No abstract

In order to deter cyber terrorism, it is important to identify the terrorists, since punishment may not deter them. The identification probability relies heavily on tracking cyber terrorists. However, there are legal and technical challenges to tracking terrorists. This paper proposes suggestions and insights on overcoming these challenges. Three types of infrastructures must be present in order to deter cyber terrorism: technical, policy, and legal. We list some of the key items that academics as well as practitioners need to focus on to improve cyber-terrorism deterrence.

Information Systems (IS) Security has become a critical issue in the IT world. Among all threats against IS security, the insider threat is the greatest. This paper proposes a game theoretical model to study the economic impact of insider threats on IS security investments. We identify three factors influencing the optimal IS security investment: breach function sensitivity, deterrence level, and advantage rate. Our simulation results show that the optimal investment required to protect an information systems infrastructure from insiders is several magnitudes higher than for protecting against external hackers.does not work for malicious insiders, because their intentions are to steal, modify, or destroy valuable data/files. In this paper, we treat a malicious insider as an internal hacker, who has more advantages over an external hacker. Without a special mention, an insider equals to a malicious insider, as well as an internal hacker, in this paper.The quality of IS security is highly related to the investments in IS security (Bojanc & Jerman-Blazic, 2008). The appropriate level of the IS security investment can enhance the capability of organizations and governments to reduce the threats from insiders (Bodin & Gordon, 2005). The aim of this paper is to use game theory to model the insider threat risks in the IT-based information systems. We propose a static game model which can then be used to compare the optimal investments for insiders and external hackers. This paper attempts to find an appropriate approach to study the economic impact of insider threats on IS security investments.

Despite the commercial success of data mining, a major drawback has been acknowledged across academic, industry, and government sectors, namely, the issue of violating the privacy of individuals. We propose a data transformation method based on wavelets to disguise private data while preserving the original classification patterns. Wavelet transformations have been used extensively in signal processing for data reduction, multiresolution analysis, and removing noise from data. In our implementation, two commonly used wavelet transforms, the Haar and the Daub-4 transforms, are tested for pattern and privacy preservation in classification mining tasks. Empirical results confirm that the Haar and the Daub-4 transforms preserve the classification patterns and preserve the privacy for real valued data.

The purpose of this paper is to describe the design and implementation of a Web-based geographic information system (GIS) for providing online crash information and statistical information for commercial vehicle crashes. The system is capable of displaying crash data such as specific geographic location, period and time of crashes, severity, contributing factors, and cost. The system supports interagency communication with the purpose of reducing the number of crashes. Through the description of the design and implementation of the system, we demonstrate the feasibility of addressing spatial problems in a collaborative OLAP environment. It provides a guide for the design and development of similar systems and identifies a series or related, but yet unsolved, research problems.