Arnold Mashud Abukari, Abukari Abdul Aziz Danaa, Diyawu Mumin, Shiraz Ismail
{"title":"针对智能手机摄像头攻击的多指标轻量级防御方案","authors":"Arnold Mashud Abukari, Abukari Abdul Aziz Danaa, Diyawu Mumin, Shiraz Ismail","doi":"10.34198/ejms.13223.543553","DOIUrl":null,"url":null,"abstract":"Over the years, cyber criminals have succeeded in exposing some vulnerabilities in smartphones and have exploited those vulnerabilities in several ways. In recent years, one of the growing attacks on smartphones is the camera-based attacks. Attackers are able to exploit smartphone vulnerabilities to cause harm to smartphone users by using cameras of the smartphones to capture images and videos. Privacy leakage and confidentiality remains a big threat to smartphone users and this has gained attention from researchers and industry players across the world. In this research paper, a multi-indicator light weight defense scheme is presented to address the rising smartphone camera-based attacks. The random forest algorithm, the Gini coefficient index and the entropy method are adopted in the designing of the proposed scheme. The means of the threat indicators and the Mean Square Deviation (MSD) is also calculated in order to ensure accurate scores and weight assignments of the threat indicators. The proposed multi-indicator light weight scheme demonstrated to be consistent with real situations. A review of literature in camera-based attacks is also presented in this research paper.","PeriodicalId":482741,"journal":{"name":"Earthline Journal of Mathematical Sciences","volume":"46 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Multi-Indicator Light Weight Defense Scheme for Smartphone Camera-Based Attacks\",\"authors\":\"Arnold Mashud Abukari, Abukari Abdul Aziz Danaa, Diyawu Mumin, Shiraz Ismail\",\"doi\":\"10.34198/ejms.13223.543553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the years, cyber criminals have succeeded in exposing some vulnerabilities in smartphones and have exploited those vulnerabilities in several ways. In recent years, one of the growing attacks on smartphones is the camera-based attacks. Attackers are able to exploit smartphone vulnerabilities to cause harm to smartphone users by using cameras of the smartphones to capture images and videos. Privacy leakage and confidentiality remains a big threat to smartphone users and this has gained attention from researchers and industry players across the world. In this research paper, a multi-indicator light weight defense scheme is presented to address the rising smartphone camera-based attacks. The random forest algorithm, the Gini coefficient index and the entropy method are adopted in the designing of the proposed scheme. The means of the threat indicators and the Mean Square Deviation (MSD) is also calculated in order to ensure accurate scores and weight assignments of the threat indicators. The proposed multi-indicator light weight scheme demonstrated to be consistent with real situations. A review of literature in camera-based attacks is also presented in this research paper.\",\"PeriodicalId\":482741,\"journal\":{\"name\":\"Earthline Journal of Mathematical Sciences\",\"volume\":\"46 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Earthline Journal of Mathematical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34198/ejms.13223.543553\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earthline Journal of Mathematical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34198/ejms.13223.543553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-Indicator Light Weight Defense Scheme for Smartphone Camera-Based Attacks
Over the years, cyber criminals have succeeded in exposing some vulnerabilities in smartphones and have exploited those vulnerabilities in several ways. In recent years, one of the growing attacks on smartphones is the camera-based attacks. Attackers are able to exploit smartphone vulnerabilities to cause harm to smartphone users by using cameras of the smartphones to capture images and videos. Privacy leakage and confidentiality remains a big threat to smartphone users and this has gained attention from researchers and industry players across the world. In this research paper, a multi-indicator light weight defense scheme is presented to address the rising smartphone camera-based attacks. The random forest algorithm, the Gini coefficient index and the entropy method are adopted in the designing of the proposed scheme. The means of the threat indicators and the Mean Square Deviation (MSD) is also calculated in order to ensure accurate scores and weight assignments of the threat indicators. The proposed multi-indicator light weight scheme demonstrated to be consistent with real situations. A review of literature in camera-based attacks is also presented in this research paper.