Syed Rafiul Hussain, Imtiaz Karim, Abdullah Al Ishtiaq, Omar Chowdhury, E. Bertino
{"title":"违规行为:4G LTE蜂窝设备的自动黑箱违规检查","authors":"Syed Rafiul Hussain, Imtiaz Karim, Abdullah Al Ishtiaq, Omar Chowdhury, E. Bertino","doi":"10.1145/3460120.3485388","DOIUrl":null,"url":null,"abstract":"The paper focuses on developing an automated black-box testing approach called DIKEUE that checks 4G Long Term Evolution (LTE) control-plane protocol implementations in commercial-off-the-shelf (COTS) cellular devices (also, User Equipments or UEs) for noncompliance with the standard. Unlike prior noncompliance checking approaches which rely on property-guided testing, DIKEUE adopts a property-agnostic, differential testing approach, which leverages the existence of many different control-plane protocol implementations in COTS UEs. DIKEUE uses deviant behavior observed during differential analysis of pairwise COTS UEs as a proxy for identifying noncompliance instances. For deviant behavior identification, DIKEUE first uses black-box automata learning, specialized for 4G LTE control-plane protocols, to extract input-output finite state machine (FSM) for a given UE. It then reduces the identification of deviant behavior in two extracted FSMs as a model checking problem. We applied DIKEUE in checking noncompliance in 14 COTS UEs from 5 vendors and identified 15 new deviant behavior as well as 2 previous implementation issues. Among them, 11 are exploitable whereas 3 can cause potential interoperability issues.","PeriodicalId":135883,"journal":{"name":"Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Noncompliance as Deviant Behavior: An Automated Black-box Noncompliance Checker for 4G LTE Cellular Devices\",\"authors\":\"Syed Rafiul Hussain, Imtiaz Karim, Abdullah Al Ishtiaq, Omar Chowdhury, E. Bertino\",\"doi\":\"10.1145/3460120.3485388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper focuses on developing an automated black-box testing approach called DIKEUE that checks 4G Long Term Evolution (LTE) control-plane protocol implementations in commercial-off-the-shelf (COTS) cellular devices (also, User Equipments or UEs) for noncompliance with the standard. Unlike prior noncompliance checking approaches which rely on property-guided testing, DIKEUE adopts a property-agnostic, differential testing approach, which leverages the existence of many different control-plane protocol implementations in COTS UEs. DIKEUE uses deviant behavior observed during differential analysis of pairwise COTS UEs as a proxy for identifying noncompliance instances. For deviant behavior identification, DIKEUE first uses black-box automata learning, specialized for 4G LTE control-plane protocols, to extract input-output finite state machine (FSM) for a given UE. It then reduces the identification of deviant behavior in two extracted FSMs as a model checking problem. We applied DIKEUE in checking noncompliance in 14 COTS UEs from 5 vendors and identified 15 new deviant behavior as well as 2 previous implementation issues. Among them, 11 are exploitable whereas 3 can cause potential interoperability issues.\",\"PeriodicalId\":135883,\"journal\":{\"name\":\"Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3460120.3485388\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3460120.3485388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noncompliance as Deviant Behavior: An Automated Black-box Noncompliance Checker for 4G LTE Cellular Devices
The paper focuses on developing an automated black-box testing approach called DIKEUE that checks 4G Long Term Evolution (LTE) control-plane protocol implementations in commercial-off-the-shelf (COTS) cellular devices (also, User Equipments or UEs) for noncompliance with the standard. Unlike prior noncompliance checking approaches which rely on property-guided testing, DIKEUE adopts a property-agnostic, differential testing approach, which leverages the existence of many different control-plane protocol implementations in COTS UEs. DIKEUE uses deviant behavior observed during differential analysis of pairwise COTS UEs as a proxy for identifying noncompliance instances. For deviant behavior identification, DIKEUE first uses black-box automata learning, specialized for 4G LTE control-plane protocols, to extract input-output finite state machine (FSM) for a given UE. It then reduces the identification of deviant behavior in two extracted FSMs as a model checking problem. We applied DIKEUE in checking noncompliance in 14 COTS UEs from 5 vendors and identified 15 new deviant behavior as well as 2 previous implementation issues. Among them, 11 are exploitable whereas 3 can cause potential interoperability issues.