Anthony Y. Fu, Xiaotie Deng, Wenyin Liu, Greg Little
{"title":"The methodology and an application to fight against Unicode attacks","authors":"Anthony Y. Fu, Xiaotie Deng, Wenyin Liu, Greg Little","doi":"10.1145/1143120.1143132","DOIUrl":null,"url":null,"abstract":"Unicode is becoming a dominant character representation format for information processing. This presents a very dangerous usability and security problem for many applications. The problem arises because many characters in the UCS (Universal Character Set) are visually and/or semantically similar to each other. This presents a mechanism for malicious people to carry out Unicode Attacks, which include spam attacks, phishing attacks, and web identity attacks. In this paper, we address the potential attacks, and propose a methodology for countering them. To evaluate the feasibility of our methodology, we construct a Unicode Character Similarity List (UC-SimList). We then implement a visual and semantic based edit distance (VSED), as well as a visual and semantic based Knuth-Morris-Pratt algorithm (VSKMP), to detect Unicode attacks. We develop a prototype Unicode attack detection tool, IDN-SecuChecker, which detects phishing weblinks and fake user name (account) attacks. We also introduce the possible practical use of Unicode attack detectors.","PeriodicalId":273244,"journal":{"name":"Symposium On Usable Privacy and Security","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Symposium On Usable Privacy and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1143120.1143132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38
Abstract
Unicode is becoming a dominant character representation format for information processing. This presents a very dangerous usability and security problem for many applications. The problem arises because many characters in the UCS (Universal Character Set) are visually and/or semantically similar to each other. This presents a mechanism for malicious people to carry out Unicode Attacks, which include spam attacks, phishing attacks, and web identity attacks. In this paper, we address the potential attacks, and propose a methodology for countering them. To evaluate the feasibility of our methodology, we construct a Unicode Character Similarity List (UC-SimList). We then implement a visual and semantic based edit distance (VSED), as well as a visual and semantic based Knuth-Morris-Pratt algorithm (VSKMP), to detect Unicode attacks. We develop a prototype Unicode attack detection tool, IDN-SecuChecker, which detects phishing weblinks and fake user name (account) attacks. We also introduce the possible practical use of Unicode attack detectors.