Efficient Trajectory Formulation for Drone Sink in Wireless Sensor Networks: An Asanoha-Based Approach

Nitesh, Kumar; Malwe, Shweta R.; Keshari, Amit Kumar; Amritanjali,

doi:10.1007/s13369-021-06468-9

Cited by 3 publications

(1 citation statement)

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“…Researchers proposed various algorithms for Adhoc-Networks to cope with misbehaving node attacks. However, the trivial mitigation/detection protocols of Adhoc-Networks such as, Vehicular-Adhoc Networks (VANETs) [26], Mobile-Adhoc-Networks (MANETs) [27], Wireless-Sensor-Networks (WSNs)/Underwater-Wireless-Sensor-Networks (UWSNs) [28], [29], Autonomous-Vehicles (AVs) [30], and TCP/IP [31] are not applicable in challenging ICNs such as DTNs, due to long/variable-delay, frequent-disruption, and frequent dis-connectivity of nodes in DTNs.…”

Section: Introductionmentioning

confidence: 99%

FAPMIC: Fake Packet and Selective Packet Drops Attacks Mitigation by Merkle Hash Tree in Intermittently Connected Networks

et al. 2023

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Delay/Disruption Tolerant Networks (DTNs) are a special category of IntermittentlyCon-nectedNetworks (ICNs). It has features such as long-delay, frequent-disruption, asymmetrical-data-rates, and high-bundle-error-rates. DTNs have been mainly developed for planet-to-planet networks, commonly known as Inter-Planetary-Networks (IPNs). However, DTNs have shown undimmed potency in challenged communication networks, such as DakNet, ZebraNet, KioskNet and WiderNet. Due to unique characteristics (Intermittent-connectivity and long-delay) DTNs face tough/huge/several challenges in various research areas i.e bundle-forwarding, key-distribution, privacy, bundle-fragmentation, and malicious/selfish nodes particularly. Malicious/selfish nodes launch various catastrophic attacks, this includes, fake packet attacks, selective packet drops attacks, and denial-of-service/flood attacks. These attacks inevitably consume limited resources (persistent-buffer and bandwidth) in DTNs. Fake-packet and selective-packet-drops attacks are top among the challenging attacks in ICNs. The focus of this article is on critical analyses of fake-packet and selective-packet-drops attacks. The panoramic view on misbehavior nodes mitigation algorithms are analyzed, and evaluated mathematically through several parameters for detection probability/accuracy. This article presents a novel algorithm to detects/mitigates fake-packet and selective-packet-drops attacks. Trace-driven simulation results show the proposed algorithm of this article accurately (enhanced detectionaccuracy, reduces false-positive/false-negative rates) detects malicious nodes which launch fake-packet and selective-packet-drops attacks, unlike previously proposed algorithms which detect only one attack (fakepacket or packet-drops at a time) or detect only malicious path (do not exactly detect malicious nodes which launch attacks).

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