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    Digital Transformation- The Internet of Things- Opportunities and Challenges
    (2020) Rachana C R, Associate Professor & Head, DoS in Computer Science, PG Wing of SBRR Mahajana First Grade College (Autonomous) Pooja Bhagavat Memorial Mahajana Education Centre, K.R.S. Road, Metagalli, Mysuru-16.
    Internet of Everything is the most promising domain in the world of Connectivity which encompasses the Internet of Things. The Internet of Things refers to assigning digital identifiers to objects around us, allowing inanimate things like devices, electronic appliances, vehicles, and others to be remotely accessed by human for ease of use and convenience. The Internet of Everything brings together people, process, information and objects to make networks of Communication more meaningful and valuable than ever before, thus providing economic opportunities for businesses and individuals. IoE will help businesses achieve this goal by creating newer opportunities for greater optimization and efficiencies. The Internet of Things has taken over the business markets over the last few years. The viable benefits of IoE has encouraged and empowered Entrepreneurs through cost-cutting, efficient execution of innovative business ideas. People experience the environment around them through their senses (hearing, touch, sight, taste, and smell). In this context, IoE is an exponential proxy for sensing, understanding, and managing the world around. This paper focuses on exploring the huge competitive advantages for organizations who adopt IoT/IoE based technologies. Further, the paper also discusses the important challenges of Information Technology, specific to the Internet of Everything.
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    Data Security in Cloud Computing: A Research Perspective
    (2022-11) Rachana CR Associate Professor & Head, Department of Studies in Computer Science, First Grade College (Autonomous), PG Wing, Memorial Mahajana Education Centre, KRS Road, Metagalli, Mysuru-570016
    Security plays a very important role in the life of every living being. Today, in the ‘Technology’ engulfed businesses, data security is crucial for users and vendors alike. Cloud computing as a technology is the driving force behind all the financial transactions being completed every second across the globe. In the current context, Cloud data security is crucial and is of utmost importance. Data Security in the cloud refers to the technologies, policies, services, security controls that protect data in the cloud from loss, leakage or misuse through security breaches and unauthorized access. Securing data in the cloud is essential in e-commerce because attacks on the data can result in loss of revenue for businesses. Cyber criminals use advanced tools and techniques to steal information from the cloud servers for financial gain and other unscrupulous benefits. Securing data while it is at rest or in transit is most important for businesses. Efficient Data security tools and techniques must be applied to protect the data resident in the cloud. This paper closely examines the Issues and challenges of Data Security in Cloud Computing with reference to e-commerce.
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    Research into the world of Cloud-Virtual Reality
    (2023-10) RACHANA C R Associate Professor and Head DoS in Computer Science, PG Wing of SBRR Mahajana First Grade College, KRS Road, Metagalli, Mysuru-570016.; Praveen R, IV sem MCA, DoS in Computer Science, SBRR Mahajana First Grade College (A), PG Wing, Pooja Bhagavat Memorial Mahajana Education Centre, KRS Road, Metagalli, Mysuru.
    Virtual Reality technology has not been able to penetrate the mainstream consumer market due to restrictions on hardware and content. With the advancement of cloud computing technologies, Virtual Reality hardware and technology applications may now be supported strongly. The metaverse, cloud VR gaming, and cloud VR stimulator are just a few of the real-world applications that are now employing cloud computing in Virtual Reality. We can lower the cost of Virtual Reality technology which would begin a new era of many users to apply cloud-based technologies. With the aid of technology, it will be possible to operate from anywhere without having to transport a lot of equipment. The performance, usability, and compatibility of Virtual Reality software and hardware can be improved by cloud computing on the level of hardware and content. The VR dataset is made available for public collaboration through the Internet using a VR-Cloud server. The digital asset that represents the layout of our pedestrian bridge comprises images of all the streets, buildings, trees, and other urban amenities. In the virtual environment of the metropolitan area, where they run and stroll according to predetermined behaviour scenarios, the cars and people are created and entered. By employing cloud communication software to analyse simulations of vehicles and pedestrian crowds and to debate design ideas, users share the VR reality by connecting to the VR Cloud servers from remote devices. This research demonstrates how VR-cloud may be combined with Neuralink and NFT in the virtual world for future enhancement. This paper is a research note on cloud computing and its application using the Virtual Reality (VR) platform for the modern world with futuristic innovations.
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    Evaluating the Effectiveness of Multi-Factor Authentication (MFA) Mechanisms in Mitigating Security Risks in Cloud Services
    (2024-11-01) RACHANA C R Associate Professor and Head DoS in Computer Science, PG Wing of SBRR Mahajana First Grade College, KRS Road, Metagalli, Mysuru-570016.
    ABSTRACT Multi-factor authentication (MFA) enhances the security of cloud resources by requiring multiple forms of verification, thus mitigating risks associated with single-factor authentication vulnerabilities. As organizations increasingly adopt cloud computing for its scalability and efficiency, the accompanying security vulnerabilities have prompted the need for robust authentication solutions. MFA enhances security by requiring multiple verification methods—such as knowledge-based factors (passwords), possession-based factors (smartphones or tokens), and inherent factors (biometrics)—before granting access to sensitive data and applications. SMS-based Multi Factor Authentication is about sending a one-time code via text message, which, despite its widespread use, is susceptible to interception. App-based Multi Factor Authentication generates Time-based One-Time Passwords (TOTPs), offers a higher level of security as it is less vulnerable to interception compared to Short Messaging Service. This relies on users having access to their mobile devices, as well as the app. Hardware token-based Multi Factor Authentication employs physical devices such as USB tokens or smart cards, provides robust protection by generating one-time codes or by using cryptographic methods that are difficult to replicate or intercept. This paper compares the effectiveness of various MFA techniques—specifically SMS-based, app-based, and hardware token-based methods—in protecting cloud resources.
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    Navigating the Data Minefield: Ethical Dilemmas in the Digital Age
    (2025-10-31) RACHANA C R Associate Professor and Head DoS in Computer Science, PG Wing of SBRR Mahajana First Grade College, KRS Road, Metagalli, Mysuru-570016.
    In today’s rapidly changing digital world, data has emerged as a powerful force that influences how we live, work, and communicate. Yet, the gathering, analysis, and application of data also present numerous ethical challenges that require careful attention. Ethical data management extends beyond mere compliance with regulations; it is fundamentally about building trust and driving technological progress in a way that benefits society. In an era where data holds immense value as the currency of the digital age, the importance of data ethics continues to escalate. Achieving this requires a concerted effort from governments, organizations, and individuals to prioritize ethical principles and ensure responsible practices that uphold societal well-being. As data becomes increasingly central to modern decision-making, protecting individual privacy has evolved from a technical challenge to an ethical imperative. While policies like the General Data Protection Regulation (GDPR) offer legal boundaries, algorithmic techniques form the backbone of practical privacy preservation. This paper explores three of the most effective and ethically aligned algorithmic solutions: Differential Privacy, Federated Learning, and Synthetic Data Generation. Each method not only addresses technical concerns but also upholds key ethical values such as individual autonomy, fairness, and responsible innovation. Keywords: Ethics; Federated learning; Privacy; Synthetic Data Generation
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    Malicious Node Detection in a Wireless Sensor Network
    (2023-08-01) 1Anmol, 2Pallavi Joshi
    Wireless Sensor Networks (WSNs) are vulnerable to malicious attacks that can disrupt operations and compromise data integrity. This paper proposes a method for detecting malicious node in WSNs using the Cooja network simulator and machine learning (ML) algorithms, specifically Random Forest and SVM. The approach involves collecting a dataset of normal and malicious traffic patterns simulated in Cooja. Features are extracted from the network traffic data, including packet size, addresses, timing, frequency, and network topology. Feature selection techniques identify informative features for distinguishing between normal and malicious node. The dataset splits into testing and training sets, and the Random Forest algorithm is trained using the training set. Performance evaluation measures accuracy, precision, recall, and F1-score. Additionally to enhance detection performance further, the SVM algorithm is incorporated. Known for its ability to handle high-dimensional data and separate complex decision boundaries, SVM constructs a hyperplane for effective identification of malicious nodes in the WSN.. The optimized models are deployed in real-time WSN environments to monitor incoming traffic continuously. Alerts are generated upon detecting malicious node, enabling prompt response and mitigation. This proposed method offers an effective means of detecting malicious node, improving the security and reliability of WSNs. The results highlight the potential of machine learning algorithms, specifically SVM and Random Forest, in accurately classifying and identifying malicious patterns. By incorporating these techniques, robust security mechanisms for WSNs can be developed. Keywords: - Wireless Sensor Networks (WSNs), Malicious node detection, Cooja network simulator, Machine learning algorithms, SVM, Random Forest, Dataset collection, Feature extraction, Feature selection, Training and testing sets, Performance evaluation, Hyperparameter tuning, Real-time monitoring, Alert generation, Data integrity, Network security, Robust security mechanisms.
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    Handwriting Detection System Using Brain Net and AI Algorithm
    (2024-01-01) Pawan Mandal1, Ritu Gupta2, Dr. Naveen3, Arica Nancy John4, Priyanka Dhondiyal5, Vinay Singh6, Dr. Amandeep Kaur7, Kajal Shrivastav8
    Abstract:-Handwriting Detection System that integrates Brain-Computer Interface (BrainNet) technology with advanced Artificial Intelligence (AI) algorithms. The system leverages the power of neural networks and deep learning to accurately identify and authenticate individuals based on their handwriting patterns. The BrainNet interface allows for direct communication between the human brain and the computer system, enabling a more natural and seamless interaction for handwriting input. This innovative approach not only enhances user experience but also opens new avenues for biometric authentication by utilizing the unique neural signatures associated with handwriting. Our AI algorithm employs deep learning techniques, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to analyze and recognize intricate patterns within the handwriting data obtained through BrainNet. The model is trained on diverse datasets to ensure robust performance across various handwriting styles and individuals. The proposed system include real-time handwriting recognition, adaptability to individual writing variations, and a high level of accuracy in user authentication. The integration of BrainNet technology ensures a more intuitive and user-friendly interaction, making the system accessible to a wide range of users.the effectiveness of the Handwriting Detection System, showcasing its potential for secure authentication and document verification applications. The combination of BrainNet and AI algorithms establishes a synergistic relationship, pushing the boundaries of what is achievable in the realm of handwriting recognition and biometric authentication. The evolving landscape of human-computer interaction, offering a novel perspective on the integration of brain-machine interfaces with artificial intelligence for enhanced handwriting-related applications. The proposed system holds promise for applications in security, finance, forensics, and other domains where reliable user authentication and document verification are paramount.