Software defined network based architecture to improve security in a swarm of drones

Guerber, Christophe; Larrieu, Nicolas; Royer, Mickal

doi:10.1109/icuas.2019.8797834

Cited by 19 publications

(8 citation statements)

References 16 publications

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“…After describing different network architectures, [42] focuses on comparing an in-band, centralized SDN control architecture with a traditional MANET using the AODV routing protocol. As the paper puts special emphasis on cybersecurity, in the MANET configuration AODV is complemented with iptables for packet filtering, while in the SDN architecture the inherent SDN flow control plays the role of denying flows based on security considerations.…”

Section: B In-band Control Planementioning

confidence: 99%

Software-Defined Networking Meets Software-Defined Radio in Mobile ad hoc Networks: State of the Art and Future Directions

et al. 2022

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The aims of this survey article are to elaborate on cross-layer optimization, Software-Defined Networking (SDN) and Software-Defined Radio (SDR) as separate domains of wireless network design for which a unified view has not been adequately considered to date and present lessons learned, with a view towards the challenges associated with SDN-SDR interaction that would facilitate benefits in crosslayer optimization of mobile ad hoc networks (MANETs). We focus on MANETs because (i) they are still at the forefront of technology, and in some scenarios they are the only meaningful option for establishing communication; (ii) they expose the full potential and benefits of coexistence and interaction of SDN and SDR, in terms of optimizing key performance indicators. While SDN and SDR are mature technologies, their interaction and joint consideration have been largely overlooked. Current SDN approaches do not span the physical (PHY) and medium-access control (MAC) layers, but they rather concentrate on network-level routing and traffic flow optimization. As a result, PHY-and MAC-layer related parameters which notoriously affect key network performance metrics remain static or at best are adapted based on some heuristic or local approaches. On the other hand, the reach of SDR architectures is restricted to the PHY and MAC layers. We discuss the state of the art of cross-layer optimization, SDN and SDR, and current challenges associated with coexistence and interaction of SDN and SDR. Such an interaction would extend the span of SDN to PHY and MAC layers and lead to realizations of centralized approaches across all layers so as to control and optimize parameters, towards global network objectives. It would also create a bridge between centralized network control that is inherent in SDN and the distributed nature of MANETs, with the add-on features of flexible and fast PHY and MAC layer adaptation offered by SDR, for solid, autonomous and ultimately better network control implementations that span all layers, towards realizing and implementing the holy grail of real cross-layer optimization.INDEX TERMS Software-defined networking (SDN), software-defined radio (SDR), coexistence, mobile ad hoc networks (MANETs), cross-layer design and optimization.

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Section: B In-band Control Planementioning

confidence: 99%

Software-Defined Networking Meets Software-Defined Radio in Mobile ad hoc Networks: State of the Art and Future Directions

et al. 2022

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“…In contrast, UAVs themselves act as the data plane that acknowledges the controller's commands [195], whereas the application plane performs all decision-making and high-level operations like setting up network function virtualization. Several research works [196], [197], [198] have focused on switching and routing of UAV nodes for addressing security threats. The authors in [196] have proposed an SDN-assisted system model for providing robust relaying and data security against intentional jamming by utilizing centralized SDN-controlled UAV switches.…”

Section: Secured Uav Communications Using Sdnmentioning

confidence: 99%

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

et al. 2022

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Unmanned aerial vehicles (UAVs) have been instrumental in enabling many new applications and services, including military and rescue operations, aerial surveillance, civilian applications, precision farming, as well as providing extensive wireless network access in remote areas. They have also been used in other areas such as transmission line and oil rig monitoring, disaster recovery, etc. With their increasing payload ability and flight duration, using UAVs is a preferred choice for a multitude of upcoming wireless communication systems. However, because of their open operational nature, UAVs are highly vulnerable to severe security breaches via cyber attacks, eavesdropping on navigational and communication links, etc. Given their widespread applications, the requirement of secured UAV communications has become more and more critical since security failures can lead to detrimental consequences. Several works have examined the extent of privacy and security issues in UAV-assisted networks and introduced various mitigation techniques to address different security challenges. In this paper, a comprehensive survey is conducted that centers on the security issues related to UAV-aided networks. A descriptive taxonomy of various security intrusions on the UAV networks and commonly-used secrecy performance metrics are thoroughly reviewed. An in-depth discussion is provided on alleviating threats with proactive security techniques blended with key wireless communication technologies such as mmWave, non-orthogonal multiple access (NOMA), massive multiple-input multiple-output (MIMO), and cognitive radio. Moreover, several emerging topics like machine learning, software-defined networks, fog and edge computing, blockchain, are discussed in the context of UAV-aided secure communications.INDEX TERMS Physical layer security, unmanned aerial vehicles (UAVs), proactive mitigation techniques, secrecy metrics, emerging wireless technologies.GAURAV KUMAR PANDEY (Graduate Student Member, IEEE) received the B.Tech. degree in electrical and electronics engineering from the

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“…This approach imple-ments the flow-based and path-based security policies to secure SDN architecture compare to the OpenSec framework. Later, Guerber et al in [12] proposed to handle the wormhole, DDoS, and blackhole attacks. Despite the benefits of SDN, multi-swarm UAV communication security is a big challenge, and BC technology is a feasible solution to handle the above-mentioned issues.…”

Section: Softwarization: Techniques and Conceptsmentioning

confidence: 99%

Blockchain-Envisioned Softwarized Multi-Swarming UAVs to Tackle COVID-I9 Situations

et al. 2021

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Software defined network based architecture to improve security in a swarm of drones

Cited by 19 publications

References 16 publications

Software-Defined Networking Meets Software-Defined Radio in Mobile ad hoc Networks: State of the Art and Future Directions

Software-Defined Networking Meets Software-Defined Radio in Mobile ad hoc Networks: State of the Art and Future Directions

Security Threats and Mitigation Techniques in UAV Communications: A Comprehensive Survey

Blockchain-Envisioned Softwarized Multi-Swarming UAVs to Tackle COVID-I9 Situations

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