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Artificial Intelligence for Big Data

You're reading from  Artificial Intelligence for Big Data

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788472173
Pages 384 pages
Edition 1st Edition
Languages
Authors (2):
Anand Deshpande Anand Deshpande
Profile icon Anand Deshpande
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (19) Chapters close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. Big Data and Artificial Intelligence Systems 2. Ontology for Big Data 3. Learning from Big Data 4. Neural Network for Big Data 5. Deep Big Data Analytics 6. Natural Language Processing 7. Fuzzy Systems 8. Genetic Programming 9. Swarm Intelligence 10. Reinforcement Learning 11. Cyber Security 12. Cognitive Computing 1. Other Books You May Enjoy Index

Understanding SIEM


Security Incident and Event Management (SIEM) is a process that helps cyber security implementation by gathering security-related information (network and application logs for example) at a centralized location or tags those information assets at the edge (the location where the data is generated in the case of IoT) and uses this information for identification of anomalies which indicates breaches to the security infrastructure of an enterprise.

The SIEM also facilitates continuous monitoring of the security infrastructure by providing intuitive visualization dashboards. SIEM as a process is implemented as a suite of software which is governed by enterprise security with role-based access control. The common characteristic features of the SIEM system are depicted in the following diagram:

Figure 11.9 Features of the SIEM system

The SIEM software application needs to support the basic building blocks as follows:

  • Data Collection: The SIEM software should support a variety of...
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