of transactions per day.Figure 20.10 Median time confirmation of transactions.Figure 20.11 Algorithm modification.Figure 20.12 Execution of new algorithm.Figure 20.13 Block services.Figure 20.14 Block services.Figure 20.15 Transaction services.Figure 20.16 Working directory.Figure 20.17 Number of transactions per day.Figure 20.18 Energy consumption per day.Figure 20.19 Block size.Figure 20.20 Future scopes of blockchain.20 Chapter 21Figure 21.1 Linking of multiple blocks in a blockchain system.Figure 21.2 Typical block structure in a blockchain system.Figure 21.3 SHA-256 Hash Function.Figure 21.4 SHA-256 Hash Function after block segmentation.Figure 21.5 Insertion/encryption of a new block into the blockchain.Figure 21.6 Vote count process in online voting system using blockchain approach...Figure 21.7 General interaction in online voting system using blockchain.Figure 21.8 Potential framework of an online voting system using blockchain.Figure 21.9 Steganographic system framework [3].Figure 21.10 Steganographic embedding process [3].Figure 21.11 Proposed system framework using visual cryptography [4].Figure 21.12 Sample image share generation in proposed system [4].Figure 21.13 Creation of the cover image [5].Figure 21.14 Use of stego image to envelope secret message [5].Figure 21.15 Candidate insertion into database [6].Figure 21.16 Eligible voter registration and validation [6].Figure 21.17 Voting process and winner determining algorithm [6].Figure 21.18 Mobile website interface samples [6].Figure 21.19 Blockchain structure used by the proposed system [7].Figure 21.20 Proposed system framework using blockchain [7].Figure 21.21 Voter registration page [8].Figure 21.22 Voting page [8].Figure 21.23 Hash value of the image with the secret ink [8].Figure 21.24 Login procedures of the proposed system [9].Figure 21.25 Iris image registration process [9].Figure 21.26 Iris image authentication process [9].Figure 21.27 Voter NID and SIM registration phase [10].Figure 21.28 SIM login verification phase [10].Figure 21.29 Preferred candidate vote count incrementing [10].Figure 21.30 Results outcome at the end of polling [10].Figure 21.31 Error messages during an unsuccessful login [10].Figure 21.32 Image steganography and visual cryptography system framework [11].Figure 21.33 User registration phase and password hashing [11].Figure 21.34 Voter and administrator authentication using hash and salt value [1...Figure 21.35 Administrator homepage [11].Figure 21.36 Voting system based on secret sharing authentication framework [12]...Figure 21.37 Algorithm to form shares [12].Figure 21.38 Algorithm to reconstruct shares [12].
21 Chapter 22Figure 22.1 Variants of cybersecurity.Figure 22.2 Categories of machine learning methods for cybersecurity.
List of Table
1 Chapter 1Table 1.1 Arduino function and its description.Table 1.2 Arduino programming requirement.
2 Chapter 6Table 6.1 Various definitions of trust in WSN.
3 Chapter 7Table 7.1 Summary of agriculture sensor.
4 Chapter 10Table 10.1 Datasets for deep learning in IoT.
5 Chapter 11Table 11.1 Evaluating parameters.Table 11.2 Evaluation on databases.Table 11.3 Comparative analysis: CNN methods. Note: All parameters are measured ...Table 11.4 Comparative analysis on existing methods. Note: All parameters are me...
6 Chapter 14Table 14.1 Brief descriptions of basic machine learning algorithms used in diffe...
7 Chapter 15Table 15.1 Big data tools.
8 Chapter 17Table 17.1 List of text mining algorithms.Table 17.2 Sentiment analysis algorithms and approaches.Table 17.3 Different characteristics of sentiment, emotion, and behavioral analy...
9 Chapter 19Table 19.1 Layered structure of cybersecurity.
10 Chapter 20Table 20.1 Survey of literature review.Table 20.2 Comparison of the consensus algorithms with respect to generic parame...Table 20.3 Comparison of the consensus algorithms with respect to performance-re...
11 Chapter 21Table 21.1 Comparing the existing online voting system.
Guide
1 Cover
2 Table of Contents
5 Preface
7 Index
Pages
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