To secure information systems, the security risks and requirements must be clearly understood before the proper security mechanisms can be identified and designed. Today’s security requirement specifications are generally incomplete and narrowly focused, which leads to ineffective security designs of information systems. The author asserts that multiple views—management, threat, resource, process, assessment, and legal—of information systems provides an opportunity for a better understanding of security risks and requirements. In this paper, the author proposes a six-view perspective of a system security framework to identify a more complete set of security risks and requirements. The proposed framework presents a synergistic view of the system security in which the author presents an extensive list of heuristics/guidelines under each view, discussing security issues, risks, and requirements. Through a case study, the authors shows that a multiple view perspective of system security is effective in determining a more complete set of security requirements than the traditional approach of focusing on threats alone.

The extent methods largely ignore the importance of integrating security requirements with business requirements and providing built-in steps for dealing with these requirements seamlessly. To address this problem, a new approach to secure network analysis and design is presented. The proposed method, called the SEACON method, provides an integrated approach to use existing principles of information systems analysis and design with the unique requirements of distributed secure network systems. We introduce several concepts including security adequacy level, process-location-security matrix, data-location- security matrix, and secure location model to provide built-in mechanisms to capture security needs and use them seamlessly throughout the steps of analyzing and designing secure networks. This method is illustrated and compared to other secure network design methods. The SEACON method is found to be a useful and effective method.

In this correspondence, we point out some of the major shortcomings that we have discovered in the article titled "Factors that Impact Implementing a System Development Methodology" by Roberts et al. (1998). The article was published in the August 1998 issue of IEEE Transactions of Software Engineering. The article contains multiple problems that, if not pointed out, have the potential to lead to a state of confusion among researchers and practitioners alike. In particular, the article has the following problems: (1) The authors claim that the lack of theoretical basis for their factors is due to the fact that SDM implementation has never been studied in the literature. In fact, there is a multitude of studies very similar to that of Roberts at al. (2) The study does not meet commonly accepted standards for factor analysis procedures such as a minimum sample size ratio of 5:1, a ratio mandated even by the authors' own citations. This and other factor analysis problems lead to results that are questionable. In order to make the published article more useful to researchers and practitioners, this paper corrects some of the inaccuracies in the Roberts et al.'s article by: providing a brief literature review of some articles that are similar to the Roberts et al., study; and noting some of the technical inaccuracies in the data analysis procedures used by the authors so that the results can be interpreted in the proper context.

A number of research communities recognize artificial intelligence (AI) as a valid reference discipline. However, several papers have criticized AI's research methodologies. This paper attempts to clarify and improve the methods used in AI. Definitions are proposed for terms such as AI theory, principles, hypotheses, and observations. Next, a unified view of AI research methodology is proposed. This methodology contains a long term dimension based upon the scientific method and an individual project dimension. The individual project dimension identifies four strategies: hypothetical/deductive, hermeneutical/inductive, case-based, and historical analysis. The strategies differ according to how prototyping is used in an experiment.>

Much research has been done in developing improved genetic algorithms (GA's). Past research has focused on the improvement of operators and parameter settings and indicates that premature convergence is still the preeminent problem in GA's. This paper presents an improved genetic algorithm based on migration and artificial selection (GAMAS). GAMAS is an algorithm whose architecture is specifically designed to confront the causes of premature convergence. Though based on simple genetic algorithms, GAMAS is not concerned with the evolution of a single population, but instead is concerned with macroevolution, or the creation of multiple populations or species, and the derivation of solutions from the combined evolutionary effects of these species. New concepts that are emphasized in this architecture are artificial selection, migration, and recycling. Experimental results show that GAMAS consistently outperforms simple genetic algorithms and alleviates the problem of premature convergence.>

The author proposes a technique called control and definition modularization (CDM), which derives a systematic program layout from a given structure chart using the concepts of 'control' and 'definition' modules. A control module includes processes for handling a conceptual data object not directly implementable. A definition module defines operations associated with a concrete data object implementable using a primitive or derived data type of a programming language. Grouping the operations available for each concrete data object, and keeping them separated from execution flow, improves programs maintainability. This technique extends the structured design methodology and provides designers with a systematic way of deriving informational strength modules as well as a structured physical layout from the structure chart. A program based on the CDM technique is easier to understand and maintain. This research makes a significant contribution toward bridging the gap between structured design and object-oriented concepts.>