PoK

Author:Peng Ning,Kun Sun

Description:
This paper presents a systematic analysis of insider attacks against mobile ad hoc routing protocols, using the Ad hoc On Demand Distance Vector (AODV) proto col as an example. It identifies a number of attack goals, and then studies how to achieve these goals through misuses of the routing messages. To facilitate the anal ysis, it classifies insider attacks into two categories: atomic misuses and compound misuses. Atomic misuses are performed by manipulating a single routing message,which cannot be further divided; compound misuses are composed of combinations of atomic misuses and possibly normal uses of the routing protocol. The analy sis results in this paper reveal several classes of insider attacks, including route disruption, route invasion, node isolation, and resource consumption. Finally, this paper presents simulation results that validate and demonstrate the impact of these attacks.

Author:Kun Sun,Pai Peng,Peng Ning,Cliff Wang

Description:
In wireless sensor networks, clustering sensor nodes into small groups is an effective technique to achieve scalability, self organization, power saving, channel access, routing, etc. A number of cluster formation protocols have been proposed recently. However, most existing protocols assume benign environments, and are vulnerable to attacks from malicious nodes. In this paper, we propose a secure distributed cluster formation protocol to organize sensor networks into mutually disjoint cliques. Our protocol has the following properties: (1) normal nodes are divided into mutually disjoint cliques; (2) all the normal nodes in each clique agree on the same clique memberships; (3) while external attackers can be prevented from participating in the cluster formation process, inside attackers that do not follow the protocol semantics can be identified and removed from the network; (4) the communication overhead is moderate; (5) the protocol is fully distributed.

Author:Dudy Lim,Yew Soon Ong,Yao chu Jin,Bernhard Sendhoff,Bu Sung Lee

Description:
In this paper, we present an efficient Hierarchical Parallel Genetic Algorithm frame work using Grid computing (GEHPGA). The framework is developed using stan dard Grid technologies and has two distinctive features, 1) an extended GridRPC API to conceal the high complexity of Grid environment, and 2) a metascheduler for seamless resource discovery and selection. To assess the practicality of the frame work, theoretical analysis on the possible speed up o®ered is presented. Empirical study on GEHPGA using a benchmark problem and a realistic aerodynamic airfoil shape optimization problem for diverse Grid environments having di®erent com munication protocols, cluster sizes, processing nodes, at geographically disparate locations also indicates that the proposed GE HPGA using Grid computing oers a credible framework for providing significant speed up to evolutionary design optimization in science and engineering.

Author:Hsinchun Chen

Description:
Information retrieval using probabilistic techniques has attracted significant attention on the part of researchers in information and computer science over the past few decades. In the 198Os, knowledge based techniques also made an impressive contribution to “intelligent” information retrieval and indexing. More recently, information science researchers have turned to other newer artificial intelligence based inductive learning techniques including neural networks, symbolic learning, and genetic algorithms. These newer techniques, which are grounded on diverse paradigms, have provided great opportunities for researchers to enhance the information processing and retrieval capabilities of current information storage and retrieval systems. In this article, we first provide an overview of these newer techniques and their use in information science research. To familiarize readers with these techniques,we present three popular methods: the connectionist Hopfield network; the symbolic ID3/ID5R and evolution based genetic algorithms. We discuss their knowledge representations and algorithms in the context of information retrieval. Sample implementation and testing results from our own research are also provided for each technique. We believe these techniques are promising in their ability to analyze user queries, identify users information needs, and suggest alternatives for search. With proper user system interactions, these methods can greatly complement the prevailing full-text, keywordbased,probabilistic, and knowledge based techniques.

Author:ENRIC PLAZA, LORRAINE MCGINTY

Description:
Distribution of resources within case based reasoning (CBR) architectures is beneficial in a variety of application contexts. This article briefly discusses some of the approaches that fall under the heading of distributed CBR, and their general impact.