Abbas K. Zaidi

A multi-technique approach for user identification through keystroke dynamics

Legitimate user authentication is an important part of the problems related to computer and system security. The maintenance of security becomes even more difficult when an invalid user gets the system access information. The paper presents a suite of techniques for password authentication using neural networks, fuzzy logic, statistical methods, and several hybrid combinations of these approaches. The approaches presented in the paper use typing biometrics of a user, in addition to conventional login information, to identify a user.

Validation and verification of decision making rules

A methodology for the validation and verification of decision making rules is presented. The methodology addresses the general problem of detecting problematic cases in a set of rules expressed as statements in formal logic. This representation of the decision rules makes the problem general in terms of application domains, and also provides an analytical base for defining errors. The approach is based on viewing a rule base as an organization of information that flows from one process (rule) to another. The key step in the methodology is the transformation of the set of decision rules into an equivalent Petri net. The static and dynamic properties of the resulting Petri net are shown to reveal patterns of structures that correspond to the problematic cases. The techniques presented in this paper are based on theory and are supported by software tools.

A heuristic approach for best sets of actions determination in influence nets

The paper presents a heuristic approach for the problem of finding the best or close-to-best sets of actions in uncertain situations modeled by influence nets. The approach enhances the analysis capability of influence nets by allowing the user to observe the combined impact of actions on the desired effect in contrast to the sensitivity analysis that allows the user to evaluate individual impacts only. Unlike the exhaustive search which works in exponential time, the proposed approach generates result in polynomial time. The paper also demonstrates the generalization of alternative sets of actions.

Planning temporal events using point-interval logic

The paper presents a temporal logic and its application to planning time-critical missions. An extended version of the Point-Interval Logic (PIL) is presented that incorporates both point and interval descriptions of time. The points and intervals in this formalism represent time stamps and time delays, respectively, associated with events/activities in a mission as constraints on or as resultants of a planning process. The lexicon of the logic offers the flexibility of qualitative and/or quantitative descriptions of temporal relationships between points and intervals of a system. The provision for qualitative temporal relationships makes the approach suitable for situations where all the required quantitative information may not be available to planners. A graph-based approach, called the Point Graph (PG) methodology, is shown to implement the axiomatic system of PIL by transforming the temporal specifications into Point Graphs. A temporal inference engine uses the Point Graph representation to infer and verify the feasibility of temporal relations among system intervals/points. The paper demonstrates the application of PIL and its inference engine to a mission-planning problem.

Theory of Influence Networks

Influence networks are Bayesian networks whose probabilities are approximated via expert provided influence constants. They represent a modeling and analysis formalism for addressing complex decision problems. In this paper, we present a comprehensive theory of influence networks that incorporates design constraints for consistency, temporal issues and a dynamic programming evolution of the influence constants. We also include numerical evaluations for several example timed influence networks.

Meta-modeling the Cultural Behavior Using Timed Influence Nets

A process that can be used to assist analysts in developing domain specific Timed Influence Nets (TIN) is presented. The process can be used to represent knowledge about a situation that includes descriptions of cultural behaviors and actions that may influence such behaviors. One of the main challenges in using TINs has been the difficulty in formulating them. Many Subject Matter Experts have difficulty in expressing their knowledge in the TIN representation. The ontology based meta modeling approach described in this paper provides potential assistance to these modelers so that they can quickly create new models for new situations and thus can spend more time doing analysis. The paper describes the theoretic concepts used and a process that leads to an automated TIN generation. A simple example is provided to illustrate the technique.

Validation and Verification of Decision Making Rules

Abstract A methodology for the validation and verification (V&V) of decision making rules is proposed. The methodology addresses the general problem of detecting problematic cases in a set of rules. The rules are expressed as statements in formal logic. The definition of decision rules in formal logic makes the problem general in terms of application domains, and also provides an analytical base for defining errors. The approach is based on viewing a rule base as an organization of information that flows from one process (rule) to another. Since Petri Nets provide a powerful modeling and analysis tool for information flow structures, the methodology transforms a set of decision rules into an equivalent Petri Net representation. The static and dynamic properties of the graph are shown to reveal patterns of Petri Net structures that correspond to the problematic cases. The tools and techniques presented in this paper are based on theory and are supported by software tools.

Modeling with Influence Networks using influence constants: A new approach

Complex decision problems present numerous modeling and analysis challenges. A number of approaches have been devised in an effort to meet these challenges; one of them is Influence Networks. In this paper, we present a new comprehensive approach to the formalism of Influence Networks that eliminates previously existing inconsistencies and incorporates temporal issues as well. We also use the approach to evaluate a specific decision problem.

Improving cluster tools performance using colored Petri nets in semiconductor manifacturing

Semiconductor manufacturing is a capital-extensive industry. How to utilize billions of dollars of equipment as efficiently as possible is a critical factor for a semiconductor manufacturer to succeed in stiff competition. Improving performance of manufacturing process increases overall tool throughput, reduces operating costs, and saves companies millions of dollars. In this study, we develop a methodology to analyze and improve a cluster tools performance. A Colored Petri Net model is developed to determine internal bottleneck resource of the tool. Results conclude that the methodology improves tool efficiency and provides significant cost savings.

An algorithm for activation timed influence nets

Activation Timed Influence Net (ATIN) is a term representing a progressively evolving sequence of actions, where the effects of an action become the preconditions of the action that follows. An ATIN integrates the notions of time and uncertainty in a network model, where nodes explicitly represent mechanisms and/or tactical actions that are responsible for changes in the state of a domain. In this paper, we present an algorithm for the initialization of actions within a ATIN.