Agent fabrication and its implementation for agent-based electronic commerce

In the last decade, agent-based e-commerce has emerged as a potential role for the next generation of e-commerce. How to create agents for e-commerce applications has become a serious consideration in this field. This paper proposes a new scheme named agent fabrication and elaborates its implementation in multi-agent systems based on the SAFER (Secure Agent Fabrication, Evolution & Roaming) architecture. First, a conceptual structure is proposed for software agents carrying out e-commerce activities. Furthermore, agent module suitcase is defined to facilitate agent fabrication. With these definitions and facilities in the SAFER architecture, the formalities of agent fabrication are elaborated. In order to enhance the security of agent-based e-commerce, an infrastructure of agent authorization and authentication is integrated in agent fabrication. Our implementation and prototype applications show that the proposed agent fabrication scheme brings forth a potential solution for creating agents in agent-based e-commerce applications

Incremental evolution of classifier agents using incremental genetic algorithms

Ph.DDOCTOR OF PHILOSOPH

HandyBroker - An intelligent product-brokering agent for M-commerce applications with user preference tracking

One of the potential applications for agent-based systems is m-commerce. A lot of research has been done on making such systems intelligent to personalize their services for users. In most systems, user-supplied keywords are generally used to help generate profiles for users. In this paper, an evolutionary ontology-based product-brokering agent has been designed for m-commerce applications. It uses an evaluation function to represent a user’s preference instead of the usual keyword-based profile. By using genetic algorithms, the agent tracks the user’s preferences for a particular product by tuning some parameters inside its evaluation function. A prototype called “Handy Broker” has been implemented in Java and the results obtained from our experiments looks promising for m-commerce use

A Factory-based Approach to Support E-commerce Agent Fabrication

With the development of Internet computing and software agent technologies, agent-based e-commerce is emerging. How to create agents for e-commerce applications has become an important issue along the way to success. We propose a factory-based approach to support agent fabrication in e-commerce and elaborate a design based on the SAFER (Secure Agent Fabrication, Evolution & Roaming) framework. The details of agent fabrication, modular agent structure, agent life cycle, as well as advantages of agent fabrication are presented. Product-brokering agent is employed as a practical agent type to demonstrate our design and Java-based implementation

Reactive Planning for Olfactory-Based Mobile Robots

Abstract-Olfaction is a long distance sense, which is widely used by animals for foraging or reproductive activities. Olfaction plays a significant role in natural life of most animals. For some animals, olfactory cues are far more effective than visual or auditory cues in search for objects such as foods and nests. Although chemical sensing is far simpler than vision or hearing, navigation in a chemical diffusion field is still not well understood. Therefore, this powerful primary sense has rarely been used inside the robotics community. This paper presents an effective olfactory-based planning and search algorithms for using on mobile robots. Olfactory-based mobile robots use odors as a guide to navigate and track in the unknown environments. The planning algorithms are based on Bayesian inference theory and artificial potential field methods. Inputs to the algorithms include the measured flow and the detection or non-detection events that happened at the robot location. This methodology results in algorithms for predicting likelihood of source location versus position. The robot would then optimize a desired trajectory to navigate in the odor plume and locate the odor source location

Feature selection for modular GA-based classification

Genetic algorithms (GAs) have been used as conventional methods for classifiers to adaptively evolve solutions for classification problems. Feature selection plays an important role in finding relevant features in classification. In this paper, feature selection is explored with modular GA-based classification. A new feature selection technique, Relative Importance Factor (RIF), is proposed to find less relevant features in the input domain of each class module. By removing these features, it is aimed to reduce the classification error and dimensionality of classification problems. Benchmark classification data sets are used to evaluate the proposed approach. The experiment results show that RIF can be used to find less relevant features and help achieve lower classification error with the feature space dimension reduced

Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis

Product recommendation and preference tracking systems have been adopted extensively in e-commerce businesses. However, the heterogeneity of product attributes results in undesired impediment for an efficient yet personalized e-commerce product brokering. Amid the assortment of product attributes, there are some intrinsic generic attributes having significant relation to a customer’s generic preference. This paper proposes a novel approach in the detection of generic product attributes through feature analysis. The objective is to provide an insight to the understanding of customers’ generic preference. Furthermore, a genetic algorithm is used to find the suitable feature weight set, hence reducing the rate of misclassification. A prototype has been implemented and the experimental results are promising

Double threshold authentication using body area radio channel characteristics

The demand of portable and body-worn devices for remote health monitoring is ever increasing. One of the major challenges caused by this influx of wireless body area network (WBAN) devices is security of user's extremely vital and personal information. Conventional authentication techniques implemented at upper layers of the Open System Interconnection (OSI) model usually consumes huge amount of power. They also require significant changes at hardware and software levels. It makes them unsuitable for inherently low powered WBAN devices. This letter investigates the usability of a double threshold algorithm as a physical layer security measure in these scenarios. The algorithm is based on the user's behavioral fingerprint extracted from the radio channel characteristics. Effectiveness of this technique is established through experimental measurements considering a variety of common usage scenarios. The results show that this method provides high level of security against false authentication attacks and has great potential in WBANs

Patterns-of-Life Aided Authentication

Wireless Body Area Network (WBAN) applications have grown immensely in the past few years. However, security and privacy of the user are two major obstacles in their development. The complex and very sensitive nature of the body-mounted sensors means the traditional network layer security arrangements are not sufficient to employ their full potential, and novel solutions are necessary. In contrast, security methods based on physical layers tend to be more suitable and have simple requirements. The problem of initial trust needs to be addressed as a prelude to the physical layer security key arrangement. This paper proposes a patterns-of-life aided authentication model to solve this issue. The model employs the wireless channel fingerprint created by the user’s behavior characterization. The performance of the proposed model is established through experimental measurements at 2.45 GHz. Experimental results show that high correlation values of 0.852 to 0.959 with the habitual action of the user in different scenarios can be used for auxiliary identity authentication, which is a scalable result for future studies