6228197
Copy detection for intellectual property protection of VLSI designs
We give the first study of copy detection techniques for VLSI CAD applications; these techniques are complementary to previous watermarking-based IP protection methods in finding and proving improper use of design IP. After reviewing related literature (notably in the text processing domain), we propose a generic methodology for copy detection based on determining basic elements within structural representations of solutions (IPs), calculating (context-independent) signatures for such elements, and performing fast comparisons to identify potential violators of IP rights. We give example implementations of this methodology in the domains of scheduling, graph coloring and gate-level layout; experimental results show the effectiveness of our copy detection schemes as well as the low overhead of implementation. We remark on open research areas, notably the potentially deep and complementary interaction between watermarking and copy detection.
195861616
Optimization-intensive watermarking techniques for decision problems
Recently, a number of watermarking-based intellectual property protection techniques have been proposed. Although they have been applied to different stages in the design process and have a great variety of technical and theoretical features, all of them share two common properties: they all have been applied solely to optimization problems and do not involve any optimization during the watermarking process. In this paper we propose the first set of optimization-intensive watermarking techniques for decision problems. In particular we demonstrate how one can select a subset of superimposed watermarking constraints so that the uniqueness of the signature and the likelihood of satisfying an instance of the satisfiability problem are simultaneously maximized. We have developed three watermarking SAT techniques: adding clauses, deleting literals, push-out and pull-back. Each technique targets different types of signature induced constraint superimposition on an instance of the SAT problem. In addition to comprehensive experimental validation, we theoretically analyze the potentials and limitations of the proposed watermarking techniques. Furthermore, we analyze the three proposed optimization-intensive watermarking SAT techniques in terms of their suitability for copy detection.
1973000
Gateway placement for latency and energy efficient data aggregation [wireless sensor networks]
We propose the use of multiple gateways to significantly reduce latency and energy consumption in multi-hop wireless sensor networks during data aggregation. We have derived efficient integer linear programming formulations as well as a novel negative selection statistically-tuned heuristics. The heuristics are based on newly developed relaxation based lower bounds that are also used to quantify the effectiveness of the proposed heuristics. Our simulation study indicates that the use of gateways can often reduce latency and energy consumption by several times.
2985827
Flexible ASIC: shared masking for multiple media processors
ASIC provides more than an order of magnitude advantage in terms of density, speed, and power requirement per gate. However, economic (cost of masks) and technological (deep micron manufacturability) trends favor FPGA as an implementation platform. In order to combine the advantages of both platforms and alleviate their disadvantages, recently a number of approaches, such as structured ASIC/regular fabrics, have been proposed. Our goal is to introduce an approach that has the same objective, but is orthogonal to those already proposed. The idea is to implement several ASIC designs in such a way that they share the datapath, memory structure, and several bottom layers of interconnect, while each design has only a few unique metal layers. We identified and addressed two main problems in our quest to develop a CAD flow for realization of such designs. They are: (i) the creation of the datapath, and (ii) the identification of common and unique interconnect for each design. Both problems are solved optimally using ILP formulations. We assembled a design flow platform using two new programs and the Trimaran and Shade tools. We quantitatively analyzed the advantages and disadvantages of the approach using the Mediabench benchmark suite.
1221107
A probabilistic constructive approach to optimization problems
We propose a new optimization paradigm for solving intractable combinatorial problems. The technique, named Probabilistic Constructive (PC), combines the advantages of both constructive and probabilistic algorithms. The constructive aspect provides relatively short runtime and makes the technique amenable for the inclusion of insights through heuristic rules. The probabilistic nature facilitates a flexible trade-off between runtime and the quality of solution. In addition to presenting the generic technique, we apply it to the Maximal Independent Set problem. Extensive experimentation indicates that the new approach provides very attractive trade-offs between the quality of the solution and runtime, often outperforming the best previously published approaches.
1532971
Relative Generic Computational Forensic Techniques
Computational forensic engineering is the process of identification of the tool or algorithm that was used to produce a particular output or solution by examining the structural properties of the output. We introduce a new Relative Generic Forensic Engineering (RGFE) technique that has several advantages over the previously proposed approaches. The new RGFE technique not only performs more accurate identification of the tool used but also provides the identification with a level of confidence. Additionally, we introduce a generic formulation (integer linear programming formulation) which enables rapid application of the RGFE approach to a variety of problems that can be formulated as 0-1 integer linear programs. 
 
The key innovations of the RGFE technique include the development of a simulated annealing-based (SA) CART classification technique and a generic property formulation technique that facilitates property reuse. We introduce instance properties which enable an enhanced classification of problem instances leading to a higher accuracy of algorithm identification. Finally, the single most important innovation, property calibration, interprets the value for a given algorithm for a given property relative to the values for other algorithms. We demonstrated the effectiveness of the RGFE technique on the boolean satisfiability (SAT) and graph coloring (GC) problems.
969658
Performance Analysis of Secure Web Server Based on SSL
In recent years, protocols have been developed to ensure secure communications over the Internet, e.g., the secure sockets layer (SSL) and secure electronic transaction (SET). Deployment of these protocols incurs additional resource requirements at the client and server. This may have a negative impact on system performance. In this paper, we consider a scenario where users request information pages stored on a web server, and some of the requests require secure communication. An analytic model is developed to study the performance of a web server based on SSL. In our model, the details of the client-server interactions found in a typical SSL session are represented explicitly. Input parameters to this model are obtained by measuring an existing SSL implementation. Numerical examples on the performance characteristics of SSL are presented.
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.
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.
27801438
Scheduling Algorithms for Videotex Systems Under Broadcast Delivery
28524716
Deterministic projection by growing cell structure networks for visualization of high-dimensionality datasets
Recent advances in clinical proteomics data acquisition have led to the generation of datasets of high complexity and dimensionality. We present here a visualization method for high-dimensionality datasets that makes use of neuronal vectors of a trained growing cell structure (GCS) network for the projection of data points onto two dimensions. The use of a GCS network enables the generation of the projection matrix deterministically rather than randomly as in random projection. Three datasets were used to benchmark the performance and to demonstrate the use of this deterministic projection approach in real-life scientific applications. Comparisons are made to an existing self-organizing map projection method and random projection. The results suggest that deterministic projection outperforms existing methods and is suitable for the visualization of datasets of very high dimensionality.