Narayan Securing Hadoop

Implement robust end-to-end security for your Hadoop ecosystem
1. Auflage 2025
ISBN: 978-1-78328-526-6
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 116 Seiten

Implement robust end-to-end security for your Hadoop ecosystemKey Features - Master the key concepts behind Hadoop security as well as how to secure a Hadoop-based Big Data ecosystem
- Understand and deploy authentication, authorization, and data encryption in a Hadoop-based Big Data platform
- Administer the auditing and security event monitoring system
Book DescriptionSecurity of Big Data is one of the biggest concerns for enterprises today. How do we protect the sensitive information in a Hadoop ecosystem? How can we integrate Hadoop security with existing enterprise security systems? What are the challenges in securing Hadoop and its ecosystem? These are the questions which need to be answered in order to ensure effective management of Big Data. Hadoop, along with Kerberos, provides security features which enable Big Data management and which keep data secure. This book is a practitioner's guide for securing a Hadoop-based Big Data platform. This book provides you with a step-by-step approach to implementing end-to-end security along with a solid foundation of knowledge of the Hadoop and Kerberos security models. This practical, hands-on guide looks at the security challenges involved in securing sensitive data in a Hadoop-based Big Data platform and also covers the Security Reference Architecture for securing Big Data. It will take you through the internals of the Hadoop and Kerberos security models and will provide detailed implementation steps for securing Hadoop. You will also learn how the internals of the Hadoop security model are implemented, how to integrate Enterprise Security Systems with Hadoop security, and how you can manage and control user access to a Hadoop ecosystem seamlessly. You will also get acquainted with implementing audit logging and security incident monitoring within a Big Data platform.What you will learn - Understand the challenges of securing Hadoop and Big Data and master the reference architecture for Big Data security
- Demystify Kerberos and the Hadoop security model
- Learn the steps to secure a Hadoop platform with Kerberos
- Integrate Enterprise Security Systems with Hadoop security and build an integrated security model
- Get detailed insights into securing sensitive data in a Hadoop Big Data platform
- Implement audit logging and a security event monitoring system for your Big Data platform
- Discover the various industry tools and vendors that can be used to build a secured Hadoop platform
- Recognize how the various Hadoop components interact with each other and what protocols and security they implement
- Design a secure Hadoop infrastructure and implement the various security controls within the enterprise
Who this book is forThis book is great for Hadoop practitioners (solution architects, Hadoop administrators, developers, and Hadoop project managers) who are looking to get a good grounding in what Kerberos is all about and who wish to learn how to implement end-to-end Hadoop security within an enterprise setup. It's assumed that you will have some basic understanding of Hadoop as well as be familiar with some basic security concepts.

Autoren/Hrsg.

Narayan, Sudheesh

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Über Autor(innen)

Narayan Sudheesh :

Sudheesh Narayanan is a Technology Strategist and Big Data Practitioner with expertise in technology consulting and implementing Big Data solutions. With over 15 years of IT experience in Information Management, Business Intelligence, Big Data & Analytics, and Cloud & J2EE application development, he provided his expertise in architecting, designing, and developing Big Data products, Cloud management platforms, and highly scalable platform services. His expertise in Big Data includes Hadoop and its ecosystem components, NoSQL databases (MongoDB, Cassandra, and HBase), Text Analytics (GATE and OpenNLP), Machine Learning (Mahout, Weka, and R), and Complex Event Processing. Sudheesh is currently working with Genpact as the Assistant Vice President and Chief Architect – Big Data, with focus on driving innovation and building Intellectual Property assets, frameworks, and solutions. Prior to Genpact, he was the co-inventor and Chief Architect of the Infosys BigDataEdge product.