S. Bhandari, F. Herbreteau, V. Laxmi, A. Zemmari, P. Roop, M. Gaur
Sensitive (private) information can escape from one app to another using one of the multiple communication methods provided by Android for inter-app communication. This leakage can be malicious. In such a scenario, individual benign app, in collusion with other conspiring apps, if present, can leak the private information. In this work in progress, we present, a new model-checking based approach for inter-app collusion detection. The proposed technique takes into account simultaneous analysis of multiple apps. We are able to identify any set of conspiring apps involved in the collusion. To evaluate the efficacy of our tool, we developed Android apps that exhibit collusion through inter-app communication. Eight demonstrative sets of apps have been contributed to widely used test dataset named DroidBench. Our experiments show that proposed technique can accurately detect the presence/absence of collusion among apps. To the best of our knowledge, our proposal has improved detection capability than other techniques.
{"title":"Detecting Inter-App Information Leakage Paths","authors":"S. Bhandari, F. Herbreteau, V. Laxmi, A. Zemmari, P. Roop, M. Gaur","doi":"10.1145/3052973.3055163","DOIUrl":"https://doi.org/10.1145/3052973.3055163","url":null,"abstract":"Sensitive (private) information can escape from one app to another using one of the multiple communication methods provided by Android for inter-app communication. This leakage can be malicious. In such a scenario, individual benign app, in collusion with other conspiring apps, if present, can leak the private information. In this work in progress, we present, a new model-checking based approach for inter-app collusion detection. The proposed technique takes into account simultaneous analysis of multiple apps. We are able to identify any set of conspiring apps involved in the collusion. To evaluate the efficacy of our tool, we developed Android apps that exhibit collusion through inter-app communication. Eight demonstrative sets of apps have been contributed to widely used test dataset named DroidBench. Our experiments show that proposed technique can accurately detect the presence/absence of collusion among apps. To the best of our knowledge, our proposal has improved detection capability than other techniques.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76236845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xingzi Yuan, Omid Setayeshfar, Hongfei Yan, Pranav Panage, Xuetao Wei, K. H. Lee
The goal of cyber attack investigation is to fully reconstruct the details of an attack, so we can trace back to its origin, and recover the system from the damage caused by the attack. However, it is often difficult and requires tremendous manual efforts because attack events occurred days or even weeks before the investigation and detailed information we need is not available anymore. Consequently, forensic logging is significantly important for cyber attack investigation. In this paper, we present DroidForensics, a multi-layer forensic logging technique for Android. Our goal is to provide the user with detailed information about attack behaviors that can enable accurate post-mortem investigation of Android attacks. DroidForensics consists of three logging modules. API logger captures Android API calls that contain high-level semantics of an application. Binder logger records interactions between applications to identify causal relations between processes, and system call logger efficiently monitors low-level system events. We also provide the user interface that the user can compose SQL-like queries to inspect an attack. Our experiments show that Droid Forensics has low runtime overhead (2.9% on average) and low space overhead (105 ~ 169 MByte during 24 hours) on real Android devices. It is effective in the reconstruction of realworld Android attacks we have studied.
{"title":"DroidForensics: Accurate Reconstruction of Android Attacks via Multi-layer Forensic Logging","authors":"Xingzi Yuan, Omid Setayeshfar, Hongfei Yan, Pranav Panage, Xuetao Wei, K. H. Lee","doi":"10.1145/3052973.3052984","DOIUrl":"https://doi.org/10.1145/3052973.3052984","url":null,"abstract":"The goal of cyber attack investigation is to fully reconstruct the details of an attack, so we can trace back to its origin, and recover the system from the damage caused by the attack. However, it is often difficult and requires tremendous manual efforts because attack events occurred days or even weeks before the investigation and detailed information we need is not available anymore. Consequently, forensic logging is significantly important for cyber attack investigation. In this paper, we present DroidForensics, a multi-layer forensic logging technique for Android. Our goal is to provide the user with detailed information about attack behaviors that can enable accurate post-mortem investigation of Android attacks. DroidForensics consists of three logging modules. API logger captures Android API calls that contain high-level semantics of an application. Binder logger records interactions between applications to identify causal relations between processes, and system call logger efficiently monitors low-level system events. We also provide the user interface that the user can compose SQL-like queries to inspect an attack. Our experiments show that Droid Forensics has low runtime overhead (2.9% on average) and low space overhead (105 ~ 169 MByte during 24 hours) on real Android devices. It is effective in the reconstruction of realworld Android attacks we have studied.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77613814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Memory corruption errors in C/C++ programs remain the most common source of security vulnerabilities in today's systems. Over the last 10+ years the security community developed several defenses [4]. Data Execution Prevention (DEP) protects against code injection -- eradicating this attack vector. Yet, control-flow hijacking and code reuse remain challenging despite wide deployment of Address Space Layout Randomization (ASLR) and stack canaries. These defenses are probabilistic and rely on information hiding. The deployed defenses complicate attacks, yet control-flow hijack attacks (redirecting execution to a location that would not be reached in a benign execution) are still prevalent. Attacks reuse existing gadgets (short sequences of code), often leveraging information disclosures to learn the location of the desired gadgets. Strong defense mechanisms have not yet been widely deployed due to (i) the time it takes to roll out a security mechanism, (ii) incompatibility with specific features, and (iii) performance overhead. In the meantime, only a set of low-overhead but incomplete mitigations has been deployed in practice. Control-Flow Integrity (CFI) [1,2] and Code-Pointer Integrity (CPI) [3] are two promising upcoming defense mechanisms, protecting against control-flow hijacking. CFI guarantees that the runtime control flow follows the statically determined control-flow graph. An attacker may reuse any of the valid transitions at any control-flow transfer. We compare a broad range of CFI mechanisms using a unified nomenclature based on (i) a qualitative discussion of the conceptual security guarantees, (ii) a quantitative security evaluation, and (iii)~an empirical evaluation of their performance in the same test environment. For each mechanism, we evaluate (i) protected types of control-flow transfers, (ii) the precision of the protection for forward and backward edges. For open-source compiler-based implementations, we additionally evaluate (iii) the generated equivalence classes and target sets, and (iv) the runtime performance. CPI on the other hand is a dynamic property that enforces selective memory safety through bounds checks for code pointers by separating code pointers from regular data.
{"title":"Control-Flow Hijacking: Are We Making Progress?","authors":"Mathias Payer","doi":"10.1145/3052973.3056127","DOIUrl":"https://doi.org/10.1145/3052973.3056127","url":null,"abstract":"Memory corruption errors in C/C++ programs remain the most common source of security vulnerabilities in today's systems. Over the last 10+ years the security community developed several defenses [4]. Data Execution Prevention (DEP) protects against code injection -- eradicating this attack vector. Yet, control-flow hijacking and code reuse remain challenging despite wide deployment of Address Space Layout Randomization (ASLR) and stack canaries. These defenses are probabilistic and rely on information hiding. The deployed defenses complicate attacks, yet control-flow hijack attacks (redirecting execution to a location that would not be reached in a benign execution) are still prevalent. Attacks reuse existing gadgets (short sequences of code), often leveraging information disclosures to learn the location of the desired gadgets. Strong defense mechanisms have not yet been widely deployed due to (i) the time it takes to roll out a security mechanism, (ii) incompatibility with specific features, and (iii) performance overhead. In the meantime, only a set of low-overhead but incomplete mitigations has been deployed in practice. Control-Flow Integrity (CFI) [1,2] and Code-Pointer Integrity (CPI) [3] are two promising upcoming defense mechanisms, protecting against control-flow hijacking. CFI guarantees that the runtime control flow follows the statically determined control-flow graph. An attacker may reuse any of the valid transitions at any control-flow transfer. We compare a broad range of CFI mechanisms using a unified nomenclature based on (i) a qualitative discussion of the conceptual security guarantees, (ii) a quantitative security evaluation, and (iii)~an empirical evaluation of their performance in the same test environment. For each mechanism, we evaluate (i) protected types of control-flow transfers, (ii) the precision of the protection for forward and backward edges. For open-source compiler-based implementations, we additionally evaluate (iii) the generated equivalence classes and target sets, and (iv) the runtime performance. CPI on the other hand is a dynamic property that enforces selective memory safety through bounds checks for code pointers by separating code pointers from regular data.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81014775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Malware & Machine Learning 1","authors":"I. Martinovic","doi":"10.1145/3248557","DOIUrl":"https://doi.org/10.1145/3248557","url":null,"abstract":"","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81656989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Mobile Security 2","authors":"Andrew J. Paverd","doi":"10.1145/3248561","DOIUrl":"https://doi.org/10.1145/3248561","url":null,"abstract":"","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87671672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inter-Component Communication (ICC) provides a message passing mechanism for data exchange between Android applications. It has been long believed that inter-app ICCs can be abused by malware writers to launch collusion attacks using two or more apps. However, because of the complexity of performing pairwise program analysis on apps, the scale of existing analyses is too small (e.g., up to several hundred) to produce concrete security evidence. In this paper, we report our findings in the first large-scale detection of collusive and vulnerable apps, based on inter-app ICC data flows among 110,150 real-world apps. Our system design aims to balance the accuracy of static ICC resolution/data-flow analysis and run-time scalability. This large-scale analysis provides real-world evidence and deep insights on various types of inter-app ICC abuse. Besides the empirical findings, we make several technical contributions, including a new open-source ICC resolution tool with improved accuracy over the state-of-the-art, and a large database of inter-app ICCs and their attributes.
{"title":"Collusive Data Leak and More: Large-scale Threat Analysis of Inter-app Communications","authors":"Amiangshu Bosu, Fang Liu, D. Yao, G. Wang","doi":"10.1145/3052973.3053004","DOIUrl":"https://doi.org/10.1145/3052973.3053004","url":null,"abstract":"Inter-Component Communication (ICC) provides a message passing mechanism for data exchange between Android applications. It has been long believed that inter-app ICCs can be abused by malware writers to launch collusion attacks using two or more apps. However, because of the complexity of performing pairwise program analysis on apps, the scale of existing analyses is too small (e.g., up to several hundred) to produce concrete security evidence. In this paper, we report our findings in the first large-scale detection of collusive and vulnerable apps, based on inter-app ICC data flows among 110,150 real-world apps. Our system design aims to balance the accuracy of static ICC resolution/data-flow analysis and run-time scalability. This large-scale analysis provides real-world evidence and deep insights on various types of inter-app ICC abuse. Besides the empirical findings, we make several technical contributions, including a new open-source ICC resolution tool with improved accuracy over the state-of-the-art, and a large database of inter-app ICCs and their attributes.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86761991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Encryption","authors":"Di Ma","doi":"10.1145/3248551","DOIUrl":"https://doi.org/10.1145/3248551","url":null,"abstract":"","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79418526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Side Channel Attacks","authors":"Hoda A. Khezaimy","doi":"10.1145/3248562","DOIUrl":"https://doi.org/10.1145/3248562","url":null,"abstract":"","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75706761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Drew Davidson, Yaohui Chen, F. George, Long Lu, S. Jha
A majority of today's mobile apps integrate web content of various kinds. Unfortunately, the interactions between app code and web content expose new attack vectors: a malicious app can subvert its embedded web content to steal user secrets; on the other hand, malicious web content can use the privileges of its embedding app to exfiltrate sensitive information such as the user's location and contacts. In this paper, we discuss security weaknesses of the interface between app code and web content through attacks, then introduce defenses that can be deployed without modifying the OS. Our defenses feature WIREframe, a service that securely embeds and renders external web content in Android apps, and in turn, prevents attacks between em- bedded web and host apps. WIREframe fully mediates the interface between app code and embedded web content. Un- like the existing web-embedding mechanisms, WIREframe allows both apps and embedded web content to define simple access policies to protect their own resources. These policies recognize fine-grained security principals, such as origins, and control all interactions between apps and the web. We also introduce WIRE (Web Isolation Rewriting Engine), an offline app rewriting tool that allows app users to inject WIREframe protections into existing apps. Our evaluation, based on 7166 popular apps and 20 specially selected apps, shows these techniques work on complex apps and incur acceptable end-to-end performance overhead.
{"title":"Secure Integration of Web Content and Applications on Commodity Mobile Operating Systems","authors":"Drew Davidson, Yaohui Chen, F. George, Long Lu, S. Jha","doi":"10.1145/3052973.3052998","DOIUrl":"https://doi.org/10.1145/3052973.3052998","url":null,"abstract":"A majority of today's mobile apps integrate web content of various kinds. Unfortunately, the interactions between app code and web content expose new attack vectors: a malicious app can subvert its embedded web content to steal user secrets; on the other hand, malicious web content can use the privileges of its embedding app to exfiltrate sensitive information such as the user's location and contacts. In this paper, we discuss security weaknesses of the interface between app code and web content through attacks, then introduce defenses that can be deployed without modifying the OS. Our defenses feature WIREframe, a service that securely embeds and renders external web content in Android apps, and in turn, prevents attacks between em- bedded web and host apps. WIREframe fully mediates the interface between app code and embedded web content. Un- like the existing web-embedding mechanisms, WIREframe allows both apps and embedded web content to define simple access policies to protect their own resources. These policies recognize fine-grained security principals, such as origins, and control all interactions between apps and the web. We also introduce WIRE (Web Isolation Rewriting Engine), an offline app rewriting tool that allows app users to inject WIREframe protections into existing apps. Our evaluation, based on 7166 popular apps and 20 specially selected apps, shows these techniques work on complex apps and incur acceptable end-to-end performance overhead.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82590569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Malware & Machine Learning 2","authors":"R. Deng","doi":"10.1145/3248559","DOIUrl":"https://doi.org/10.1145/3248559","url":null,"abstract":"","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82747299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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