Journal of IoT-based Distributed Sensor Networks

Blockchain-Based Device Lifecycle Tracking: Enhancing Sustainability and Transparency

Aniket Dhumal — 2024-05-21

The rapid proliferation of electronic devices has raised concerns about Electronic waste (E-waste) management, device lifecycles, and their environmental impact. This paper discusses the ownership life cycle of the electronic device, which Blockchain Technology maintains—first-owner, second-owner and so on. We can avoid the inappropriate usage of electronic devices. In response, this research project presents a comprehensive solution for tracking the lifecycle of electronic devices using Blockchain technology. By leveraging the transparency, security, and immutability offered by Blockchain, our solution aims to enhance sustainability practices, improve user awareness, and promote responsible device disposal. This project bridges the domains of Blockchain technology and device lifecycle management, examining how Blockchain’s decentralized ledger can revolutionize the tracking of device ownership, usage history, repair records, and end-of-life disposal. Through a thorough literature review, we explore the state of existing research in Blockchain technology, device lifecycle tracking, and the intersection of these areas.

Optimizing On-Device AI: Overcoming Resource Constraints in Federated Learning for IoT

T. Aditya Sai Srinivas — 2024-08-14

Federated Learning (FL) is revolutionizing privacy in distributed IoT systems by eliminating the need to share raw data. However, it has its challenges. On the client side, attackers can tamper with data or inject false information, leading to what's known as backdoor poisoning attacks. Meanwhile, central servers can compromise data integrity and privacy by manipulating updates and extracting sensitive information from gradients. This is particularly problematic in IoT networks where user privacy is paramount. Innovative techniques like differential privacy and secure aggregation are being developed to tackle these issues and protect user data. Communication and learning convergence also pose significant hurdles due to uneven data distribution and the varied capabilities of IoT devices. To address this, new communication protocols and optimization algorithms are being implemented. Resource management is another critical area, given the limited computational power of many IoT devices. Solutions like resource-aware FL architectures and optimized AI models are emerging to ease these constraints. Additionally, advancements in AI hardware and lightweight training strategies are making deploying AI on IoT sensors more feasible. Finally, adopting standards such as ETSI Multi-access Edge Computing (MEC) and modern communication protocols is essential for the widespread deployment of FL-IoT systems, ensuring they are secure, efficient, and interoperable.

Cybersecurity in Aviation: Protecting Avionics and Passenger Data

Chikkala Kedareswari Kaivalya — 2024-08-16

Cybersecurity in aeronautics is crucial to protecting avionics systems and passenger data from growing threats. As modern aircraft increasingly rely on interconnected digital systems, securing these systems cannot be overstated. Avionics systems play a central role in ensuring the safety and efficiency of flight operations, making them prime targets for cyber-attacks. Threats such as hacking, malware, insider threats, and sophisticated tactics from evolving cyber adversaries pose significant risks to these systems. This paper underscores the necessity of implementing robust cybersecurity measures to safeguard avionics systems. Key protective strategies include:

Securing hardware and software.
Employing encrypted communication protocols.
Conducting real-time system monitoring.
Deploying advanced intrusion detection systems.

Equally important is protecting passenger data, which is often at risk of unauthorized access or breaches. To mitigate these risks, the paper advocates for using encryption, secure data storage solutions, stringent access controls, and adherence to data protection regulations. The role of international and national regulatory frameworks in establishing cybersecurity standards is critically examined. These frameworks are vital in setting the guidelines that ensure consistent and comprehensive security measures across the aviation industry. Finally, the paper explores the ongoing challenges and future directions in enhancing cybersecurity in aeronautics, emphasizing the need for continuous adaptation to emerging threats.

Data Fusion and Analysis in IoT Sensor Networks

Rashi Singh — 2024-08-28

The Internet of Things (IoT) has rapidly expanded, resulting in the development of extensive and intricate sensor networks. These networks are essential for various applications, from smart city management to environmental monitoring and industrial automation. As these networks generate enormous amounts of data, effective data fusion and analysis become crucial for deriving actionable insights and making informed decisions. This paper delves into the fundamental aspects of data fusion and analysis within IoT sensor networks, highlighting essential methods and addressing various challenges and advancements in the field. The paper provides an in-depth exploration of several data processing methods, including data aggregation, denoising, outlier identification, and missing data imputation. Numerous fusion techniques are examined, such as identity-based fusion, related feature extraction, and direct fusion, and the importance of data fusion is highlighted even further. The study also looks into how data analysis may be combined with cutting-edge cloud, fog, and edge computing technologies, emphasizing how these technologies can help address issues with IoT sensor networks and data analysis. This study attempts to give meaningful insights and a comprehensive grasp of IoT sensor data processing, fusion, and analysis by providing a thorough overview of these methodologies.

A Review of Game-Theoretic Approaches in Distributed IoT

Manas Kumar Yogi — 2024-08-28

This paper comprehensively reviews game-theoretic approaches applied to distributed Internet of Things (IoT) systems. Game theory, focusing on strategic interactions among autonomous agents, offers valuable insights into optimizing various aspects of IoT networks, including resource allocation, security, load balancing, and network formation. We explore fundamental game-theoretic concepts and their traditional applications in distributed systems, highlighting how these models address the unique challenges of IoT environments. The review covers both cooperative and non-cooperative game theories and advanced models such as differential games and evolutionary game theory. Additionally, we discuss the integration of game theory with emerging technologies like blockchain, 5G, and edge computing, as well as the application of multi-objective optimization to balance conflicting goals within IoT networks. The paper also examines limitations such as scalability, computational complexity, and real-world implementation challenges. By synthesizing existing research and identifying future directions, this review aims to advance the understanding and application of game-theoretic approaches in enhancing distributed IoT systems' performance, security, and efficiency.