Neeraj Kumar, Arzoo Miglani

Probabilistic Data Structures for Blockchain-Based Internet of Things Applications (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book covers theory and practical knowledge of probabilistic data structures (PDS) and blockchain (BC) concepts. It introduces the applicability of PDS in BC and each PDS has been explained through code snippets and illustrative examples. Further, it covers applications of PDS to BC along with implementation codes in Python.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 322
• Erscheinungstermin: 27. Januar 2021
• Englisch
• ISBN-13: 9781000327632
• Artikelnr.: 60915401

Autorenporträt

Prof. Neeraj Kumar received his Ph.D. in CSE from Shri Mata Vaishno Devi University, Katra (Jammu and Kashmir), India in 2009, and was a postdoctoral research fellow in Coventry University, Coventry, UK. He is working as a Professor in the Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology (Deemed to be University), Patiala (Pb.), India. His research areas are Network management, IoT, Big Data Analytics, Deep learning and cyber-security.

Arzoo Miglani is currently pursuing Ph.D. from Thapar Institute of Engineering & Technology (TIET), Patiala. She had worked with DIT University, Dehradun for 2 years as an assistant professor and with TIET for 1 year. She has done her ME in Information Security from TIET in 2015. She has completed her B.tech from GJU, Hisar in 2009. She is GATE qualified. Her research area includes Wireless Sensor networks and network security, blockchain and content centric networking.

Inhaltsangabe

Part I-Background: 1. Overview of Internet of Things. 2 Smart applications.
3. IoT challenges. Part II- Blockchain overview. 4 Python Basics. 5.
Cryptography primitives. 6. Blockchain technology and technical
foundations. 7. Verification and validation methods used by Blockchain. 8.
Data structures for Blockchain. Part III-Probabilistic data structures: An
overview. 9. Introduction to probabilistic data structures. 10. Membership
Query Probabilistic Data Structures. 11. Cardinality Estimation
Probabilistic Data Structures. 12. Frequency Count Query Probabilistic Data
Structures. 13. Approximate Similarity Search Query Probabilistic Data
Structures. Part IV-Integration of Probabilistic Data Structures with
Blockchain. 14. Applicability of membership query PDS with Blockchain. 15.
Applicability of cardinality estimation PDS with Blockchain. 16.
Applicability of frequency estimation PDS with Blockchain. 17.
Applicability of approximate similarity search PDS with Blockchain.