35433625
Secure Mobile Computing
As more and more people enjoy the various services brought by mobile computing, it is becoming a global trend in today’s world. At the same time, securing mobile computing has been paid increasing attention. In this article, we discuss the security issues in mobile computing environment. We analyze the security risks confronted by mobile computing and present the existing security mechanisms.
15237323
Testing and Fault Tolerance of Multistage Interconnection Networks
Test length is independent of network size in this simple, straightforward methodology for testing MINs (multistage interconnection networks). It requires only four test sequences for single-fault diagnosis. 26 references.
22890668
Arithmetic Algorithms in a Negative Base
Algorithms are described for the basic arithmetic operations in a negative base. These algorithms are simpler, faster, and more general than those proposed by Sankar et al.
43408451
Network Intrusion Detection System Using Random Projection Technique
26743853
Design and Analysis of a Class of Highly Scalable Hierarchical Networks: PdBCube
Abstract A class of hierarchical networks called the dBCube, that provides cost-effective and high-performance communication in large multicomputer systems, has recently been introduced. Such a compound graph of a hypercube and a de Bruijn (dB) graph utilizes every node of the hypercube as a gateway for intercluster communication. This paper presents a partially connected dBCube subclass (PdBCube), wherein the use of fewer nodes as gateways makes the PdBCube highly scalable in terms of both the hypercube and the dB size. This enhancement in scalability can be achieved by two different approaches to assigning gateways. Performance degradation of the proposed PdBCube is illustrated in terms of diameter and average distance. Improvement in track efficiency and reduction in cost are observed to be directly related to a decrease in the number of remote links.
40094538
A Generic Design Methodology for Deadlock-Free Routing in Multicomputer Networks
This paper introduces a generic methodology for defining deadlock-free wormhole routing schemes in any arbitrary network. The basic strategy is to partition a graph into subdigraphs with no cyclic dependencies and selectively assign virtual channels. The usefulness of our scheme is shown for the n-dimensional hypercube, the n-dimensional mesh, and the k-ary n-cube torus by identifying subdigraph characteristics that ensure acyclic routing. Further generalization which allows partial cyclic dependencies without deadlock is achieved by our extended generic methodology. We also illustrate how to identify shortest fixed path and nonminimal adaptive routing schemes using minimum required channels.
14060994
On nearest neighbor indexing of nonlinear trajectories
In recent years, the problem of indexing mobile objects has assumed great importance because of its relevance to a wide variety of applications. Most previous results in this area have proposed indexing schemes for objects with linear trajectories in one or two dimensions. In this paper, we present methods for indexing objects with nonlinear trajectories. Specifically, we identify a useful condition called the convex hull property and show that any trajectory satisfying this condition can be indexed by storing a careful representation of these objects in a traditional index structure. Since a wide variety of relevant nonlinear trajectories satisfy this condition, our result significantly expands the class of trajectories for which nearest neighbor indexing schemes can be devised. We also show that even though many non-linear trajectories do not satisfy the convex hull condition, an approximate representation can often be found which satisfies it. We discuss examples of techniques which can be utilized to find representations that satisfy the convex hull property. We present empirical results to demonstrate the effectiveness of our indexing method.
3172403
On overlay schemes to support point-in-range queries for scalable grid resource discovery
A resource directory is a critical component of a grid architecture. P2P computing paradigm could address some of the scalability issues that make distributed resource discovery services challenging. Unfortunately, most existing distributed hash table (DHT) based P2P overlays have difficulty in treating attribute range queries that are common in resource discovery lookups. This paper proposes a general framework for range-based resource discovery. In particular, the proposed framework maps tree-structured logical data (i.e., range indexing) onto a DHT-based physical node space (i.e., resource brokers). In this paper, we consider three mapping schemes from the logical space onto the physical space. Each mapping scheme uses a different replication mechanism to reduce range search time and to achieve load balance. We analytically and experimentally compare the performance characteristics (query/update costs and workload distributions) of these schemes and discuss their applicability under different resource discovery service scenarios.
1271310
Policy ratification
It is not sufficient to merely check the syntax of new policies before they are deployed in a system; policies need to be analyzed for their interactions with each other and with their local environment. That is, policies need to go through a ratification process. We believe policy ratification becomes an essential part of system management as the number of policies in the system increases and as the system administration becomes more decentralized. In this paper, we focus on the basic tasks involved in policy ratification. To a large degree, these basic tasks can be performed independent of policy model and language and require little domain-specific knowledge. We present algorithms from constraint, linear, and logic programming disciplines to help perform ratification tasks. We provide an algorithm to efficiently assign priorities to the policies based on relative policy preferences indicated by policy administrators. Finally, with an example, we show how these algorithms have been integrated with our policy system to provide feedback to a policy administrator regarding potential interactions of policies with each other and with their deployment environment.
15003245
Probabilistic treatment of MIXes to hamper traffic analysis
The goal of anonymity providing techniques is to preserve the privacy of users, who has communicated with whom, for how long, and from which location, by hiding traffic information. This is accomplished by organizing additional traffic to conceal particular communication relationships and by embedding the sender and receiver of a message in their respective anonymity sets. If the number of overall participants is greater than the size of the anonymity set and if the anonymity set changes with time due to unsynchronized participants, then the anonymity technique becomes prone to traffic analysis attacks. We are interested in the statistical properties of the disclosure attack, a newly suggested traffic analysis attack on the MIXes. Our goal is to provide analytical estimates of the number of observations required by the disclosure attack and to identify fundamental (but avoidable) 'weak operational modes' of the MIXes and thus to protect users against a traffic analysis by the disclosure attack.
7357174
On the design and quantification of privacy preserving data mining algorithms
The increasing ability to track and collect large amounts of data with the use of current hardware technology has lead to an interest in the development of data mining algorithms which preserve user privacy. A recently proposed technique addresses the issue of privacy preservation by perturbing the data and reconstructing distributions at an aggregate level in order to perform the mining. This method is able to retain privacy while accessing the information implicit in the original attributes. The distribution reconstruction process naturally leads to some loss of information which is acceptable in many practical situations. This paper discusses an Expectation Maximization (EM) algorithm for distribution reconstruction which is more effective than the currently available method in terms of the level of information loss. Specifically, we prove that the EM algorithm converges to the maximum likelihood estimate of the original distribution based on the perturbed data. We show that when a large amount of data is available, the EM algorithm provides robust estimates of the original distribution. We propose metrics for quantification and measurement of privacy-preserving data mining algorithms. Thus, this paper provides the foundations for measurement of the effectiveness of privacy preserving data mining algorithms. Our privacy metrics illustrate some interesting results on the relative effectiveness of different perturbing distributions.