Security with AI and machine learning : using advanced tools to improve application security at the edge / Laurent Gil and Allan Liska.

Format:

Book

Author/Creator:

Gil, Laurent, author.

Liska, Allan, author.

Language:

English

Subjects (All):

Machine learning.

Artificial intelligence.

Computer networks--Security measures.

Computer networks.

Computer security.

Physical Description:

1 online resource (1 volume) : illustrations

Edition:

First edition.

Place of Publication:

Sebastopol, CA : O'Reilly Media, [2018]

System Details:

text file

Summary:

For security professionals seeking reliable ways to combat persistent threats to their networks, there’s encouraging news. Tools that employ AI and machine learning have begun to replace the older rules- and signature-based tools that can no longer combat today’s sophisticated attacks. In this ebook, Oracle’s Laurent Gil and Recorded Future’s Allan Liska look at the strengths (and limitations) of AI- and ML-based security tools for dealing with today’s threat landscape. This high-level overview demonstrates how these new tools use AI and ML to quickly identify threats, connect attack patterns, and allow operators and analysts to focus on their core mission. You’ll also learn how managed security service providers (MSSPs) use AI and ML to identify patterns from across their customer base. This ebook explains: Why rules-based, signature-based, and firewall solutions have fallen short How automated bots enable cybercriminals and nation-state actors to attack your network The evolution of the botnet: how threat actors constantly change their attack strategy How AI and ML techniques in web applications help you observe, quantify, and classify inbound requests How to detect insider threats and advanced persistent threat actors with AI and ML tools Case studies that show how a media company, an airline, and a university use AL and ML in security

Notes:

Description based on online resource; title from title page (Safari, viewed March 19, 2019).

Includes bibliographical references.

ISBN:

9781492043133

1492043133

9781492043126

1492043125

OCLC:

1090145241