Machine Learning And Data Mining For Computer Security: Methods And Applications

Maloof

ISBN 10: 184628029X / ISBN 13: 9781846280290

Editore: Springer, 2005

Riguardo questo articolo

Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Codice articolo ABNR-241780

Dati bibliografici

• Titolo: Machine Learning And Data Mining For Computer Security: Methods And Applications
• Editore: Springer
• Data di pubblicazione: 2005
• Lingua: Inglese
• ISBN 10: 184628029X
• ISBN 13: 9781846280290
• Rilegatura: Brossura
• Edizione: Edizione Internazionale
• Condizione: New

Descrizione articolo

Riassunto

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information processing and combines and extends results from computer security.

The first part of the book surveys the data sources, the learning and mining methods, evaluation methodologies, and past work relevant for computer security. The second part of the book consists of articles written by the top researchers working in this area. These articles deals with topics of host-based intrusion detection through the analysis of audit trails, of command sequences and of system calls as well as network intrusion detection through the analysis of TCP packets and the detection of malicious executables.

This book fills the great need for a book that collects and frames work on developing and applying methods from machine learning and data mining to problems in computer security.

Dalla quarta di copertina

The Internet began as a private network connecting government, military, and academic researchers. As such, there was little need for secure protocols, encrypted packets, and hardened servers. When the creation of the World Wide Web unexpectedly ushered in the age of the commercial Internet, the network's size and subsequent rapid expansion made it impossible retroactively to apply secure mechanisms. The Internet's architects never coined terms such as spam, phishing, zombies, and spyware, but they are terms and phenomena we now encounter constantly.

Programming detectors for such threats has proven difficult. Put simply, there is too much information---too many protocols, too many layers, too many applications, and too many uses of these applications---for anyone to make sufficient sense of it all. Ironically, given this wealth of information, there is also too little information about what is important for detecting attacks.

Methods of machine learning and data mining can help build better detectors from massive amounts of complex data. Such methods can also help discover the information required to build more secure systems. For some problems in computer security, one can directly apply machine learning and data mining techniques. Other problems, both current and future, require new approaches, methods, and algorithms.

This book presents research conducted in academia and industry on methods and applications of machine learning and data mining for problems in computer security and will be of interest to researchers and practitioners, as well students.

  Dr. Maloof not only did a masterful job of focusing the book on a critical area that was in dire need of research, but he also strategically picked papers that complemented each other in a productive manner. This book is a must read for anyone interested in how research can improve computer security.

Dr Eric Cole, Computer Security Expert