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Next-Generation Systems and Secure Computing is essential for anyone looking to stay ahead in the rapidly evolving landscape of technology. It offers crucial insights into advanced computing models and their security implications, equipping readers with the knowledge needed to navigate the complex challenges of today's digital world.
The development of technology in recent years has produced a number of scientific advancements in sectors like computer science. The advent of new computing models has been one particular development within this sector. New paradigms are always being invented, greatly expanding cloud computing technology. Fog, edge, and serverless computing are examples of these revolutionary advanced technologies. Nevertheless, these new approaches create new security difficulties and are forcing experts to reassess their current security procedures. Devices for edge computing aren't designed with the same IT hardware protocols in mind. There are several application cases for edge computing and the Internet of Things (IoT) in remote locations. Yet, cybersecurity settings and software upgrades are commonly disregarded when it comes to preventing cybercrime and guaranteeing data privacy.
Next-Generation Systems and Secure Computing compiles cutting-edge studies on the development of cutting-edge computing technologies and their role in enhancing current security practices. The book will highlight topics like fault tolerance, federated cloud security, and serverless computing, as well as security issues surrounding edge computing in this context, offering a thorough discussion of the guiding principles, operating procedures, applications, and unexplored areas of study. Next-Generation Systems and Secure Computing is a one-stop resource for learning about the technology, procedures, and individuals involved in next-generation security and computing.
Subhabrata Barman is an assistant professor in the Department of Computer Science and Engineering, Haldia Institute of Technology, West Bengal, India, with over 19 years of teaching and research experience. He has edited a number of internationally published books and journals. Additionally, he is a professional member of the Computer Society of India, the Institute for Electrical and Electronics Engineers, the International Association of Computer Science and Information Technology, and the International Association of Engineers. His research interests include wireless networks, computational intelligence, remote sensing and geoinformatics, precision agriculture, and parallel and grid computing.
Santanu Koley, PhD, is a professor in the Computer Science and Engineering Department at Haldia Institute of Technology, West Bengal, India, with more than 19 years of teaching experience and more than eighteen years of research experience. He has published over 50 research publications in numerous national and international journals, conferences, books, and book chapters. His main areas of research include machine learning, cloud computing, digital image processing, and artificial intelligence.
Subhankar Joardar, PhD, is a professor and head of the Department of Computer Science and Engineering, Haldia Institute of Technology, India. He has published over 20 technical papers in referred journals and conferences. Additionally, he has served as an organizing chair and program committee member for several international conferences and is a member of the Computer Society of India. His current research interests include swarm intelligence, routing in mobile ad hoc networks, and machine learning.
Sunanda Jana1, Swarnajit Bhattacharya1, Mrinmoy Sen1*, Abhinandan Khan2, Arnab Kumar Maji3 and Rajat Kumar Pal2
1Haldia Institute of Technology, WB, India
2University of Calcutta, Kolkata, India
3North-Eastern Hill University, Meghalaya, India
In this era of digital communication and multimedia content sharing, ensuring the security and privacy of sensitive video data is of utmost importance. Symmetric key encryption is a widely used technique for securing video content; however, the generation of secure and unpredictable encryption keys remains a challenge. This study proposes a novel approach that employs Sudoku puzzles as a mechanism for generating symmetric keys. Then, by passing the key through fernet module, the Sudoku-Fernet cipher key was extracted for video encryption. The Sudoku puzzle's inherent properties of uniqueness, complexity, and nonlinearity make it an ideal candidate for key generation. The proposed method combines the strength of the Giant Sudoku instance of size 25 × 25 with a cryptographic fernet module to enhance the security of video encryption systems, offering an innovative solution to protect sensitive video content without affecting cost and time.
Keywords: Symmetric key, fernet, sudoku-fernet cipher key, video encryption, security
Sudoku puzzle [1] is a popular logic-based number-placement game that has gained worldwide popularity. Its structure consists of an n × n square grid, containing some clues as preassigned, forming a Sudoku puzzle, where n is an integer and Vn is an integer. Thus, minigrids are formed with size Vn × Vn. In each minigrid, each integer between 1 and n appears only once. Standard Sudoku consists of a 9 × 9 grid divided into nine 3 × 3 subgrids. The goal is to fill in the empty cells with digits from 1 to 9, ensuring that each row, column, and subgrid contains every digit exactly once. Sudoku puzzles can be of various sizes and configurations beyond the classic 9 × 9 grid. Some common Sudoku types are based on different grid sizes [10]:
3D Sudoku [11] is a variation of the classic Sudoku puzzle that adds an extra dimension to the game. Instead of the usual 9 × 9 grid, 3D Sudoku is played on a 9 × 9 × 9 grid, which means that it has nine 3 × 3 × 3 cubes. The objective is the same as that of traditional Sudoku: fill in the grid so that every row, column, and 3 × 3 × 3 cube contains the numbers 1 through 9 with no repetition.
Figure 1.1 shows a 25 × 25 Sudoku instance where clues are highlighted in red, whereas Figure 1.2 provides a solution to that Sudoku instance. Although Sudoku puzzles are primarily enjoyed as recreational games, they have also found interesting applications in various fields. One such application is video encryption, in which Sudoku-based algorithms can be utilized to secure video content.
Figure 1.1 An instance of a 2D Sudoku puzzle of size 25 × 25 with clues highlighted in red.
Figure 1.2 A solution instance of 2D Sudoku puzzle of size 25 × 25 given in Figure 1.1.
A Sudoku instance can be solved in multiple ways because we can start from any given clue present in the minigrids. However, in contemporary literature, no technique has been described to determine the number of starting cells. The starting cell becomes fascinating to a mathematician only if it follows a minimal route, and the removal or inclusion of a single clue may generate another Sudoku instance for which other new solutions may exist. Moreover, no current technique can determine the minimum number of clues to be provided to the cells. This accounts for the maximum number of variations in Sudoku puzzle instances. The authors in [8] stated that a minimum of 17 clues are needed to ensure that a Sudoku instance, if solvable, has only one unique solution. Therefore, any Sudoku puzzle instance with fewer than 17 givens, if valid, must have more than one solution. However, a valid Sudoku instance may have multiple correct solutions even if the instance includes more than 17 clues. Several techniques exist for the solving a Sudoku puzzle, which differ depending on the difficulty level of the puzzle. According to contemporary literature, the level of difficulty of a Sudoku puzzle is governed by its number of clues [9]. The relationship between the difficulty level of a Sudoku puzzle and the number of clues presented is shown in Table 1.1.
In addition to the number of clues, the position of the empty cells also influences the difficulty level. For any two Sudoku puzzle instances with the same number of clues, the puzzle where the clues are present in clusters/groups is assigned a higher difficulty level than the puzzle with an even distribution of clues. According to the row and column constraints presented in [9], the minimum possible number of clues, in each row and column for different difficulty levels is set as given in Table 1.2.
Sudoku can also be used for video encryption. Sudoku puzzles have a unique property that can be used to scramble and encrypt data. Sudoku puzzles can be used to create a 9 × 9 matrix that can be used to map the pixels of a video frame to new positions. This scrambling process makes it difficult for unauthorized users to decrypt a video without the correct key.
Table 1.1 Definition of the Sudoku instance difficulty level according to the number of given clues.
Table 1.2 Minimum possible number of clues, in each row and column of a Sudoku instance for different levels of difficulty.
There are several different ways to use Sudoku puzzles for video encryption. A common method is to use the Sudoku matrix to create a permutation function. This function can then be applied to the pixels of a video frame to scramble them. Another common method is to use a Sudoku matrix to create a substitution function. This function can...
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