Biblio

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.

To help establish a more scientific basis for security science, which will enable the development of fundamental theories and move the field from being primarily reactive to primarily proactive, it is important for research results to be reported in a scientifically rigorous manner. Such reporting will allow for the standard pillars of science, namely replication, meta-analysis, and theory building. In this paper we aim to establish a baseline of the state of scientific work in security through the analysis of indicators of scientific research as reported in the papers from the 2015 IEEE Symposium on Security and Privacy. To conduct this analysis, we developed a series of rubrics to determine the completeness of the papers relative to the type of evaluation used (e.g. case study, experiment, proof). Our findings showed that while papers are generally easy to read, they often do not explicitly document some key information like the research objectives, the process for choosing the cases to include in the studies, and the threats to validity. We hope that this initial analysis will serve as a baseline against which we can measure the advancement of the science of security.

Smartphone users often use private and enterprise data with untrusted third party applications.  The fundamental lack of secrecy guarantees in smartphone OSes, such as Android, exposes this data to the risk of unauthorized exfiltration.  A natural solution is the integration of secrecy guarantees into the OS.  In this paper, we describe the challenges for decentralized information flow control (DIFC) enforcement on Android.  We propose context-sensitive DIFC enforcement via lazy polyinstantiation and practical and secure network export through domain declassification.  Our DIFC system, Weir, is backwards compatible by design, and incurs less than 4 ms overhead for component startup.  With Weir,  we demonstrate practical and secure DIFC enforcement on Android.

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 papers that cover a breadth of security isolation techniques and discuss trade-offs among different design choices and limitations of existing  approaches.