17046491
Lightweight agents for intrusion detection
We have designed and implemented an intrusion detection system (IDS) prototype based on mobile agents. Our agents travel between monitored systems in a network of distributed systems, obtain information from data cleaning agents, classify and correlate information, and report the information to a user interface and database via mediators.Agent systems with lightweight agent support allow runtime addition of new capabilities to agents. We describe the design of our Multi-agent IDS and show how lightweight agent capabilities allowed us to add communication and collaboration capabilities to the mobile agents in our IDS.
14348286
A Visual Model Approach for Parsing Colonoscopy Videos
Colonoscopy is an important screening procedure for colorectal cancer. During this procedure, the endoscopist visually inspects the colon. Currently, there is no content-based analysis and retrieval system that automatically analyzes videos captured from colonoscopic procedures and provides a user-friendly and efficient access to important content. Such a system will be valuable as an educational resource for endoscopic research, a platform to assess procedural skills for endoscopists, and a platform for mining for unknown abnormality patterns that may lead to colorectal cancer. The first necessary step for the analysis is parsing for semantic units. In this paper, we propose a new visual model approach that employs visual features extracted directly from compressed videos together with audio analysis to discover important semantic units called scenes. Our experimental results show average precision and recall of 93% and 85%, respectively.
14591533
Leveraging broadband access for true on-demand delivery of Internet videos
We consider in this paper how the increasingly popular broadband access can be leveraged for scalable and cost-effective video service. Although much work has been done for such service, the existing techniques either are not designed for on-demand video delivery, or do not take into account the vastly improved client receiving capability. In this paper, we address this problem and develop three novel video delivery techniques with two ultimate goals: minimizing service latency and maximize data sharing. With the new techniques, a client can be served as soon as server resource becomes available and meanwhile, all its receiving bandwidth can be used for data receiving. In particular, in the proposed dynamic scheduling algorithm, the efficiency of data sharing is further improved by also exploring server bandwidth for early delivery of video segments. This innovation is contradicted to the intuition that each video segment should be delivered as late as possible in order to maximize data sharing. We evaluate the performance of our new techniques using simulation and our study convincingly shows that with the new schemes, zero service latency can indeed be achieved with very minimal system resource.
14407932
Automatic measurement of quality metrics for colonoscopy videos
Colonoscopy is the accepted screening method for detection of colorectal cancer or its precursor lesions, colorectal polyps. Indeed, colonoscopy has contributed to a decline in the number of colorectal cancer related deaths. However, not all cancers or large polyps are detected at the time of colonoscopy, and methods to investigate why this occurs are needed. We present a new computer-based method that allows automated measurement of a number of metrics that likely reflect the quality of the colonoscopic procedure. The method is based on analysis of a digitized video file created during colonoscopy, and produces information regarding insertion time, withdrawal time, images at the time of maximal intubation, the time and ratio of clear versus blurred or non-informative images, and a first estimate of effort performed by the endoscopist. As these metrics can be obtained automatically, our method allows future quality control in the day-to-day medical practice setting on a large scale. In addition, our method can be adapted to other healthcare procedures. Last but not least, our method may be useful to assess progress during colonoscopy training, or as part of endoscopic skills assessment evaluations.
2308501
A framework for parsing colonoscopy videos for semantic units
Colonoscopy is an important screening procedure for colorectal cancer. During this procedure, the endoscopist visually inspects the colon. Currently, there is no content-based analysis and retrieval system that automatically analyzes videos captured from colonoscopic procedures and provides a user-friendly and efficient access to important content. Such a system will be valuable for endoscopic research and education. The first necessary step for the analysis is parsing for semantic units. Since the characteristics of colonoscopy videos differ from those of videos studied in the literature, we introduce a new video parsing framework that includes: (i) a new scene definition and a new video parsing paradigm; (ii) a novel scene segmentation algorithm using audio analysis and finite state automata to recognize scenes and associated boundaries. Our experimental results show average precision and recall of 95% and 81%, respectively, for parsing scenes. The framework is extensible to videos captured from other endoscopic procedures such as upper gastrointestinal endoscopy, enteroscopy, cystoscopy, and laparoscopy.
8229875
A Reputation-based Trust Management in Peer-to-Peer Network Systems
Peer-to-peer networks have gained a lot of attention over the last couple of years, mainly due to the popularity of the free multimedia file-sharing program Napster and a legal battle around it. Being open by nature P2P systems represent an ideal environment for various types of malicious intrusions. The problem of securing hosts on P2P network while keeping the openness of the system has been studied extensively over last couple of years but still remains open. Existing solutions based on reputation management either employ centralized algorithms or rely on peers' cooperation on the network. We describe a fully decentralized approach that allows computing peers' reputation based on the traffic between a node and its peers, independently of these peers willingness to cooperate in calculation of their reputation. 1 INTRODUCTION Peer-to-peer (P2P) network systems are increasingly gaining popularity on the Internet. These networks allow individual hosts (peers) to share and distribute various types of information over the Internet. By their nature, P2P networks are structured in a way that allows an open and unsupervised communication between peers. Therefore, these systems are vulnerable to various types of attacks, among which are denial-of-service attacks (DoS) and distribution of viruses. To protect themselves from malicious intentions, hosts should be able to identify reliable peers for communication. Identifying these peers is a challenging task in highly dynamic network environments like P2P networks. In this paper we suggest a solution to this problem based on the notion of trust. We propose a policy for managing traffic in peer-to-peer network based on peers' reputation. We also describe a model for computing this reputation using the trust score based on the peers' interaction with each other. Unlike most existing reputation-based models, our approach does not employ a centralized storage and only produces reputation scores on demand. The proposed solution is fully distributed and does not require any cooperation from the rest of the network. Our model aims to help users to select the most reliable peers whose past behavior shows willingness to participate in a proper functioning of the P2P system and at the same time to anticipate possible attacks from malicious peers by limiting their access to the victim peer's resources. In this paper we focus on a particular type of P2P systems, called Gnutella, which proved to be one of the most popular P2P systems. Furthermore, unlike other popular P2P applications such as KaZaa, the source …
10377978
Scheduling of soft real-time systems for context-aware applications
Context-aware applications pose new challenges, including a need for new computational models, uncertainty management, and efficient optimization under uncertainty. Uncertainty can arise at two levels: multiple and single tasks. When a mobile user changes environments, the context changes resulting in the possibility of the user requesting tasks which are specific for the new environment. However as the user moves these requested tasks may no longer be context relevant. Additionally, the runtime of each task is often highly dependent on the input data. We introduce an hierarchical multi-resolution statistical task model that captures relevant aspects at the task and intertask levels, and captures not only uncertainty, but also introduces the notion of utility for the user. We have developed a system of nonparametric statistical techniques for modeling the runtime of a specific task. This model is a framework where we define problems of design and optimization of statistical soft real-time systems (SSRTS). The main algorithmic novelty is a cumulative potential-based task scheduling heuristic for maximizing utility. The heuristic conducts global optimization and induces low runtime overhead. We demonstrate the effectiveness of the scheduling heuristic using a Trimaran-based evaluation platform.
2971347
Computational forensic techniques for intellectual property protection
Computational forensic engineering (CFE) aims to identify the entity that created a particular intellectual property (IP). Specifically, our goal is to identify the synthesis tool or compiler which was used to produce a specific design or program. Rather than relying on watermarking content or designs, the generic CFE methodology analyzes the statistics of certain features of a given IP and quantizes the likelihood that a well known source has created it. In this paper, we describe the generic methodology of CFE and present a set of techniques that, given a set of compilation tools, identify the one used to generate a particular hardware/software design. The generic CFE approach has four phases: 1) feature and statistics data collection; 2) feature extraction; 3) entity clustering; and 4) validation. In addition to IP protection, the developed CFE paradigm can have other potential applications: optimization algorithm selection and tuning, benchmark selection, and source-verification for mobile code.
19086803
Transaction management in design databases
Abstract Conventional data base systems are not suitable for handling advanced applications encountered in engineering, such as CAD/CAM, CASE, CAE, and VLSI design. The data bases in such environments, also called design data bases, are characterized by the presence of many complex data objects denoted by a large number of small tables, as opposed to a few large tables encountered in conventional data bases. The transaction model used in tracking data bases for banking, inventory control, and other such applications use view serializability as the correctness criterion. While view serializability is appropriate for tracking data bases, it is unnecessarily restrictive for engineering data bases. We propose a transaction model that is suitable for accessing shared design data based on coserializability. The transaction model supports long-duration transactions with intermediate commit points. In addition to the conventional nested transaction hierarchy, the model allows for cooperation between nested design transactions needed in a design environment.
8690187
Distributed Simulation Using a Network of Processors
Abstract Simulation, particulary of networks of queues, is an application with a high degree of inherent parallelism and is of great practical interest. We hope to exploit this parallelism by performing simulations using a network of cheap, but slow, micro-processors. We define a taxonomy by which we classify a number of parameters of a distributed simulation method, and seek solutions to problems of synchronization, deadlock prevention and inter-process communication arising with various methods in each class of the taxonomy. We concentrate in particular on the class (loose, event-driven) which seems to possess the greatest potential parallelism, and on the class (scaled, tight, time-driven) which allows mock-up studies of real systems. We give algorithms for deadlock prevention and detection, and briefly discuss the design of a distributed operating system to support the simulation application. This research forms part of a joint program with the Dept. of Computer Sciences, University of Texas at Austin, directed by Prof. K.M. Chandy.
7994830
Watermarking graph partitioning solutions
Trends in the semiconductor industry towards extensive design and code reuse motivate a need for adequate intellectual property protection (IPP) schemes. We offer a new general IPP scheme called constraint-based watermarking and analyze it in the context of the graph partitioning problem. Graph partitioning is a critical optimization problem that has many applications, particularly in the semiconductor design process. Our IPP technique for graph partitioning watermarks solutions to graph partitioning problems so that they carry an author's signature. Our technique is transparent to the actual CAD tool which does the partitioning. Our technique produces solutions that have very low quality degradation levels, yet carry signatures that are convincingly unambiguous, extremely unlikely to be present by coincidence, and difficult to detect or remove without completely resolving the partitioning problem.