{"title":"基于 VADIA-Verkle 树的机会型移动社交网络数据完整性攻击应对方法","authors":"Vimitha R Vidhya Lakshmi","doi":"10.58346/jowua.2024.i1.011","DOIUrl":null,"url":null,"abstract":"Opportunistic Mobile Social Networks (OMSN) are prone to data integrity attacks that jeopardize the integrity of the routing data inside the network. Among the several techniques that cope with these attacks in OMSN, tree-based approaches have proven to be the most effective due to its ease of data verification and ensurance in data integrity. This paper evaluates two tree-based data structures, Merkle tree and Verkle tree in terms of their effectiveness in detecting and preventing such attacks. The evaluation considers tree-generation time and proof-checking time, and the results demonstrate that the Verkle tree is a bandwidth-efficient solution and have lower proof-checking time, with a reduction of 98.33% than Merkle tree. This makes Verkle tree a good choice for handling data integrity attacks in OMSN. A Verkle tree-based approach, named VADIA, is proposed to handle data integrity attacks such as packet dropping, packet modification and pollution attack in OMSN. The proposed approach is implemented in the Opportunistic Network Environment (ONE) simulator and is shown to be effective in detecting malicious nodes and paths, reducing false negative rates, and improving accuracy in detecting malicious activities. The results demonstrate a 47%, 84% and 69% improvement in malicious node, malicious path and malicious activity detection over a period of time. Furthermore, the approach achieves an 80% reduction in false negative rates.","PeriodicalId":38235,"journal":{"name":"Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications","volume":"40 20","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"VADIA-Verkle Tree-based Approach for Dealing Data Integrity Attacks in Opportunistic Mobile Social Networks\",\"authors\":\"Vimitha R Vidhya Lakshmi\",\"doi\":\"10.58346/jowua.2024.i1.011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Opportunistic Mobile Social Networks (OMSN) are prone to data integrity attacks that jeopardize the integrity of the routing data inside the network. Among the several techniques that cope with these attacks in OMSN, tree-based approaches have proven to be the most effective due to its ease of data verification and ensurance in data integrity. This paper evaluates two tree-based data structures, Merkle tree and Verkle tree in terms of their effectiveness in detecting and preventing such attacks. The evaluation considers tree-generation time and proof-checking time, and the results demonstrate that the Verkle tree is a bandwidth-efficient solution and have lower proof-checking time, with a reduction of 98.33% than Merkle tree. This makes Verkle tree a good choice for handling data integrity attacks in OMSN. A Verkle tree-based approach, named VADIA, is proposed to handle data integrity attacks such as packet dropping, packet modification and pollution attack in OMSN. The proposed approach is implemented in the Opportunistic Network Environment (ONE) simulator and is shown to be effective in detecting malicious nodes and paths, reducing false negative rates, and improving accuracy in detecting malicious activities. The results demonstrate a 47%, 84% and 69% improvement in malicious node, malicious path and malicious activity detection over a period of time. Furthermore, the approach achieves an 80% reduction in false negative rates.\",\"PeriodicalId\":38235,\"journal\":{\"name\":\"Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications\",\"volume\":\"40 20\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.58346/jowua.2024.i1.011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58346/jowua.2024.i1.011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
VADIA-Verkle Tree-based Approach for Dealing Data Integrity Attacks in Opportunistic Mobile Social Networks
Opportunistic Mobile Social Networks (OMSN) are prone to data integrity attacks that jeopardize the integrity of the routing data inside the network. Among the several techniques that cope with these attacks in OMSN, tree-based approaches have proven to be the most effective due to its ease of data verification and ensurance in data integrity. This paper evaluates two tree-based data structures, Merkle tree and Verkle tree in terms of their effectiveness in detecting and preventing such attacks. The evaluation considers tree-generation time and proof-checking time, and the results demonstrate that the Verkle tree is a bandwidth-efficient solution and have lower proof-checking time, with a reduction of 98.33% than Merkle tree. This makes Verkle tree a good choice for handling data integrity attacks in OMSN. A Verkle tree-based approach, named VADIA, is proposed to handle data integrity attacks such as packet dropping, packet modification and pollution attack in OMSN. The proposed approach is implemented in the Opportunistic Network Environment (ONE) simulator and is shown to be effective in detecting malicious nodes and paths, reducing false negative rates, and improving accuracy in detecting malicious activities. The results demonstrate a 47%, 84% and 69% improvement in malicious node, malicious path and malicious activity detection over a period of time. Furthermore, the approach achieves an 80% reduction in false negative rates.
期刊介绍:
JoWUA is an online peer-reviewed journal and aims to provide an international forum for researchers, professionals, and industrial practitioners on all topics related to wireless mobile networks, ubiquitous computing, and their dependable applications. JoWUA consists of high-quality technical manuscripts on advances in the state-of-the-art of wireless mobile networks, ubiquitous computing, and their dependable applications; both theoretical approaches and practical approaches are encouraged to submit. All published articles in JoWUA are freely accessible in this website because it is an open access journal. JoWUA has four issues (March, June, September, December) per year with special issues covering specific research areas by guest editors.