Detection of Multiple Attackers and Provide Security for UAV Networks
P. Jenifa1, S. Gomathi2, V. Perathuselvi3
1P. Jenifa*, P.G. Student, Computer Science and Engineering, Francis Xavier Engineering College, Tamil Nadu, India.
2Dr. S. Gomathi, Associate Professor, Computer Science and Engineering, Francis Xavier Engineering College, Tamil Nadu, India.
3Mrs. V. Perathuselvi, Assistant Prof., Computer Science and Engineering, Francis Xavier Engineering College, Tamil Nadu, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 22, 2020. | Manuscript published on March 10, 2020. | PP: 1413-1416 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2632039520/2020©BEIESP | DOI: 10.35940/ijitee.E2632.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Remote controlled aerial vehicle networks haven’t received right smart analysis attention. Specifically, security problem area unit is a serious concern as a result of such networks that carry very important data square measure at risk of numerous attacks. In our projected system to style and implemented a novel Location –Aided Delay Tolerant Routing Protocol(LADTR) with intrusion detection and response scheme, that operates at the UAV(Unmanned Aerial Vehicle)and ground station level, to find spiteful anomalies that menace the network. And conjointly UAV networks to be used in post-disaster operation, which combined with Store Carry Forward (SCF) techniques. During this theme, a group of detection and response techniques square measure projected to observe the UAV behaviors and reason them into appropriate list (normal, abnormal, suspect, malicious) in keeping with the detected cyber attack. Our simulation result make sure that the projected theme performs well in terms of attack detection even with an oversized range of UAVs and attackers since it exhibits a high detection rate , an occasional range of false positives, and prompt detection overhead and conjointly improve the packet delivery magnitude relation, network time period.
Keywords: UAV, Intrusion, Cyber, Detection, Anomaly.
Scope of the Article: Large-scale cyber systems