Internet of Drones (IoD) is the interconnection of unmanned aerial vehicles or drones deployed for collecting sensitive data to be used in critical applications. The drones transmit the collected data to the control room (CR) for analysis, while CR sends control commands to the drone to monitor their operations. This exchange of information between the drones and CR takes place through a wireless communication channel, which is susceptible to various security risks. Therefore, it is vital to ensure the confidentiality and integrity of such information in the IoD environment. To this end, authenticated key management (AKM) protocols can be leveraged to provide reliable and secure communication. However, due to the peculiarities associated with IoD environments, it is challenging to devise a robust and resource-efficient AKM protocol. To tackle this challenge, in this article, we propose a robust AKM protocol for IoD (RAMP-IoD). RAMP-IoD uses lightweight cryptography-based authenticated encryption primitive and elliptic-curve cryptography along with a hash function to perform the AKM process. Moreover, RAMP-IoD verifies the user’s authenticity and then sets up a session key (SK) between the user and a specific drone for indecipherable communications. We verify the security of SK using the random oracle model. Scyther-based validation demonstrates that RAMP-IoD is protected against replay and man-in-the-middle attacks. Moreover, the informal analysis illustrates that RAMP-IoD is secure against various covert security attacks. Through a comparative study, we also demonstrate that RAMP-IoD provides enhanced security with low storage, communication, and computational overheads as compared to related AKM protocols.

A drone is an unmanned aerial vehicle, which is deployed in a particular Fly Zone (FZ), and used to collect crucial information from its surrounding environment to be transmitted to the server for further processing. Generally, a Mobile User (MU) is required to access the real-time information collected by the drone stationed in a specific FZ securely. Therefore, to ensure secure and reliable communications an Authenticated Key Exchange (AKE) protocol is imperative to the Internet of Drone (IoD) environment. An AKE scheme ensures only authentic MU to access IoD network resources. Upon successful authentication, MU and drone can set up a secret session key for secure communication in the future. This paper presents a novel Lightweight AKE Protocol for IoD Environment (LAKE-IoD), which first ensures the authenticity of MU and also renders session key establishment mechanism between MU and drone with the help of a server. LAKE-IoD is an AKE protocol, which is based on an authenticated encryption scheme AEGIS, hash function, and bit-wise XOR operation. Meticulous formal security verification by employing a software tool known as Scyther and informal security analysis demonstrates that LAKE-IoD is protected against different well-known active and passive security attacks. Additionally, Burrows-Abadi-Needham logic is applied to verify the logical completeness of LAKE-IoD. Furthermore, a comparison of LAKE-IoD with the related schemes shows that LAKE-IoD incurs less communication, computational and storage overhead.

In response to the rapid advancements in facial manipulation technologies, particularly facilitated by Generative Adversarial Networks (GANs) and Stable Diffusion-based methods, this paper explores the critical issue of deepfake content creation. The increasing accessibility of these tools necessitates robust detection methods to curb potential misuse. In this context, this paper investigates the potential of Vision Transformers (ViTs) for effective deepfake image detection, leveraging their capacity to extract global features. Objective: The primary goal of this study is to assess the viability of ViTs in detecting multiclass deepfake images compared to traditional Convolutional Neural Network (CNN)-based models. By framing the deepfake problem as a multiclass task, this research introduces a novel approach, considering the challenges posed by Stable Diffusion and StyleGAN2. The objective is to enhance understanding and efficacy in detecting manipulated content within a multiclass context. Novelty: This research distinguishes itself by approaching the deepfake detection problem as a multiclass task, introducing new challenges associated with Stable Diffusion and StyleGAN2. The study pioneers the exploration of ViTs in this domain, emphasizing their potential to extract global features for enhanced detection accuracy. The novelty lies in addressing the evolving landscape of deepfake creation and manipulation. Results and Conclusion: Through extensive experiments, the proposed method exhibits high effectiveness, achieving impressive detection accuracy, precision, and recall, and an F1 rate of 99.90% on a multiclass-prepared dataset. The results underscore the significant potential of ViTs in contributing to a more secure digital landscape by robustly addressing the challenges posed by deepfake content, particularly in the presence of Stable Diffusion and StyleGAN2. The proposed model outperformed when compared with state-of-the-art CNN-based models, i.e., ResNet-50 and VGG-16.

With the widespread utilization of Internet-enabled smart devices (SDs), the Industrial Internet of Things (IIoT) has become prevalent in recent years. SDs exchange information through the open Internet, which creates security and privacy concerns for the exchanged information. To address these concerns, various solutions exist in the literature which, because of high computational and communication overheads, are not appropriate for the resource constricted IIoT environment. This paper proposes a resource-efficient authentication protocol for the IIoT, called REAP-IIoT, which employs a Lightweight Cryptography (LWC)-based Authenticated Encryption with Associative Data (AEAD) primitive AEGIS along with hash function. LWC-based AEAD primitives are suitable for resource constraint SDs because they require fewer computational resources. Moreover, REAP-IIoT renders the privacy-preserving user authentication functionality and establishes a Session Key (SK) between SDs deployed in the IIoT environment and users. Both user and SD utilize the established SK for encrypted communication. The security of SK, established during the Authentication and Key Exchange (AKE) process of REAP-IIoT, is validated through the broadly accepted random or real model. Besides, Scyther-based security verification is conducted to illustrate that REAP-IIoT is secure and can protect the man-in-the-middle and replay attacks. Additionally, the informal security analysis is carried out to show that REAP-IIoT is protected against various covert security risks. A thorough comparison reveals that REAP-IIoT renders enhanced security characteristics apart from its low communication, storage, and computational overheads than the relevant AKE protocols.

Internet of Drones (IoD) offers several advantages, such as enabling ground communications in areas with connectivity limitations due to physical obstacles. However, IoD also introduces new security vulnerabilities. For instance, an attacker could launch a drone capture attack to obtain confidential credentials and inject counterfeit information into the IoD network, jeopardizing its smooth operation. In such scenarios, authentication plays a crucial role in ensuring security. Unfortunately, the existing authentication frameworks are insufficient to protect against attacks in the IoD environment. In this article, we propose a secure and anonymous authentication framework called SAAF-IoD for the IoD. SAAF-IoD utilizes a chaotic map in combination with symmetric encryption and hash functions. It allows external users of the IoD network to establish a session key with the deployed drone by performing mutual authentication with the Ground-Station Server (GS). The proposed SAAF-IoD framework provides resistance against privileged insider attacks and GS bypass attacks. We validate the resilience of SAAF-IoD against various security attacks through both formal and informal analyses. Furthermore, we compare the efficiency of the proposed framework with a benchmark scheme in terms of communication and computational costs. Our results demonstrate that SAAF-IoD requires fewer resources than the relevant schemes while offering enhanced security features.