Digital Signature Quantification in the Bitcoin Blockchain: A Statistical Approach

  • Hussein Kazem
  • , Youakim Badr
  • , Nour El Madhoun
  • , Pierrick Conord

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Digital signatures are crucial for blockchain security, ensuring transaction authenticity, integrity, and non-repudiation. This reliance on secure digital signatures also extends to emerging blockchain applications like in the Internet of Vehicles (IoV) and the Internet of Devices (IoD). However, the emergence of Post-Quantum Cryptography (PQC) poses a potential threat to blockchain performance by significantly increasing the size of digital signatures and public keys. This paper examines the number of signatures per block in the Bitcoin network using a real-world data-driven analysis. We propose an efficient signature counting algorithm that processes transaction data and accounts for all acceptable digital signature formats. To evaluate the methodology and the quality of the data, we apply the Shapiro-Wilk test for normality and use the Coefficient of Variation (CV) to assess data distribution and variability. This research advances blockchain analytics by offering a systematic approach to quantifying digital signatures.

Original languageEnglish (US)
Title of host publication2025 12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages93-99
Number of pages7
ISBN (Electronic)9798331552763
DOIs
StatePublished - 2025
Event12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025 - Paris, France
Duration: Jun 18 2025Jun 20 2025

Publication series

Name2025 12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025

Conference

Conference12th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2025
Country/TerritoryFrance
CityParis
Period6/18/256/20/25

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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