Machine learning is the study of building computer programs that improve their performance through experience. To meet the challenge of developing and maintaining larger and complex software systems in a dynamic and changing environment, machine learning methods have been playing an increasingly important role in many software development and maintenance tasks. Advances in Machine Learning Applications in Software Engineering provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. This book depicts applications of several machine...

A mobile agent system could be attacked by malicious agents, platforms and third parties. Mobile agents simply offer greater opportunities for abuse and misuse, which broadens the scale of threats significantly. In addition, since mobile agents have some unique characteristics such as their mobility, security problems have become more complicated in these systems. These security problems have become a bottleneck in the development and maintenance of mobile agent systems, especially in security sensitive applications such as electronic commerce. This book introduces the concept and structure...

Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms.

This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover...

This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emphasizes on the prediction and learning algorithms for intrusion detection and highlights techniques for intrusion detection of wired computer networks and wireless sensor networks. The performance comparison of various IDS via simulation will also be included.

Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine...

With the rapid growth of networking and high-computing power, the demand for large-scale and complex software systems has increased dramatically. Many of the software systems support or supplant human control of safety-critical systems such as flight control systems, space shuttle control systems, aircraft avionics control systems, robotics, patient monitoring systems, nuclear power plant control systems, and so on. Failure of safety-critical systems could result in great disasters and loss of human life. Therefore, software used for safety- critical systems should preserve high assurance...

The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics.