{"title":"一种基于遗传算法的数字数据指纹识别新技术","authors":"S. Iftikhar, Z. Anwar, Muhammad Kamran","doi":"10.1109/HONET.2014.7029385","DOIUrl":null,"url":null,"abstract":"With the rapid sharing of secret documents over the Internet, identifying an unauthorized copying and identity of the guilty agent is becoming more important. Fingerprinting techniques ensure ownership protection and tamper proofing and help in identifying the guilty agent who is responsible for the data leakage. However, these techniques are not robust when the guilty agent attacks the data in a large amount. In this paper a novel and robust, fingerprinting technique is proposed through employing Genetic Algorithm (GA) - a biologically inspired evolutionary computation technique. The robustness of the proposed technique is demonstrated against collusion, deletion and alteration attacks.","PeriodicalId":297826,"journal":{"name":"2014 11th Annual High Capacity Optical Networks and Emerging/Enabling Technologies (Photonics for Energy)","volume":"10 20","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A novel and robust fingerprinting technique for digital data based on Genetic Algorithm\",\"authors\":\"S. Iftikhar, Z. Anwar, Muhammad Kamran\",\"doi\":\"10.1109/HONET.2014.7029385\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid sharing of secret documents over the Internet, identifying an unauthorized copying and identity of the guilty agent is becoming more important. Fingerprinting techniques ensure ownership protection and tamper proofing and help in identifying the guilty agent who is responsible for the data leakage. However, these techniques are not robust when the guilty agent attacks the data in a large amount. In this paper a novel and robust, fingerprinting technique is proposed through employing Genetic Algorithm (GA) - a biologically inspired evolutionary computation technique. The robustness of the proposed technique is demonstrated against collusion, deletion and alteration attacks.\",\"PeriodicalId\":297826,\"journal\":{\"name\":\"2014 11th Annual High Capacity Optical Networks and Emerging/Enabling Technologies (Photonics for Energy)\",\"volume\":\"10 20\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 11th Annual High Capacity Optical Networks and Emerging/Enabling Technologies (Photonics for Energy)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HONET.2014.7029385\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 11th Annual High Capacity Optical Networks and Emerging/Enabling Technologies (Photonics for Energy)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HONET.2014.7029385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel and robust fingerprinting technique for digital data based on Genetic Algorithm
With the rapid sharing of secret documents over the Internet, identifying an unauthorized copying and identity of the guilty agent is becoming more important. Fingerprinting techniques ensure ownership protection and tamper proofing and help in identifying the guilty agent who is responsible for the data leakage. However, these techniques are not robust when the guilty agent attacks the data in a large amount. In this paper a novel and robust, fingerprinting technique is proposed through employing Genetic Algorithm (GA) - a biologically inspired evolutionary computation technique. The robustness of the proposed technique is demonstrated against collusion, deletion and alteration attacks.