An efficient cyber defense framework for UAV-Edge computing network

Sedjelmaci, Hichem; Boudguiga, Aymen; Jemaa, Inès Ben; Senouci, Sidi‐Mohammed

doi:10.1016/j.adhoc.2019.101970

Cited by 18 publications

(6 citation statements)

References 27 publications

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“…The joint optimization considered the trajectory optimization, computing and communication resources allocated at the UAV, and task offloading decisions made at the IoT devices. UAV-assisted MECs for solving task offloading were discussed in detail by using different techniques [68][69][70][71][72][73][74].…”

Section: Uav Computingmentioning

confidence: 99%

Computing in the Sky: A Survey on Intelligent Ubiquitous Computing for UAV-Assisted 6G Networks and Industry 4.0/5.0

Alsamhi

Shvetsov

Kumar

et al. 2022

Drones

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Unmanned Aerial Vehicles (UAVs) are increasingly being used in a high-computation paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless communication networks. These networks have an avenue for generating a considerable amount of heterogeneous data by the expanding number of Internet of Things (IoT) devices in smart environments. However, storing and processing massive data with limited computational capability and energy availability at local nodes in the IoT network has been a significant difficulty, mainly when deploying Artificial Intelligence (AI) techniques to extract discriminatory information from the massive amount of data for different tasks.Therefore, Mobile Edge Computing (MEC) has evolved as a promising computing paradigm leveraged with efficient technology to improve the quality of services of edge devices and network performance better than cloud computing networks, addressing challenging problems of latency and computation-intensive offloading in a UAV-assisted framework. This paper provides a comprehensive review of intelligent UAV computing technology to enable 6G networks over smart environments. We highlight the utility of UAV computing and the critical role of Federated Learning (FL) in meeting the challenges related to energy, security, task offloading, and latency of IoT data in smart environments. We present the reader with an insight into UAV computing, advantages, applications, and challenges that can provide helpful guidance for future research.

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Section: Uav Computingmentioning

confidence: 99%

Computing in the Sky: A Survey on Intelligent Ubiquitous Computing for UAV-Assisted 6G Networks and Industry 4.0/5.0

Alsamhi

Shvetsov

Kumar

et al. 2022

Drones

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show abstract

“…The security was dealt with through a different prism in [86], where a reputation-based scheme was used. First, the UAVs were considered as mobile devices and part of a vehicular ecosystem to collect measurements from the environment.…”

Section: E Its Scenariosmentioning

confidence: 99%

Secure UAV-Aided Mobile Edge Computing for IoT: A Review

et al. 2022

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As the Internet of Things (IoT) ecosystem evolves, innovative applications with stringent demands with respect to latency will emerge. To handle computation-intensive tasks in a timely manner, data offloading to Mobile Edge Computing (MEC) servers has been suggested. On the other hand, prospective IoT networks are expected to include Unmanned Aerial Vehicles (UAVs) to enhance coverage and connectivity, while retaining reliable communication links with ground nodes in urban, suburban, and rural terrain. Nevertheless, the evolution of UAV-aided MEC-enabled IoT presupposes the mitigation of security threats through the implementation of efficient and robust countermeasures. As UAVs inherently have certain limitations in terms of energy, computational, and memory resources, designing lightweight security solutions is required. This paper provides an overview of the UAV-aided MEC-enabled IoT and a detailed presentation of use cases and application scenarios, where security is of utmost importance. Subsequently, up-to-date research works on security solutions for the UAV-aided MEC-enabled IoT are comprehensively presented. To this end, the adoption of information-theoretic techniques that ensure adequate Physical-Layer Security (PLS) is discussed along with sophisticated security approaches based on emerging technologies, such as Blockchain and Machine Learning (ML). In addition, research studies on software-and hardware-based methods for the identification and authentication of network nodes are presented. Finally, this paper provides future perspectives in this research domain, stimulating further work.INDEX TERMS Blockchain, Internet of Things (IoT), Machine Learning (ML), Mobile Edge Computing (MEC), Physical-Layer Security (PLS), Unmanned Aerial Vehicle (UAV).

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“…Although MEC can provide better security than cloud computing owing to the short distance between users and the MEC server, the features of aerial MEC make it vulnerable to potential attacks. For example, the public and openaccess channels that UAVs use for communications may cause passive eavesdropping, active interfering, information leakage or manipulations, and denial of service (DoS) attacks, etc., while the detection of malicious nodes is difficult due to the dynamic network topology [183]. Existing solutions, such as the physical-layer security mechanisms and NFV/SDN-based security orchestration, have tried to address the eavesdropping and DoS attacks.…”

Section: Security Protection and Privacy Preservingmentioning

confidence: 99%