2722356
Forensic engineering techniques for VLSI CAD tools
The proliferation of the Internet has affected the business model of almost all semiconductor and VLSI CAD companies that rely on intellectual property (IP) as their main source of revenues. The fact that IP has become more accessible and easily transferable, has influenced the emergence of copyright infringement as one of the most common obstructions to e-commerce of IP.
In this paper, we propose a generic forensic engineering technique that addresses a number of copyright infringement scenarios. Given a solution <italic>S<subscrpt>P</subscrpt></italic> to a particular optimization problem instance <italic>P</italic> and a finite set of algorithms <italic>A</italic> applicable to <italic>P</italic>, the goal is to identify with a certain degree of confidence the algorithm <italic>A<subscrpt>i</subscrpt></italic> which has been applied to <italic>P</italic> in order to obtain <italic>S<subscrpt>P</subscrpt></italic>. We have applied forensic analysis principles to two problem instances commonly encountered in VLSI CAD: graph coloring and boolean satisfiability. We have demonstrated that solutions produced by strategically different algorithms can be associated with their corresponding algorithms with high accuracy.
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.
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.
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.
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.
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.
2968096
An effective erasure node algorithm for slot reuse in DQDB
The distributed queue dual bus (DQDB) protocol, which has been specified by the IEEE 802.6 as the metropolitan area networks (MANs) standard, has an undesirable feature that busy slots that have been already received (i.e. read) continue to propagate downstream unnecessarily. The use of special nodes, known as erasure nodes, allows conversion of read slots to empty, so that downstream nodes may reuse these slots. This should result in an increase of the total throughput of the network. In the paper, the authors introduce and evaluate the performance of an erasure node algorithm. The algorithm keeps track of past activities on both buses to effectively balance the slot erasure and the request cancellation functions. They show that this algorithm possesses a number of features which make it superior to existing algorithms.<<ETX>>
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.
1948833
Synchronization of Distributed Simulation Using Broadcast Algorithms
Abstract Simulation, particularly of networks of queues, is an application with a high degree of inherent parallelism, and is of considerable practical interest. We continue the analysis of synchronization methods for distributed simulation, defined by the taxonomy in our previous paper. Specifically, we develop algorithms for time-driven simulation using a network of processors. For most of the synchronization methods considered, each node k of an n-node network simulation cannot proceed directly with its part of a simulation. Rather, it must compute some function Bk(ν1, ν2, …, νn), where νi is some value which must be obtained from node i. The value of νi at each node changes as the simulation progresses, and must be broadcast to every other node for the recomputation of the B-functions. In some cases, it is advantageous to compute the B-function in a distributed manner. Broadcast algorithms for such distributed computation are presented. Since the performance of a broadcast algorithm depends on the properties of the inter-process communication facility, we characterize some particular cases and give algorithms for each of them.
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 …