O. M. Olanrewaju, Adebayo Abdulhafeez Abdulwasiu, Nuhu Abdulhafiz
{"title":"增强的按需距离矢量路由协议防止黑洞攻击","authors":"O. M. Olanrewaju, Adebayo Abdulhafeez Abdulwasiu, Nuhu Abdulhafiz","doi":"10.15282/ijsecs.9.1.2023.7.0111","DOIUrl":null,"url":null,"abstract":"Wireless networks are becoming increasingly popular. Mobile ad hoc networks are one category among the different types of wireless networks that transmit packets from the sender node to the receiver node without the use of abase station or infrastructure, as the nodes serve as both hosts and routers. These networks are referred to as mobile because they are movable. MANET is an ad-hoc network that can change positions at any time, and nodes can join or leave at any moment, making it vulnerable to attacks such as Blackhole. Existing solutions, in some ways, led to more memory space consumption, while others led to an overhead. This research proposes an Enhanced On-demand Distance Vector (AODV) routing protocol to prevent Blackhole attacks on MANETs using Diffie Hellman and Message Digest 5 (DHMD), implemented using Network Simulator 2 (NS2). The performance of the proposed protocol was evaluated using the following parameters: Packet Delivery Ratio, throughput, End to End (E2E)Delay, and routing overhead. It was concluded that DHMD has reduced network over head as it resulted to 23% while AODV resulted at 38%and memory consumption for DHMD gave 0.52ms compared to AODV that gave 0.81msdue to Blackhole prevention. This research will help to mitigate the effect of blackhole attacks in a network and increase network performance by reducing overhead and memory consumption.","PeriodicalId":31240,"journal":{"name":"International Journal of Software Engineering and Computer Systems","volume":"40 3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced On-demand Distance Vector Routing Protocol to prevent Blackhole Attack in MANET\",\"authors\":\"O. M. Olanrewaju, Adebayo Abdulhafeez Abdulwasiu, Nuhu Abdulhafiz\",\"doi\":\"10.15282/ijsecs.9.1.2023.7.0111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless networks are becoming increasingly popular. Mobile ad hoc networks are one category among the different types of wireless networks that transmit packets from the sender node to the receiver node without the use of abase station or infrastructure, as the nodes serve as both hosts and routers. These networks are referred to as mobile because they are movable. MANET is an ad-hoc network that can change positions at any time, and nodes can join or leave at any moment, making it vulnerable to attacks such as Blackhole. Existing solutions, in some ways, led to more memory space consumption, while others led to an overhead. This research proposes an Enhanced On-demand Distance Vector (AODV) routing protocol to prevent Blackhole attacks on MANETs using Diffie Hellman and Message Digest 5 (DHMD), implemented using Network Simulator 2 (NS2). The performance of the proposed protocol was evaluated using the following parameters: Packet Delivery Ratio, throughput, End to End (E2E)Delay, and routing overhead. It was concluded that DHMD has reduced network over head as it resulted to 23% while AODV resulted at 38%and memory consumption for DHMD gave 0.52ms compared to AODV that gave 0.81msdue to Blackhole prevention. This research will help to mitigate the effect of blackhole attacks in a network and increase network performance by reducing overhead and memory consumption.\",\"PeriodicalId\":31240,\"journal\":{\"name\":\"International Journal of Software Engineering and Computer Systems\",\"volume\":\"40 3 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Software Engineering and Computer Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15282/ijsecs.9.1.2023.7.0111\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Software Engineering and Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15282/ijsecs.9.1.2023.7.0111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced On-demand Distance Vector Routing Protocol to prevent Blackhole Attack in MANET
Wireless networks are becoming increasingly popular. Mobile ad hoc networks are one category among the different types of wireless networks that transmit packets from the sender node to the receiver node without the use of abase station or infrastructure, as the nodes serve as both hosts and routers. These networks are referred to as mobile because they are movable. MANET is an ad-hoc network that can change positions at any time, and nodes can join or leave at any moment, making it vulnerable to attacks such as Blackhole. Existing solutions, in some ways, led to more memory space consumption, while others led to an overhead. This research proposes an Enhanced On-demand Distance Vector (AODV) routing protocol to prevent Blackhole attacks on MANETs using Diffie Hellman and Message Digest 5 (DHMD), implemented using Network Simulator 2 (NS2). The performance of the proposed protocol was evaluated using the following parameters: Packet Delivery Ratio, throughput, End to End (E2E)Delay, and routing overhead. It was concluded that DHMD has reduced network over head as it resulted to 23% while AODV resulted at 38%and memory consumption for DHMD gave 0.52ms compared to AODV that gave 0.81msdue to Blackhole prevention. This research will help to mitigate the effect of blackhole attacks in a network and increase network performance by reducing overhead and memory consumption.