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6th International Conference on process Mining (ICPM)

作者： Rauch, Simon Zellner, Ludwig Seidl, Thomas Freyt, Christian M. M. Ludwig Maximilians Univ Munchen Database Syst & Data Min Munich Germany Munich Ctr Machine Learning Munich Germany Fraunhofer IIS Ctr Appl Res Supply Chain Serv Nurnberg Germany

ISBN: (纸本)9798350365030

Business processes from many domains like manufacturing, healthcare, or business administration suffer from different amounts of uncertainty concerning the execution of individual activities and their order of occurrence. As long as a process is not entirely serial, i.e., there are no forks or decisions to be made along the process execution, we are - in the absence of exhaustive domain knowledge - confronted with the question whether and in what order activities should be executed or left out for a given case and a desired outcome. As the occurrence or non-occurrence of events has substantial implications regarding process key performance indicators like throughput times or scrap rate, there is ample need for assessing and modeling that process-inherent uncertainty. We propose a novel way of handling the uncertainty by leveraging the probabilistic mechanisms of Bayesian Networks to model processes from the structural and temporal information given in event log data and offer a comprehensive evaluation of uncertainty by modelling cases in their entirety. In a thorough analysis of well-established benchmark datasets, we show that our process-aware Bayesian Network is capable of answering process queries concerned with any unknown process sequence regarding activities and/or attributes enhancing the explainability of processes. Our method can infer execution probabilities of activities at different stages and can query probabilities of certain process outcomes. The key benefit of the process-aware query System over existing approaches is the ability to deliver probabilistic, case-diagnostic information about the execution of activities via Bayesian inference.

关键词： process query systems Bayesian Networks Predictive process Monitoring

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process query systems

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COMPUTER 2007年第1期40卷 62-+页

作者： Cybenko, George Berk, Vincent H. Dartmouth Coll Hanover NH 03755 USA

In the context of computer security, situational awareness typically means knowing which monitored systems are under attack and the nature of those attacks. For a physical sensor network within a building or extending across a geographic region, it might mean being cognizant of certain objects and activities. Extracting meaningful and actionable information from these events, however, remains a challenge. A new algorithmic and software paradigm, process query systems, addresses these event-processing challenges.

关键词： query processing Computerised Instrumentation Instrumentation Data processing process query systems Information Extraction Event processing Challenges Working Environment Noise Event Detection Computer Networks Sensor systems System Testing Application Software Computer Security Reconnaissance Instruments Computerized Monitoring process Detection PQS Modeling Framework Data Mining Security Environmental Monitoring

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Dynamic social network analysis using conversational dynamics in social networking and microblogging environments

Dynamic social network analysis using conversational dynamic...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Security and Homeland Defense IX

作者： Stocco, Gabriel Savell, Robert Cybenko, George Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)9780819481306

In many security environments, the textual content of communications may be unavailable. In these instances, it is often desirable to infer the status of the network and its component entities from patterns of communication flow. Conversational dynamics among entities in the network may provide insight into important aspects of the underlying social network such as the formational dynamics of group structures, the active state of these groups, individuals' roles within groups, and the likelihood of individual participation in conversations. To gain insight into the use of conversational dynamics to facilitate Dynamic Social Network Analysis, we explore the use of interevent timings to associate entities in the Twitter social networking and micro-blogging environment. Specifically, we use message timings to establish inter-nodal relationships among participants. In addition, we demonstrate a new visualization technique for tracking levels of coordination or synchronization within the community via measures of socio-temporal coherence of the participants.

关键词： Dynamic Social Network Analysis SNA Twitter process query systems PQS

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An experimental comparison of hypothesis management approaches for process query systems

An experimental comparison of hypothesis management approach...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Security and Homeland Defense IV

作者： Sheng, Y Madory, DC Cybenko, GV Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)0819457639

A process query System (PQS) is a generic software system that can be used in tracking applications across a variety of domains. As in most other tracking systems, multiple hypotheses about which reports are assigned to which tracks must be maintained. Since the number of hypotheses that are possible can be exponential in the number of reports, some technique for managing a pool of the best candidate hypotheses must be used. In this paper, we compare a genetic algorithm approach and a hypothesis clustering approach with the basic top-H pruning policy. Metrics for comparison include performance accuracy and computational requirements. Simulations show positive results for both of these approaches and suggest that the clustering approach has the best overall performance. Other experiments indicate that the genetic algorithm technique can converge over time to the ground truth.

关键词： hypothesis management process query systems multiple hypothesis tracking genetic algorithm clustering vector quantization

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Target tracking and localization using infrared video imagery

Target tracking and localization using infrared video imager...

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Conference on Unattended Ground, Sea, and Air Sensor Technologies and Applications VIII

作者： Barsamian, Alex Berk, Vincent H. Cybenko, George V. Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)081946287X

One of the significant problems in visual tracking of objects is the requirement for a human analyst to post-process and interpret the data. For instance, consider the task of tracking a target, in this case a moving person, using video imagery. When this person hides behind an obstruction, and is therefore no longer visible by the camera, conventional tracking systems quickly lose track of the target and are no longer able to indicate where the target is or where it was headed. A human interpreter is then needed to conclude that the person is hiding, and probably (with certain probability) is still there. A process query System (PQS) is able to track and predict the path of arbitrary objects, based only on a description of their dynamic behavior, thus eliminating the need for precise identification of each object in every frame. The PQS is therefore able to draw human-like conclusions, allowing the system to track the person even when he/she is out of view. Additionally, using dynamic descriptions of tracked objects allows for low-quality video signals, or even infrared video, to be used for tracking. In this paper we introduce a novel way of implementing a video-based tracking system using a process query System to predict the position of objects in the environment, even after they have disappeared from view. Although the image processing pipeline is trivial, tracking accuracy is remarkably high, suggesting that overall performance can be improved even further with the use of more sophisticated video processing and image recognition technology.

关键词： thermal imaging visual tracking process query systems

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Identifying and tracking dynamic processes in social networks

Identifying and tracking dynamic processes in social network...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Secuity and Homeland Defense V

作者： Chung, Wayne Savell, Robert Schuett, Jan-Peter Cybenko, George Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Univ Federal Armed Forces Inst Elect Hamburg Germany

ISBN: (纸本)0819462578

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the process query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream- the Enron email corpus.

关键词： Dynamic Social Network Analysis SNA process query systems PQS Enron email

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Detection of complex cyber attacks

Detection of complex cyber attacks

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Secuity and Homeland Defense V

作者： Gregorio-de Souza, Ian Berk, Vincent H. Giani, Annarita Bakos, George Bates, Marion Cybenko, George Madory, Doug Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)0819462578

One significant drawback to currently available security products is their inabilty to correlate diverse sensor input. For instance, by only using network intrusion detection data, a root kit installed through a weak username-password combination may go unnoticed. Similarly, an administrator may never make the link between deteriorating response times from the database server and an attacker exfiltrating trusted data, if these facts aren't presented together. Current Security Information Management systems (SIMS) can collect and represent diverse data but lack sufficient correlation algorithms. By using a process query System, we were able to quickly bring together data flowing from many sources, including NIDS, HIDS, server logs, CPU load and memory usage, etc. We constructed PQS models that describe dynamic behavior of complicated attacks and failures, allowing us to detect and differentiate simultaneous sophisticated attacks on a target network. In this paper, we discuss the benefits of implementing such a multistage cyber attack detection system using PQS. We focus on how data from multiple sources can be combined and used to detect and track comprehensive network security events that go unnoticed using conventional tools.

关键词： cyber attacks process query systems

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