Review of Security Gaps in Optimal Path Selection in Unmanned Aerial Vehicles Communication

Kayalvizhi, M.; Ramamoorthy, S.

doi:10.1007/978-981-16-9012-9_36

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Integrity ensures data consistency, accuracy, and reliability. Availability ensures that access to data will be easy for authorized parties [78]. The security protocols are one of the methods that implement mentioned rules.…”

Section: Denial Of Service (Dos) Attackmentioning

confidence: 99%

Key Agreement and Authentication Protocols in the Internet of Things: A Survey

Szymoniak

Kesar

2022

Applied Sciences

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The rapid development of Internet of things (IoT) technology has made the IoT applicable in many areas of life and has contributed to the IoT’s improvement. IoT devices are equipped with various sensors that enable them to perform the tasks they were designed for. The use of such devices is associated with securing communication between devices and users. The key stages of communication are the processes of authentication and the process of agreeing on session keys because they are the basis of the subsequent communication phases. The specially designed security protocols are used to secure communication. These protocols define the course of communication and cryptographic techniques employed for securing. In this article, we have reviewed the latest communication protocols designed to secure authentication processes and agree on session keys in IoT environments. We analyzed the proposed protocols’ security level, vulnerability, and computational and communication costs. We showed our observations, describing the requirements that a secure protocol should meet.

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Section: Denial Of Service (Dos) Attackmentioning

confidence: 99%

Key Agreement and Authentication Protocols in the Internet of Things: A Survey

Szymoniak

Kesar

2022

Applied Sciences

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“…In this context, on one hand, blockchain is emerging as a promising technology to provide the confidentiality and integrity of exchanged data between UAV devices, and generate trust between the involved UAVs, without the need for a trusted third entity [4,5]. On the other hand, collaborative/distributed Deep Learning (DL), such as Federated Learning (FL), emerges also to not only optimize UAV network management and thus meeting the requirement of their emerged applications, but also to ensure the UAVs' privacy by keeping the needed data (i.e., sensed data) on UAV devices [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Multi-Constrained and Edge-Enabled Selection of UAV Participants in Federated Learning Process

et al. 2022

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Unmanned aerial vehicles (UAVs) have gained increasing attention in boosting the performance of conventional networks due to their small size, high efficiency, low cost, and autonomously nature. The amalgamation of UAVs with both distributed/collaborative Deep Learning (DL) algorithms, such as Federated Learning (FL), and Blockchain technology have ushered in a new paradigm of Secure Multi-Access Edge Computing (S-MEC). Indeed, FL enables UAV devices to leverage their sensed data to build local DL models. The latter are then sent to a central node, e.g., S-MEC node, for aggregation, in order to generate a global DL model. Therefore, FL enables UAV devices to collaborate during several FL rounds in generating a learning model, while avoiding to share their local data, and thus ensuring UAVs’ privacy. However, UAV devices are usually limited in terms of resources such as battery, memory, and CPU. Some of the UAV devices may not be able to build a local learning models due to their resources capacity. Hence, there is a great need to select the adequate UAVs at each FL round, that are able to build a local DL model based on their resource capacities. In this paper, we design a novel and S-MEC-enabled framework that optimizes the selection of UAV participants at each FL training round, named FedSel. FedSel considers the available UAVs along with their resource capacities, in terms of energy, CPU, and memory, to determine which UAV device is able to participant in the FL process. Thus, we formulate the UAV selection problem as an Integer Linear Program, which considers the aforementioned constraints. We also prove that this problem is NP-hard, and suggest a Tabu Search (TS) metaheuristic-based approach to resolve it. Moreover, FedSel is built on top of blockchain technology, in order to ensure a secure selection of UAV participants, and hence building reliable FL-based models. Simulation results validate the efficiency of our FedSel scheme in balancing computational load among available UAVs and optimizing the UAV selection process.

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Key Distribution and Authentication Protocols in Wireless Sensor Networks: A Survey

Szymoniak

2024

ACM Comput. Surv.

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We use sensor technologies in many areas of everyday life. We use sensors to check and study various phenomena and to improve our lives. Hence, the sensors are used in medicine, industry, sports and many other aspects of everyday life. Interconnected sensors and other wireless devices and servers form Wireless Sensor Networks. During communication between the nodes of such networks, we often send private and sensitive. These data should be properly secured. Securing communication in a Wireless Sensor Network mainly affects the reconciliation and distribution of session keys and authentication. Specially designed protocols must protect both methods. In turn, the protocols may be exposed to dishonest users of such networks and thus exposed to various attacks (for example, replay attacks and smart card stolen attacks). This article surveys the existing session key negotiation, distribution and authentication protocols. We will explain the security problems and threats to which the sensor networks are exposed. We will discuss the security levels implemented by the protocols currently used in sensor networks. We will analyze the challenges and requirements faced by the newly designed protocols.

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Review of Security Gaps in Optimal Path Selection in Unmanned Aerial Vehicles Communication

Cited by 3 publications

References 13 publications

Key Agreement and Authentication Protocols in the Internet of Things: A Survey

Key Agreement and Authentication Protocols in the Internet of Things: A Survey

Multi-Constrained and Edge-Enabled Selection of UAV Participants in Federated Learning Process

Key Distribution and Authentication Protocols in Wireless Sensor Networks: A Survey

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