KATE: Kalman Trust Estimator for Internet of Drones

Bhargava, Arpita; Verma, Shekhar

doi:10.1016/j.comcom.2020.04.027

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…Bhargava et al proposed a Kalman trust estimator (KATE) in ref. [17]. KATE checks drones' misbehaviour by combining direct and indirect trust values.…”

Section: Related Workmentioning

confidence: 99%

FUBA: A fuzzy‐based unmanned aerial vehicle behaviour analytics for trust management in flying ad‐hoc networks

Benfriha,

Labraoui,

Bensaid

et al. 2023

IET Networks

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Flying Ad‐Hoc Network (FANET) is a promising ad hoc networking paradigm that can offer new added value services in military and civilian applications. Typically, it incorporates a group of Unmanned Aerial Vehicles (UAVs), known as drones that collaborate and cooperate to accomplish several missions without human intervention. However, UAV communications are prone to various attacks and detecting malicious nodes is essential for efficient FANET operation. Trust management is an effective method that plays a significant role in the prediction and recognition of intrusions in FANETs. Specifically, evaluating node behaviour remains an important issue in this domain. For this purpose, the authors suggest using fuzzy logic, one of the most commonly used methods for trust computation, which classifies nodes based on multiple criteria to handle complex environments. In addition, the Received Signal Strength Indication (RSSI) is an important parameter that can be used in fuzzy logic to evaluate a drone's behaviour. However, in outdoor flying networks, the RSSI can be seriously influenced by the humidity of the air, which can dramatically impact the accuracy of the trust results. FUBA, a fuzzy‐based UAV behaviour analytics is presented for trust management in FANETs. By considering humidity as a new parameter, FUBA can identify insider threats and increase the overall network's trustworthiness under bad weather conditions. It is capable of performing well in outdoor flying networks. The simulation results indicate that the proposed model significantly outperforms FNDN and UNION in terms of the average end‐to‐end delay and the false positive ratio.

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“…Bhargava et al proposed a Kalman trust estimator (KATE) in ref. [17]. KATE checks drones' misbehaviour by combining direct and indirect trust values.…”

Section: Related Workmentioning

confidence: 99%

FUBA: A fuzzy‐based unmanned aerial vehicle behaviour analytics for trust management in flying ad‐hoc networks

Benfriha,

Labraoui,

Bensaid

et al. 2023

IET Networks

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“…The use of UAVs seems a straightforward consideration, and indeed, there is a host of literature and surveys [49] on the use of UAVs as mobile nodes in communication networks [50], or as parts of dynamic networks [51]. Practitioners in the field have identified UAVs, used as mobile sensing devices, as having great potential when it comes to providing communication support [35,52] and mobile communication infrastructure [9,18], such as a drone-based (mobile) wireless sensor network (WSN) [53] or a wireless local area network (WLAN) in which communication is realized node to node (N2N) using ad hoc [54] routing [55] to exchange messages between nodes. Examples for the use of dronebased wireless sensors networks (WSN) [56][57][58] are, e.g., healthcare and environmental monitoring [11,[59][60][61]) as well as reconnaissance in the aftermath of a disaster [10], and general applications where the topology of the network is dynamic and adaptive [62].…”

Section: Uavs As Nodes In Mobile Networkmentioning

confidence: 99%

Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms

Husain

Zaabi

Hildmann

et al. 2022

Drones

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With the growing reliability of modern ad hoc networks, it is encouraging to analyze the potential involvement of autonomous ad hoc agents in critical situations where human involvement could be perilous. One such critical scenario is the Search and Rescue effort in the event of a disaster, in which timely discovery and help deployment is of utmost importance. This paper demonstrates the applicability of a bio-inspired technique, namely Ant Algorithms (AA), in optimizing the search time for a route or path to a trapped victim, followed by the application of Dijkstra’s algorithm in the rescue phase. The inherent exploratory nature of AA is put to use for faster mapping and coverage of the unknown search space. Four different AA are implemented, with different effects of the pheromone in play. An inverted AA, with repulsive pheromones, was found to be the best fit for this particular application. After considerable exploration, upon discovery of the victim, the autonomous agents further facilitate the rescue process by forming a relay network, using the already deployed resources. Hence, the paper discusses a detailed decision-making model of the swarm, segmented into two primary phases that are responsible for the search and rescue, respectively. Different aspects of the performance of the agent swarm are analyzed as a function of the spatial dimensions, the complexity of the search space, the deployed search group size, and the signal permeability of the obstacles in the area.

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“…Recently, UAVs are going to enable multi‐billion dollars' worth of real‐world market opportunities in the following years due to the growing applicability in different areas such as the military field, 1 product delivery, 2 intelligent transportation, 3 wireless coverage, 4 smart agriculture, 5 disaster management, 6 intelligent on‐board healthcare 7 and many more in commercial sectors. UAVs can fly autonomously in the sky and collaborate with existing network capabilities and perform all types of needful operations.…”

Section: Introductionmentioning

confidence: 99%

LoCaL: Link‐optimized cone‐assisted location routing in flying ad hoc networks

Kumar

Raw

Bansal

2022

Int J Communication

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Summary Recently, flying ad hoc networks (FANETs) has become a core research area in wireless networks that involves multiple unmanned aerial vehicles (UAVs). It is widely used in modern warfare for surveillance, monitoring and reconnaissance. The routing in FANETs poses a more significant challenge due to limited energy and frequent link disconnection between the UAVs. Consequently, an effective route is always required to ensure data transmission between UAVs. Therefore, this research proposes a link‐optimized cone‐assisted location (LoCaL) routing protocol for FANETs. The main goal of the proposed LoCaL is to enhance the link duration between the UAVs in which a source selects a forwarding UAV from a given set of neighbours by estimating the residual energy, link duration time and safety degree parameters. Proposed LoCaL provides better stability and less frequent route breaks between source and destination. Further, the mathematical formulation of the proposed approach is presented through the utility function to enhance the route stability by selecting all those relay UAVs in the cone‐shaped request zone, which reduces the routing overhead in discovering the route. Finally, the performance of the LoCaL has been presented through key indicators such as energy consumption, routing overhead, message delivery ratio, network lifetime and delay compared to the existing approaches.

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KATE: Kalman Trust Estimator for Internet of Drones

Cited by 10 publications

References 16 publications

FUBA: A fuzzy‐based unmanned aerial vehicle behaviour analytics for trust management in flying ad‐hoc networks

FUBA: A fuzzy‐based unmanned aerial vehicle behaviour analytics for trust management in flying ad‐hoc networks

Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms

LoCaL: Link‐optimized cone‐assisted location routing in flying ad hoc networks

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