Technology Sydney (UTS)Australia

Expansive soils cause problems with the founding of lightly loaded structures in many parts of the world. Foundation design for expansive soils is one of the most discussed and problematic issues in Australia as expansive soils were responsible for billions of dollars＇ worth of damage to man-made structures such as buildings and roads. Several studies and reports indicate that one of the most common and least recognized problems causing severe structural damage to houses lies in expansive soils. In this study, a critical review has been carried out on the current Australian standards for building on expansive soils and they are compared with some techniques that are not included in the current Australian standards for residential slabs and footings. Based on the results of this review, the most effective and economical method has been proposed for construction of footings on all site classifications without restriction to 75mm of characteristic movement. In addition, it has become apparent that as design procedures for footings resting on sites with extreme characteristic movements are not included in the current Australian standards, there is a strong need for well-developed and simplified standard design procedures for characteristic soil movement of greater than 75mm to be included into the Australian Standards.

关键词： expansive soils residential slabs isolated footings Australian Standards

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A review on molten sulfate salts induced hot corrosion

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Journal of Materials Science & Technology 2021年第31期90卷 243-254页

作者： Shanshan Hu harry Finkle Xingbo Liu Mechanical&Aerospace Engineering Department Benjamin M.Statler College of Engineering&Mineral ResourcesWest Virginia UniversityMorgantownWV 26506-6106USA C.Eugene Bennett Department of Chemistry West Virginia UniversityMorgantownWV 26506USA

Hot corrosion has been extensively observed in various high temperature applications,which might cause large economic *** deepen the insight and understanding of hot corrosion,herein,we provide a detailed discussion on hot corrosion induced by molten sulfate salt,in which Na_(2)SO_(4)is the main chemical *** hot corrosion is triggered and sustained by the negative solubility gradient of protective oxide from the oxide/salt interface to salt/gas *** this work,we reviewed several key factors,including temperature,gas composition,molten salt composition,alloy element and external stress,influencing the hot corrosion of alloy beneath the molten *** application of anti-corrosion coating seems to be the most effective and commercial mothed to mitigate hot ***,the progress of the development of effective coatings,e.g.,Ni-Cr coatings,aluminide coatings,silicide coatings and MCrAlY(X)coatings,has also been summarized.

关键词： Hot corrosion Molten sulfate salts Protective oxide layer Dissolution Anti-corrosion coatings

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Synchronization of home departure and arrival times in dual earner households with children:Panel regression model of time gaps

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Journal of Traffic and Transportation Engineering(English Edition) 2019年第5期6卷 504-513页

作者： Bilin Han harry Timmermans Urban Planning Group Eindhoven University of Technology

Organizing schedules and allocating time to different activities is always a challenge in dual-earner households,especially when they have *** may need to link their schedule to those of their children to allow them escorting their children to school or to take care or be with their children at *** paper reports the results of an analysis of the degree of synchronization of home departure and arrival times in dual earner households with children,where the degree of synchronization is defined as the gap between departure and arrival times of a parent and *** activity-travel diary data of different household members,a random parameters regression model is estimated to examine differences in time gaps in home departure and arrival times between parents and children as a function of gender,day of the week,age of the youngest child,and other socio-demographic *** results of the analysis provide insight into factors influencing the degree of synchronization and coordination of double activity-travel scheduling decisions in households with *** indicate that gender,number of children in the household,age of the youngest child,travel within or outside peak hours,day of the week,transport mode used for the work commute and household income level significantly affect time gaps,especially arrival time gaps.

关键词： Home departure and arrival times Synchronization Time gap Dual-earner households Random parameters panel regression model

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