Modified Bio-Inspired Algorithms for Intrusion Detection System

Sharma, Moolchand; Saini, Shachi; Bahl, Sneha; Goyal, Rohit; Deswal, Suman

doi:10.1007/978-981-15-5113-0_14

Cited by 2 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Intrusion detection systems can be developed based on behaviors or anomalies. Bio-inspired particle detection IDS can also be used [120]. An updated taxonomy of intrusion detection systems has been conducted by the authors in previous research [121].…”

Section: Network Securitymentioning

confidence: 99%

Towards Resilient UAV Swarms—A Breakdown of Resiliency Requirements in UAV Swarms

Phadke

Medrano

2022

Drones

View full text Add to dashboard Cite

UAVs have rapidly become prevalent in applications related to surveillance, military operations, and disaster relief. Their low cost, operational flexibility, and unmanned capabilities make them ideal for accomplishing tasks in areas deemed dangerous for humans to enter. They can also accomplish previous high-cost and labor-intensive tasks, such as land surveying, in a faster and cheaper manner. Researchers studying UAV applications have realized that a swarm of UAVs working collaboratively on tasks can achieve better results. The dynamic work environment of UAVs makes controlling the vehicles a challenge. This is magnified by using multiple agents in a swarm. Resiliency is a broad concept that effectively defines how well a system handles disruptions in its normal functioning. The task of building resilient swarms has been attempted by researchers for the past decade. However, research on current trends shows gaps in swarm designs that make evaluating the resiliency of such swarms less than ideal. The authors believe that a complete well-defined system built from the ground up is the solution. This survey evaluates existing literature on resilient multi-UAV systems and lays down the groundwork for how best to develop a truly resilient system.

show abstract

Section: Network Securitymentioning

confidence: 99%