Machine Learning and Data Mining for Computer Security

Machine Learning and Data Mining for Computer Security

Methods and Applications
Marcus A Maloof
Springer Nature Singapore
Besorgungstitel - wird vorgemerkt | Lieferzeit:Besorgungstitel - Lieferbar innerhalb von 10 Werktagen I

149,79 €*

Alle Preise inkl. MwSt. | Versandkostenfrei
Gewicht:
477 g
Format:
246x164x23 mm
Beschreibung:

"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.

This timely book provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. It has a strong focus on information processing and combines and extends results from the hot topic of computer security.
Survey Contributions.- An Introduction to Information Assurance.- Some Basic Concept of Machine Learning and Data Mining.- Research Contributions.- Learning to Detect Malicious Executables.- Data Mining Applied to Intrusion Detection: MITRE Experiences.- Intrusion Detection Alarm Clustering.- Behavioral Features for Network Anomaly Detection.- Cost-Sensitive Modeling for Intrusion Detection.- Data Cleaning and Enriched Representations for Anomaly Detection in System Calls.- A Decision-Theoritic, Semi-Supervised Model for Intrusion Detection.
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.

weniger

Kunden Rezensionen

Zu diesem Artikel ist noch keine Rezension vorhanden.
Helfen sie anderen Besuchern und verfassen Sie selbst eine Rezension.
> neue Rezension schreiben