CamFlow: Managed Data-sharing for Cloud Services

A model of cloud services is emerging whereby a few trusted providers manage the underlying hardware and communications whereas many companies build on this infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS applications. From the start, strong isolation between cloud tenants was seen to be of paramount importance, provided first by virtual machines (VM) and later by containers, which share the operating system (OS) kernel. Increasingly it is the case that applications also require facilities to effect isolation and protection of data managed by those applications. They also require flexible data sharing with other applications, often across the traditional cloud-isolation boundaries; for example, when government provides many related services for its citizens on a common platform. Similar considerations apply to the end-users of applications. But in particular, the incorporation of cloud services within `Internet of Things' architectures is driving the requirements for both protection and cross-application data sharing. These concerns relate to the management of data. Traditional access control is application and principal/role specific, applied at policy enforcement points, after which there is no subsequent control over where data flows; a crucial issue once data has left its owner's control by cloud-hosted applications and within cloud-services. Information Flow Control (IFC), in addition, offers system-wide, end-to-end, flow control based on the properties of the data. We discuss the potential of cloud-deployed IFC for enforcing owners' dataflow policy with regard to protection and sharing, as well as safeguarding against malicious or buggy software. In addition, the audit log associated with IFC provides transparency, giving configurable system-wide visibility over data flows. [...]Comment: 14 pages, 8 figure

SEEdit: SELinux Security Policy Configuration System with Higher Level Language

Security policy for SELinux is usually created by customizing a sample policy called refpolicy. However, describing and verifying security policy configurations is difficult because in refpolicy, there are more than 100,000 lines of configurations, thousands of elements such as permissions, macros and labels. The memory footprint of refpolicy which is around 5MB, is also a problem for resource constrained devices. We propose a security policy configuration system SEEdit which facilitates creating security policy by a higher level language called SPDL and SPDL tools. SPDL reduces the number of permissions by integrated permissions and removes label configurations. SPDL tools generate security policy configurations from access logs and tool user’s knowledge about applications. Experimental results on an embedded system and a PC system show that practical security policies are created by SEEdit, i.e., describing configurations is semiautomated, created security policies are composed of less than 500 lines of configurations, 100 configuration elements, and thememory footprint in the embedded system is less than 500KB

SEEdit: SELinux Security Policy Configuration System with Higher Level Language

Security policy for SELinux is usually created by customizing a sample policy called refpolicy. However, describing and verifying security policy configurations is difficult because in refpolicy, there are more than 100,000 lines of configurations, thousands of elements such as permissions, macros and labels. The memory footprint of refpolicy which is around 5MB, is also a problem for resource constrained devices. We propose a security policy configuration system SEEdit which facilitates creating security policy by a higher level language called SPDL and SPDL tools. SPDL reduces the number of permissions by integrated permissions and removes label configurations. SPDL tools generate security policy configurations from access logs and tool user’s knowledge about applications. Experimental results on an embedded system and a PC system show that practical security policies are created by SEEdit, i.e., describing configurations is semiautomated, created security policies are composed of less than 500 lines of configurations, 100 configuration elements, and thememory footprint in the embedded system is less than 500KB

Practical Fine-grained Privilege Separation in Multithreaded Applications

An inherent security limitation with the classic multithreaded programming model is that all the threads share the same address space and, therefore, are implicitly assumed to be mutually trusted. This assumption, however, does not take into consideration of many modern multithreaded applications that involve multiple principals which do not fully trust each other. It remains challenging to retrofit the classic multithreaded programming model so that the security and privilege separation in multi-principal applications can be resolved. This paper proposes ARBITER, a run-time system and a set of security primitives, aimed at fine-grained and data-centric privilege separation in multithreaded applications. While enforcing effective isolation among principals, ARBITER still allows flexible sharing and communication between threads so that the multithreaded programming paradigm can be preserved. To realize controlled sharing in a fine-grained manner, we created a novel abstraction named ARBITER Secure Memory Segment (ASMS) and corresponding OS support. Programmers express security policies by labeling data and principals via ARBITER's API following a unified model. We ported a widely-used, in-memory database application (memcached) to ARBITER system, changing only around 100 LOC. Experiments indicate that only an average runtime overhead of 5.6% is induced to this security enhanced version of application

ScaRR: Scalable Runtime Remote Attestation for Complex Systems

The introduction of remote attestation (RA) schemes has allowed academia and industry to enhance the security of their systems. The commercial products currently available enable only the validation of static properties, such as applications fingerprint, and do not handle runtime properties, such as control-flow correctness. This limitation pushed researchers towards the identification of new approaches, called runtime RA. However, those mainly work on embedded devices, which share very few common features with complex systems, such as virtual machines in a cloud. A naive deployment of runtime RA schemes for embedded devices on complex systems faces scalability problems, such as the representation of complex control-flows or slow verification phase. In this work, we present ScaRR: the first Scalable Runtime Remote attestation schema for complex systems. Thanks to its novel control-flow model, ScaRR enables the deployment of runtime RA on any application regardless of its complexity, by also achieving good performance. We implemented ScaRR and tested it on the benchmark suite SPEC CPU 2017. We show that ScaRR can validate on average 2M control-flow events per second, definitely outperforming existing solutions.Comment: 14 page