Enhancing Video Steganography Security for Cross-Platform Applications: A Focus on High-Definition Formats and Streaming Environments Santanu Koley, Ankur Kumar Next Generation Systems and Secure Computing, 2025 The objective of this chapter is to create a cross-platform video steganography program that can safely conceal data inside a video container. The research has been restricted to a particular video format due to the vast and intricate nature of the field of video editing. High-definition video is worn in a format that is frequently used. It takes more than a few weeks or months to thoroughly verify the security of any system or solution. Although a system's security can be partially understood in this amount of time, many security experts think a system is secure only if it has not been compromised after a number of years. Steganography and cryptography are combined in the software solution to ensure a minimal level of security. Over the last decade, online video streaming has grown immensely in popularity. Several steganographic techniques have been suggested; however, they ignore some contextually significant features. These techniques were specifically designed for “real time video” and “streaming”. Several steganographic techniques, including some basic ones that have been reported in the literature, have been reviewed in this chapter. Additionally, a study has been done on the operation of pertinent video formats and coding techniques. Lastly, thought has been paid to the security of steganographic techniques and how steganography might be used to strengthen them.
Next-Generation Systems and Secure Computing Next Generation Systems and Secure Computing, 2025 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.
A Study on Protection of Multimedia System Contents Using a Biometric-Based Encryption Technique Pinaki Pratim Acharjya, Santanu Koley, Subhabrata Barman, Subhankar Joardar, Jayeeta Majumder Next Generation Systems and Secure Computing, 2025 A framework for protecting multimedia content based on user biometric information and a layered encryption/decryption system is proposed in this chapter. Encryption schemes that require a password are susceptible to issues with illicit key exchange. It is feasible to reduce the unauthorized use of protected content by using hardware identifiers and biometric data as keys. This is achieved by combining the symmetric and asymmetric key systems. The proposed method's computational needs and applicability are also discussed. The results of experiments involving time-measurement-related encryption and decryption are also presented. Watermarking technologies can be utilized in addition to the suggested approach to allow for the creative uses of protected multimedia data.
Applications of Artificial Intelligence and Machine Learning-Enabled Businesses: A SWOT Analysis for Human Society Santanu Koley, Shatadru Sengupta, Bipasha Biswas, Kankana Datta, Manasi Jana, Apratim Mitra Artificial Intelligence Enabled Businesses how to Develop Strategies for Innovation, 2025 Developing intelligent business solutions, efficient in process implementation and effective in customer relationship management, has been well sought after since the advent of computing into businesses. After Artificial Intelligence, with its various branches, became one of the most major subject matters for study in the world, companies across all domains have been actively involved in the pursuit of assembling business processes that have the capability to adapt newer strategies based on dynamic and heavily analytical factors such as customer feedback, market dynamics, geographical forces, logistic issues, social trends, legal parameters – to name but a few. Indeed, such adaptability arises only from intelligent reasoning with AI. Machine Learning, a branch of AI, is being used learn in unsupervised environments; Deep Learning in adapting to potential future market changes using technologies based on human neurons; Natural Language Processing is helping machines interact with human clients tirelessly and automatically without the burden of reaction thereby increasing rapport. Robotics, Expert Systems and Fuzzy Logic, find their respective uses in tasks like automatic process implementation, automated disease diagnosis and prophylaxis, and automated handling of uncertainties in logistic processes. Newer and more promising uses of AI in businesses are being evolved regularly. All this remarkable progress was originally aimed at achieving the maximum goals and raising the standards in man's life. However, it is important to bring forth the issues that must be tackled while business strategising, in order to maximise AI's achievements and minimise its nullifying effects. Citing real-life and examples, we portray the various ways AI in businesses has improved and enhanced the society in general, yet some universal human values and some universally acknowledged human traits like intuition and instinct are slowly taking an exit route. This chapter shows how blind following of AI is leading to businesses going the “safe and trendy way” at the cost of genius. The examples try to show how the adverse effects of AI may be kept at bay while making business decisions. It is argued that in a properly designed environment, that is one in which the AI that is used is tuned in to benefit from human genius rather that to oppose it, AI will possibly emerge as the greatest gift of modern technology. It is, on the other hand, quite possible that AI that blunts the human effect and undermines the human effort, will prove to be the greatest technological scourge in human history.
Machine learning and computer vision for renewable energy Acharjya, Pinaki Pratim, Koley, Santanu 1981-, Barman, Subhabrata 1974- Machine Learning and Computer Vision for Renewable Energy, 2024 As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine learning and computer vision for renewable energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems.
Preface Machine Learning and Computer Vision for Renewable Energy, 2024
A study of computer vision, deep learning, and machine learning techniques for forecasting solar power and renewable energy Jayeeta Majumder, Pinaki Pratim Acharjya, Subhabrata Barman, Santanu Koley Machine Learning and Computer Vision for Renewable Energy, 2024 Utilising renewable energy sources is becoming more popular as a way to mitigate the effects of climate change and global warming. In an effort to make renewable energy more predictable, numerous prediction techniques have been developed. The objectives of this study are best illustrated by this chapter, which aims to provide a review and analysis of machine-learning and computer vision techniques in renewable solar energy projections. In addition to machine-learning and computer vision techniques for renewable solar energy projections, this chapter also focuses on the objective to deliver an optimized academic outcome, potentially necessary for the development of new solar energy fields. This could significantly contribute to the amplified usage of solar energy, which is a sustainable and cleaner energy source.
Security enhancement in cloud and edge computing through blockchain technology Santanu Koley, Pinaki Pratim Acharjya Blockchain and Iot Based Smart Healthcare Systems, 2024 The cloud computing (CC) network is designed to tackle the security and privacy challenges of centralized cloud services by distributing computing and storage resources among networked nodes. Cloud computing, on the other hand, is restricted by the performance of linked devices, posing problems in state authorization, stats encryption, consumer privacy and more. Blockchain technology (BT) is the most popular circulated network technology right now. It is utilized in numerous fields like bitcoin, IoT, etc., to tackle the consistent issue of distributed data. The difficulties that CC networks present for security and privacy are covered in this chapter. Analysis and solutions brought to edge computing networks by BT in terms of data encryption, authentication and user privacy. In this chapter, the advantages of combining the cloud computing network with blockchain technology will be discussed. Finally, memory, workload, and latency problems for related future studies have been discussed. 
An intelligent data retrieving technique and safety measures for sustainable cloud computing Keshav Kumar, Krishan Kundan Kumar, Ritam Chatterjee, Ritam Kundu, Santanu Koley, Pinaki Pratim Acharjya Improving Security Privacy and Trust in Cloud Computing, 2024 Data refers to raw facts and figures. After processing data, the information is created. Information like facts or statistics that can be recorded, stored, and analysed can be in various forms such as text, numbers, images, audio, or video. The amount of data generated every day in the data-driven world of today makes it nearly difficult to keep it all locally. Cloud services are being used by so many people and businesses to store these massive and hefty volumes of data on cloud servers. Additionally, as the need for cloud computing grows, so does the need for data recovery methods and services. The ability to recover data and information from the backup server when the primary server is down is the primary goal of recovery services and technologies. A secondary server to hold backups for the primary cloud server will be more expensive to add than the primary server itself, which is already quite expensive and time-consuming to build. The goal of this chapter is to provide realistic, cost-effective solutions to this urgent problem.
