Security Threats in Flying Ad Hoc Network (FANET)

Lateef, Safia; Rizwan, Muhammad; Hassan, Muhammad Abul

doi:10.1007/978-3-030-97113-7_5

Cited by 10 publications

(5 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Signals are identified by measuring the carrier-to-noise ratio and absolute power. A conviction model that limits misleading bits of hearsay and coordinates various sources is executed utilizing beta and Weibull disseminations 24,25 . As indicated by reproduction results, GPS parody signs can be identified and dropped with almost 100% high exactness and low correspondence cost.…”

Section: Secure Aware Routing Algorithm For Fanetmentioning

confidence: 99%

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Chandrasekar,

Shanmugavalli,

Mahesh

et al. 2024

Sci Rep

View full text Add to dashboard Cite

In wireless networking, the security of flying ad hoc networks (FANETs) is a major issue, and the use of drones is growing every day. A distributed network is created by a drone network in which nodes can enter and exit the network at any time. Because malicious nodes generate bogus identifiers, FANET is unstable. In this research study, we proposed a threat detection method for detecting malicious nodes in the network. The proposed method is found to be most effective compared to other methods. Malicious nodes fill the network with false information, thereby reducing network performance. The secure ad hoc on-demand distance vector (AODV) that has been suggested algorithm is used for detecting and isolating a malicious node in FANET. In addition, because temporary flying nodes are vulnerable to attacks, trust models based on direct or indirect reliability similar to trusted neighbors have been incorporated to overcome the vulnerability of malicious/selfish harassment. A node belonging to the malicious node class is disconnected from the network and is not used to forward or forward another message. The FANET security performance is measured by throughput, packet loss and routing overhead with the conventional algorithms of AODV (TAODV) and reliable AODV secure AODV power consumption decreased by 16.5%, efficiency increased by 7.4%, and packet delivery rate decreased by 9.1% when compared to the second ranking method. Reduced packet losses and routing expenses by 9.4%. In general, the results demonstrate that, in terms of energy consumption, throughput, delivered packet rate, the number of lost packets, and routing overhead, the proposed secure AODV algorithm performs better than the most recent, cutting-edge algorithms.

show abstract

Section: Secure Aware Routing Algorithm For Fanetmentioning

confidence: 99%

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Chandrasekar,

Shanmugavalli,

Mahesh

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…e) Replay attacks: In a replay attack, an intruder eavesdrops on legitimate routing or control messages exchanged between nodes [107], and then retransmits these packets to UAV networks, attempting to deceive the nodes and disrupt the routing process.…”

Section: B Cyber Attacksmentioning

confidence: 99%

Understanding and Securing Unmanned Aerial Vehicle (UAV) Services: A Comprehensive Tutorial

Anagnostis,

Kotzanikolaou,

Douligeris

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The southbound APIs link to the control plane by gathering policies, forwarding rules, and applying them to the relevant equipment [9]. , POX [11], Trema [12], Beacon [13], Ryu [14], Maestro [15], etc.…”

Section: Software-defined Network Architecturementioning

confidence: 99%

“…Since the control plane is typically a centrally controllable software program, it can handle network traffic dynamically. Several opensource SDN controller programs (NOS) are currently used to deploy the architecture; these are Floodlight[10], POX[11], Trema[12], Beacon[13], Ryu[14], Maestro[15], etc.…”

mentioning

confidence: 99%

POX and RYU Controller Performance Analysis on Software Defined Network

Naim,

Imad,

Abul Hassan

et al. 2023

EAI Endorsed Trans IoT

View full text Add to dashboard Cite

From the last decades different types of network schemes are pitched to enhance the user performance. Software Defined Networks (SDN) is also considered as important factor for different network schemes and its proper administration or management. Due to major deployment in today’s networking era SDN are further sub divided in to commercial and open-source controllers. Commercial and open-source controllers are utilized in different type of businesses. According to our knowledge considerable amount of literature is available on these controllers but did not provide or analyse performance of these controllers on different network parameters. This paper evaluates and compares the performance of two well-known SDN open-source controllers POX and RYU with two performance assessments. The first assessment is the implementation of optimal path by using Dijkstra's algorithm from source to destination. Second assessment is the creation of a custom topology in our desired tool (MiniNet emulator). Then, the performance in terms of QoS parameters such as Jitter, throughput, packet loss, and packet delivery ratio are computed by two end hosts in each network. After the assessments, the performance of POX are optimal as compare to the RYU and best suited to be deployed in any scenario.

show abstract

Security Threats in Flying Ad Hoc Network (FANET)

Cited by 10 publications

References 31 publications

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Understanding and Securing Unmanned Aerial Vehicle (UAV) Services: A Comprehensive Tutorial

POX and RYU Controller Performance Analysis on Software Defined Network

Contact Info

Product

Resources

About