5097434
Automated discovery of concise predictive rules for intrusion detection
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture, complete with a data warehouse and mobile and stationary agents for distributed problem-solving to facilitate building, monitoring, and analyzing global, spatio-temporal views of intrusions on large distributed systems. An agent for the intrusion detection system, which uses a machine learning approach to automated discovery of concise rules from system call traces, is described.We use a feature vector representation to describe the system calls executed by privileged processes. The feature vectors are labeled as good or bad depending on whether or not they were executed during an observed attack. A rule learning algorithm is then used to induce rules that can be used to monitor the system and detect potential intrusions. We study the performance of the rule learning algorithm on this task with and without feature subset selection using a genetic algorithm. Feature subset selection is shown to significantly reduce the number of features used while improving the accuracy of predictions.
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.
271858
Providing scalable on-demand video services for heterogeneous receivers
To provide scalable video-on-demand services, precious system bandwidth must be shared among video requests. Although many efficient bandwidth-sharing techniques have been proposed, they are all designed for homogeneous receivers, i.e., the clients are assumed to have the same receiving bandwidth. For networks with client heterogeneity, these techniques either cannot work or have to compromise their performance. In this paper, we address this problem and propose an efficient solution allowing each client to use its whole receiving bandwidth to download data. To serve a client, the server first selects a set of serving channels for the client according to its actual receiving bandwidth. The video data needed for this client are then scheduled and dynamically adjusted for delivery over these channels. We evaluate the performance of the new technique using simulation and compare it with an existing scheme. Our study shows that by effectively leveraging client heterogeneity, the new technique achieves significantly smaller service latency
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.
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.
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.
27801438
Scheduling Algorithms for Videotex Systems Under Broadcast Delivery
36690948
Analysis of Flow Control in Switched Data Networks
926253
Power minimization in QoS sensitive systems
The majority of modern multimedia and mobile systems have two common denominators: quality-of-service (QoS) requirements, such as latency and synchronization, and strict energy constraints. However, until now no synthesis techniques have been proposed for the design and efficient use of such systems. We have two main objectives: conceptual and synthesis. The conceptual objective is to develop a generic practical technique for the automatic development of online adaptive algorithms from efficient off-line algorithms using statistical techniques. The synthesis objective is to introduce the first design technique for QoS low-power synthesis. We introduce a system of provably-optimal techniques that minimize energy consumption of stream-oriented applications under two main QoS metrics: latency and synchronization. Specifically, we study how multiple voltages can be used to simultaneously satisfy hardware constraints and minimize power consumption while preserving the requested level of QoS. The purpose of the off-line algorithm is threefold. First, it is used as input to statistical software which is used to identify important and relevant parameters of the processes. Second, the algorithm provides buffer occupancy rate indicators. Lastly, it provides a way to combine buffer occupancy and QoS metrics to form a fast and efficient online algorithm. The effectiveness of the algorithms is demonstrated on a number of standard multimedia benchmarks.
47328768
Effective iterative techniques for fingerprinting design IP
Fingerprinting is an approach that assigns a unique and invisible ID to each sold instance of the intellectual property (IP). One of the key advantages fingerprinting-based intellectual property protection (IPP) has over watermarking-based IPP is the enabling of tracing stolen hardware or software. Fingerprinting schemes have been widely and effectively used to achieve this goal; however, their application domain has been restricted only to static artifacts, such as image and audio, where distinct copies can be obtained easily. In this paper, we propose the first generic fingerprinting technique that can be applied to an arbitrary synthesis (optimization or decision) or compilation problem and, therefore to hardware and software IPs. The key problem with design IP fingerprinting is that there is a need to generate a large number of structurally unique but functionally and timing identical designs. To reduce the cost of generating such distinct copies, we apply iterative optimization in an incremental fashion to solve a fingerprinted instance. Therefore, we leverage on the optimization effort already spent in obtaining previous solutions, yet we generate a uniquely fingerprinted new solution. This generic approach is the basis for developing specific fingerprinting techniques for four important problems in VLSI CAD: partitioning, graph coloring, satisfiability, and standard-cell placement. We demonstrate the effectiveness of the new fingerprinting-based IPP techniques on a number of standard benchmarks.
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.