Unmanned Aerial Vehicles (UAVs) are becoming very popular nowadays due to their wide applicability in areas ranging from package delivery systems to automated military applications. Nevertheless, communication security between a UAV and its base station (BS) is critical for completing its task without leaking sensitive information either to the adversaries or to unauthenticated users. UAVs are especially vulnerable to physical and node tampering attacks. Further, since UAV devices are generally equipped with small batteries and limited memory storage, lightweight security techniques are best suited for them. Addressing these issues, a lightweight mutual authentication scheme based on Physical Unclonable Function (PUF) for UAV-BS authentication is presented in this paper. We present a formal security analysis as well as old-fashioned cryptanalysis to show that our protocol provides various security features such as mutual authentication, user anonymity, etc. and is resilient against many security attacks such as masquerade, replay, node tampering attacks, etc. We also compare the performance of our protocol with state-of-the-art UAV-BS authentication protocols, based on computation, communication and memory storage cost.

Electric vehicles (EVs) have been slowly replacing conventional fuel based vehicles since the last decade. EVs are not only environment-friendly but when used in conjunction with a smart grid, also open up new possibilities and a Vehicle-Smart Grid ecosystem, commonly called V2G can be achieved. This would not only encourage people to switch to environment friendly EVs or Plug-in Hybrid Electric Vehicles (PHEVs), but also positively aid in load management on the power grid, and present new economic benefits to all the entities involved in such an ecosystem. Nonetheless, privacy and security remains a serious concern of smart grids. The devices used in V2G are tiny, inexpensive, and resource constrained, which renders them susceptible to multiple attacks. Any protocol designed for V2G systems must be secure, lightweight, and must protect the privacy of the vehicle owner. Since EVs and charging stations are generally not guarded by people, physical security is also a must. To tackle these issues, we propose Physical Unclonable Functions (PUF) based Secure User Key-Exchange Authentication (SUKA) protocol for V2G systems. The proposed protocol uses PUFs to achieve a two-step mutual authentication between an EV and the Grid Server. It is lightweight, secure, and privacy preserving. Simulations show that the proposed protocol performs better and provides more security features than state-of-the-art V2G authentication protocols. The security of the proposed protocol is shown using a formal security model and analysis.

Traditional multimedia experiences are undergoing a transformation as generative AI integration fosters enhanced creative workflows, streamlines content creation processes, and unlocks the potential for entirely new forms of multimedia storytelling. It has potential to generate captivating visuals to accompany a documentary based solely on historical text descriptions, or creating personalized and interactive multimedia experiences tailored to individual user preferences. From the high-resolution cameras in our smartphones to the immersive experiences offered by the latest technologies, the impact of generative imaging undeniable. This study delves into the burgeoning field of generative AI, with a focus on its revolutionary impact on image generation. It explores the background of traditional imaging in consumer electronics and the motivations for integrating AI, leading to enhanced capabilities in various applications. The research critically examines current advancements in state-of-the-art technologies like DALL-E 2, Craiyon, Stable Diffusion, Imagen, Jasper, NightCafe, and Deep AI, assessing their performance on parameters such as image quality, diversity, and efficiency. It also addresses the limitations and ethical challenges posed by this integration, balancing creative autonomy with AI automation. The novelty of this work lies in its comprehensive analysis and comparison of these AI systems, providing insightful results that highlight both their strengths and areas for improvement. The conclusion underscores the transformative potential of generative AI in image generation, paving the way for future research and development to further enhance and refine these technologies. This article serves as a critical guide for understanding the current landscape and future prospects of AI-driven image creation, offering a glimpse into the evolving synergy between human creativity and artificial intelligence.

Unmanned Aerial Vehicles (UAVs) domain has seen rapid developments in recent years. UAVs have been deployed for many applications and missions like data transmission, cellular service provisioning, and computational offloading tasks etc. Yet, UAV deployment is still limited, partially owing to the security challenges it poses. UAVs are particularly vulnerable to physical capture, cloning attacks, eavesdropping, and man in the middle attacks. To address some of these security problems, this paper develops an authentication protocol for use in UAV swarms. To ensure physical security and rapid authentication, the proposed protocol uses Physical Unclonable Functions (PUFs). The protocol achieves high scalability compared to the state of the art by authenticating multiple devices at once. The proposed protocol supports dynamic topologies and multi-hop communication by using spanning tree-based traversal. It is also resistant to mobility, device tampering attack, etc., and its improvements are achieved at significantly lower communication and communication cost as compared to state-of-the-art protocols.

In recent years, the rapid development of wireless communication-based technologies has been particularly prominent in the context of Unmanned Aerial Vehicle (UAV) applications. However, despite significant progress, the realization of the full potential of UAV-based applications is hindered by inherent security vulnerabilities, including the susceptibility of communication between drones and base stations to intrusion. This research addresses critical research gaps by proposing a novel authentication method that leverages Shamir's secret sharing. Unlike existing authentication protocols, which often rely on Physically Unclonable Functions (PUFs) that assume resistance to noise and theoretical ideals, our approach acknowledges the potential errors in PUF responses. This accommodation allows for the successful authentication of legitimate UAVs, even in the presence of external environmental factors introducing noise in PUFs. To evaluate the effectiveness of our proposed method, extensive simulations were conducted using NodeMCU and Raspberry Pi devices. We show that our approach outclasses other existing methods across multiple dimensions with communication cost of mere $450 \mu s$ on NodeMCU. Additionally, it incurs lower communication costs (1600 bits) and storage costs (352 bits), showcasing superior efficiency. Moreover, it maintains robust security and scalability while consuming reasonable energy levels, making it a comprehensive solution for UAV-based applications.