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IEEE International Conference on Information Reuse and Integration (IRI)

作者： Michael Armella Isai Michel Lombera Stuart H. Rubin Shu-Ching Chen Gordon Lee Distributed Multimedia Information Systems Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Department of Electrical & Computer Engineering San Diego State University San Diego CA USA SPAWAR Systems Center San Diego CA USA

The capability to efficiently retrieve knowledge in response to specific user queries offers the potential to create decision support systems of unprecedented utility, i.e., systems which can accelerate the learning process. This paper presents such an architecture, the Type 2 Knowledge Amplification by structured expert randomization (T2K) system. This system differs from traditional expert systems in the way knowledge rules are matched with queries. The T2K has the ability to acquire knowledge from corresponding domains to answer queries from domains in which the system has less knowledge. This system also solves the word mismatch problem by modifying queries using word substitutions. This is done through creative transformations and optimizations of knowledge rule antecedents and consequents. By pairing rules with identical antecedents or consequents, we are able to induce new rules from existing knowledge without explicit elicitation from the user. The technique presented in this paper attempts to transform both the rules in the knowledge base as well as the query in order to find a matching action for a specified query.

关键词： Knowledge acquisition Engines Expert systems distributed computing Automata Humans Multimedia systems Multimedia computing Information systems Laboratories

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Collateral Representative Subspace Projection Modeling for Supervised Classification

Collateral Representative Subspace Projection Modeling for S...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Thiago Quirino Zongxing Xie Mei-ling Shyu Shu-ching Chen Liwu Chang Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Naval Research Laboratory Center for High Assurance Computer Systems Washington D.C. USA

In this paper, a novel supervised classification approach called collateral representative subspace projection modeling (C-RSPM) is presented. C-RSPM facilitates schemes for collateral class modeling, class-ambiguity solving, and classification, resulting a multi-class supervised classifier with high detection rate and various operational benefits including low training and classification times and low processing power and memory requirements. In addition, C-RSPM is capable of adaptively selecting nonconsecutive principal dimensions from the statistical information of the training data set to achieve an accurate modeling of a representative subspace. Experimental results have shown that the proposed C-RSPM approach outperforms other supervised classification methods such as SIMCA, C4.5 decision tree, decision table (DT), nearest neighbor (NN), KNN, support vector machine (SVM), I-NN best warping window DTW, I-NN DTW with no warping window, and the well-known classifier boosting method AdaBoost with SVM

关键词： Principal component analysis Support vector machines Support vector machine classification Intrusion detection Training data Classification tree analysis Bayesian methods Laboratories distributed computing Power system modeling

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Message from the organizers

ACM International Conference Proceeding Series

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ACM International Conference Proceeding Series 2010年 vii-ix页

作者： Bode, Arndt Bouissou, Marc Distefano, Salvatore Puliafito, Antonio Trivedi, Kishor Walter, Max Technische Universität München Department of Computer Architecture Germany Electricité de France R and D/MRI Department France Università di Messina Multimedia and Distributed Systems Laboratory Italy Duke University Durham Dept. of Electrical and Computer Engineering United States

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UNPCC: A Novel Unsupervised Classification Scheme for Network Intrusion Detection

UNPCC: A Novel Unsupervised Classification Scheme for Networ...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Zongxing Xie Thiago Quirino Mei-ling Shyu Shu-ching Chen Liwu Chang Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL USA Center for High Assurance Computer Systems Naval Research Laboratory Washington D.C. DC USA

The development of effective classification techniques, particularly unsupervised classification, is important for real-world applications since information about the training data before classification is relatively unknown. In this paper, a novel unsupervised classification algorithm is proposed to meet the increasing demand in the domain of network intrusion detection. Our proposed UNPCC (unsupervised principal component classifier) algorithm is a multiclass unsupervised classifier with absolutely no requirements for any a priori class related data information (e.g., the number of classes and the maximum number of instances belonging to each class), and an inherently natural supervised classification scheme, both which present high detection rates and several operational advantages (e.g., lower training time, lower classification time, lower processing power requirement, and lower memory requirement). Experiments have been conducted with the KDD Cup 99 data and network traffic data simulated from our private network testbed, and the promising results demonstrate that our UNPCC algorithm outperforms several well-known supervised and unsupervised classification algorithms

关键词： Intrusion detection Classification algorithms Clustering algorithms computer networks distributed computing Laboratories Training data Traffic control Testing Machine learning algorithms

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Reduced-Order Models of Static Power Grids Based on Spectral Clustering

Reduced-Order Models of Static Power Grids Based on Spectral...

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Annual North-American Power Symposium

作者： Mario D. Baquedano-Aguilar Sean Meyn Arturo Bretas Department of Electrical & Computer Engineering University of Florida Gainesville FL USA Distributed Systems Group Pacific Northwest National Laboratory Richland WA USA G2Elab Grenoble INP CNRS Université Grenoble Alpes Grenoble France

For large-scale interconnected power systems that cover large geographical areas, certain electrical studies are required so that appropriate decisions ensure system reliability and low cost. For such studies, it is often neither practical nor necessary to model in detail the entire power system, which is increasingly complex due to a more diverse range of grid assets to choose from in both short and long-term planning. The goal of this paper is to present a methodology to reduce the order of large-scale power networks based on spectral graph theory given that current methods for static network reduction are not scalable. A brief analysis of some spectral clustering properties to determine which graph Laplacian matrix should be used and why is included. The analysis shows that the utilization of the normalized graph Laplacian is more advantageous for clustering purposes. Techniques are proposed to approximate cost functions for the aggregated generators. This is done via linear regression. The reduced-order model obtained with the proposed methodology has an accuracy above 94% and solves the scalability issue commonly present in other reduction methods. If the utilization of the reduced-order model is either constrained to load levels above mid-peak demand, or cost functions of aggregated units are approximated via a piece-wise quadratic approach, then the error distribution is in the order of 10- 3 .

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Integrated Web enabled control system design methodology

Integrated Web enabled control system design methodology

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IEEE International Workshop on Factory Communication systems (WFCS)

作者： A.P. Kalogeras A. Prayati C. Schwab M. Tangermann L. Ferrarini G. Papadopoulos Industrial Systems Institute Rio-Patras Greece Applied Electronics Laboratory Department of Electrical and Computer Engineering University of Patras Rio-Patras Greece Center Distributed Systems University of Magdeburg Magdeburg Germany Dip. di Elettronica e Informazione Politecnico di Milano Milan Italy

The ubiquity of the Internet infrastructure has revolutionized the industrial enterprise environment enabling the provision of advanced services, such as Web enabled configuration, maintenance and management of the industrial manufacturing processes. Thus the trend towards distributed systems is further enhanced. In order to best exploit the Web infrastructure in the industrial environment an integrated control system design methodology is needed. This paper presents a proposed architecture in the industrial environment comprising function blocks for code distribution, a special model for devices, an integrated environment for the Web enabled functionalities as well as an associated methodology.

关键词： Control systems electrical equipment industry Communication industry computer industry Manufacturing industries Electronics industry Environmental management Industrial control Application software Information technology

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Coherency-Constrained Spectral Clustering for Proactive Load Shedding: A Tri-Level Model

Coherency-Constrained Spectral Clustering for Proactive Load...

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IEEE General Meeting Power& Energy Society

作者： Mario D. Baquedano-Aguilar Arturo Bretas Sean Meyn Department of Electrical & Computer Engineering University of Florida Gainesville FL USA Distributed Systems Group Pacific Northwest National Laboratory Richland WA USA G2Elab Grenoble INP CNRS Université Grenoble Alpes Grenoble France

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

In low-inertia power grids, traditional load-shedding methods can be ineffective, causing instability and unnecessary grid islanding. This work introduces a distributed tri-level optimization model for proactive load shedding to prevent grid islanding considering generator coherency identification. Preventing islanding is crucial because it reduces the need for additional load shedding and transmission line tripping, thereby maintaining frequency stability. This is especially important in systems heavily dependent on non-dispatchable resources like wind and solar. The model employs generator coherency identification through spectral clustering using synchronizing coefficients. The results are then used as constraints in a dynamic graph based on power flow measurements to identify coherent areas for load shedding under highly stressed conditions. This approach offers practical applications and holds promise for real-world use.

关键词： Wind Islanding Power transmission lines Load shedding Power system stability Transmission line measurements Generators Stability analysis Load modeling Stress measurement

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PMU-Spill: Performance Monitor Unit Counters Leak Secrets in Transient Executions

PMU-Spill: Performance Monitor Unit Counters Leak Secrets in...

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IEEE Asian Hardware-Oriented Security and Trust (AsianHOST)

作者： Pengfei Qiu Qiang Gao Dongsheng Wang Yongqiang Lyu Chang Liu Xiaoyong Li Chunlu Wang Gang Qu Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Tsinghua University Beijing China Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing China Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland Maryland USA

ISBN: (纸本)9781665461153

The processor's Performance Monitor Unit (PMU) allows the recording of architectural and microarchitectural events for profiling purposes. In this study, we reveal a security issue caused by the fact that current PMU implementations are capable of recording some events that happened during transient executions. We propose the PMU -Spill attack, a new kind of attack that enables attackers to maliciously leak the secret data in transient executions. We demonstrate on real hardware that PMU -Spill attack can leak the secret data stored in Intel Software Guard Extensions (SGX). In addition, we perform a thorough study to reveal all the vulnerable PMU counters and find that 20 of them can be used to achieve PMU -Spill attack. Our experiments suggest that the throughput of PMU -Spill attack is up to 575.3 bytes per second (Bps) with an average error rate of 1.89% when leaking the SGX-protected secret data.

关键词： Side-channel attacks Throughput Phasor measurement units Hardware Software Recording Security

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FCloudless: A Performance-Aware Collaborative Mechanism for JointCloud Serverless

FCloudless: A Performance-Aware Collaborative Mechanism for ...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Jianfei Liu Huaimin Wang Peichang Shi Yaojie Li Penghui Ma Guodong Yi National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha 410073 China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha 410073 China Xiangjiang Lab Changsha 410073 China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha 410073 China

As a new stage in the development of the cloud computing paradigm, serverless computing has the high-level abstraction characteristic of shielding underlying details. This makes it extremely challenging for users to choose a suitable serverless platform. To address this, targeting the jointcloud computing scenario of heterogeneous serverless platforms across multiple clouds, this paper presents a jointcloud collaborative mechanism called FCloudless with cross-cloud detection of the full lifecycle performance of serverless platforms. Based on the benchmark metrics set that probe performance critical stages of the full lifecycle, this paper proposes a performance optimization algorithm based on detected performance data that takes into account all key stages that affect the performance during the lifecycle of a function and predicts the overall performance by combining the scores of local stages and dynamic weights. We evaluate FCloudless on AWS, AliYun, and Azure. The experimental results show that FCloudless can detect the underlying performance of serverless platforms hidden in the black box and its optimization algorithm can select the optimal scheduling strategy for various applications in a jointcloud environment. FCloudless reduces the runtime by 23.3% and 24.7% for cold and warm invocations respectively under cost constraints.

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Affinity-based similarity measure for Web document clustering

Affinity-based similarity measure for Web document clusterin...

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IEEE International Conference on Information Reuse and Integration (IRI)

作者： M.-L. Shyu S.-C. Chen M. Chen S.H. Rubin Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Distributed Multimedia Information System Laboratory School of Computer Science Florida International University Miami FL USA Center SSC San Diego SPA WAR Systems Center San Diego CA USA

Compared to the regular documents, the major distinguishing characteristics of the Web documents are the dynamic hyper-structure. Thus, in addition to terms or keywords for regular document clustering, Web document clustering can incorporate some dynamic information such as the hyperlinks and the access patterns extracted from the user query logs. In this paper, we extend the concept of document clustering into Web document clustering by introducing the strategy of affinity-based similarity measure, which utilizes the user access patterns in determining the similarities among Web documents via a probabilistic model. Several comparison experiments are conducted using a real data set and the experimental results demonstrate that the proposed similarity measure outperforms the cosine coefficient and the Euclidean distance method under different document clustering algorithms.

关键词： Clustering algorithms World Wide Web Uniform resource locators Particle measurements Multimedia systems distributed computing Military computing systems engineering and theory Information systems Laboratories

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