Subtitled "Combating Malware, Data Exfiltration, and more", this book reveals how attackers exploit DNS and how cybersecurity professionals can proactively use DNS to turn the tables and mitigate those threats. Joshua M Kuo and Ross Gibson show how knowing how to use the protective capabilities of DNS can give you an unprecedented head start in stopping today’s advanced cyberthreats.
Written specifically for security practitioners, and including real-world case studies, this book offers a thorough yet easy-to-digest understanding of today’s most urgent and potentially damaging DNS-based cyberthreats, how to mitigate them, and how to leverage your DNS infrastructure to further your security mission.
Author: Joshua M Kuo and Ross Gibson Publisher: Infoblox Date: July 2023 Pages: 166 ISBN: 978-1960940018 Print: 1960940015 Kindle: B0CDNYJJ9P Audience: General Level: Intermediate Category: Security
Topics covered:
- Why DNS is inherently vulnerable and why knowledge of DNS is now crucial for security teams
- How malware uses DNS to avoid detection and communicate with command-and-control (C2) infrastructure
- How threat actors use DNS in executing a broad array of attacks involving look-alike domains, domain generation algorithms, DNS tunneling, data exfiltration, and cache poisoning
- What DNSSEC is (and is not) and how it works
- How recently emerging encrypted DNS standards can impact security controls, along with the security advantages they can provide
- How DNS can be used in Zero Trust architectures
- How you can improve your security posture using the DNS infrastructure you already have
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Software Requirements Essentials
Authors: Karl Wiegers and Candase Hokanson Publisher: Addison-Wesley Pages: 208 ISBN: 9780138190286 Print: 0138190283 Kindle: B0BTLC53FF Audience: General Rating: 4.5 Reviewer: Kay Ewbank
This slim book looks at how to work out the requirements for a software project through twenty 'practices' that you c [ ... ]
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Grokking Machine Learning
Author: Luis G. Serrano Publisher: Manning Date: December 2021 Pages: 512 ISBN: 978-1617295911 Print: 1617295914 Kindle: B09LK7KBSL Audience: Python developers interested in machine learning Rating: 5 Reviewer: Mike James Another book on machine learning - surely we have enough by now?
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