Visible to the public Biblio

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Tunde-Onadele, Olufogorehan, He, Jingzhu, Dai, Ting, Gu, Xiaohui.  2019.  A Study on Container Vulnerability Exploit Detection. 2019 IEEE International Conference on Cloud Engineering (IC2E). :121–127.
Containers have become increasingly popular for deploying applications in cloud computing infrastructures. However, recent studies have shown that containers are prone to various security attacks. In this paper, we conduct a study on the effectiveness of various vulnerability detection schemes for containers. Specifically, we implement and evaluate a set of static and dynamic vulnerability attack detection schemes using 28 real world vulnerability exploits that widely exist in docker images. Our results show that the static vulnerability scanning scheme only detects 3 out of 28 tested vulnerabilities and dynamic anomaly detection schemes detect 22 vulnerability exploits. Combining static and dynamic schemes can further improve the detection rate to 86% (i.e., 24 out of 28 exploits). We also observe that the dynamic anomaly detection scheme can achieve more than 20 seconds lead time (i.e., a time window before attacks succeed) for a group of commonly seen attacks in containers that try to gain a shell and execute arbitrary code.
Dai, Ting, He, Jingzhu, Gu, Xiaohui, Lu, Shan, Wang, Peipei.  2018.  DScope: Detecting Real-World Data Corruption Hang Bugs in Cloud Server Systems. Proceedings of the ACM Symposium on Cloud Computing. :313-325.

Cloud server systems such as Hadoop and Cassandra have enabled many real-world data-intensive applications running inside computing clouds. However, those systems present many data-corruption and performance problems which are notoriously difficult to debug due to the lack of diagnosis information. In this paper, we present DScope, a tool that statically detects data-corruption related software hang bugs in cloud server systems. DScope statically analyzes I/O operations and loops in a software package, and identifies loops whose exit conditions can be affected by I/O operations through returned data, returned error code, or I/O exception handling. After identifying those loops which are prone to hang problems under data corruption, DScope conducts loop bound and loop stride analysis to prune out false positives. We have implemented DScope and evaluated it using 9 common cloud server systems. Our results show that DScope can detect 42 real software hang bugs including 29 newly discovered software hang bugs. In contrast, existing bug detection tools miss detecting most of those bugs.

Shu, Rui, Gu, Xiaohui, Enck, William.  2017.  A Study of Security Vulnerabilities on Docker Hub. Proceedings of the Seventh ACM on Conference on Data and Application Security and Privacy. :269–280.
Docker containers have recently become a popular approach to provision multiple applications over shared physical hosts in a more lightweight fashion than traditional virtual machines. This popularity has led to the creation of the Docker Hub registry, which distributes a large number of official and community images. In this paper, we study the state of security vulnerabilities in Docker Hub images. We create a scalable Docker image vulnerability analysis (DIVA) framework that automatically discovers, downloads, and analyzes both official and community images on Docker Hub. Using our framework, we have studied 356,218 images and made the following findings: (1) both official and community images contain more than 180 vulnerabilities on average when considering all versions; (2) many images have not been updated for hundreds of days; and (3) vulnerabilities commonly propagate from parent images to child images. These findings demonstrate a strong need for more automated and systematic methods of applying security updates to Docker images and our current Docker image analysis framework provides a good foundation for such automatic security update. This article is summarized in: the morning paper an interesting/influential/important paper from the world of CS every weekday morning, as selected by Adrian Colyer
Shu, Rui, Wang, Peipei, Gorski III, Sigmund A, Andow, Benjamin, Nadkarni, Adwait, Deshotels, Luke, Gionta, Jason, Enck, William, Gu, Xiaohui.  2016.  A Study of Security Isolation Techniques. ACM Comput. Surv.. 49:50:1–50:37.

Security isolation is a foundation of computing systems that enables resilience to different forms of attacks. This article seeks to understand existing security isolation techniques by systematically classifying different approaches and analyzing their properties. We provide a hierarchical classification structure for grouping different security isolation techniques. At the top level, we consider two principal aspects: mechanism and policy. Each aspect is broken down into salient dimensions that describe key properties. We break the mechanism into two dimensions, enforcement location and isolation granularity, and break the policy aspect down into three dimensions: policy generation, policy configurability, and policy lifetime. We apply our classification to a set of representative articles that cover a breadth of security isolation techniques and discuss tradeoffs among different design choices and limitations of existing approaches.