Unified Description for Network Information Hiding Methods

Until now hiding methods in network steganography have been described in arbitrary ways, making them difficult to compare. For instance, some publications describe classical channel characteristics, such as robustness and bandwidth, while others describe the embedding of hidden information. We introduce the first unified description of hiding methods in network steganography. Our description method is based on a comprehensive analysis of the existing publications in the domain. When our description method is applied by the research community, future publications will be easier to categorize, compare and extend. Our method can also serve as a basis to evaluate the novelty of hiding methods proposed in the future.Comment: 24 pages, 7 figures, 1 table; currently under revie

Securing Real-Time Internet-of-Things

Modern embedded and cyber-physical systems are ubiquitous. A large number of critical cyber-physical systems have real-time requirements (e.g., avionics, automobiles, power grids, manufacturing systems, industrial control systems, etc.). Recent developments and new functionality requires real-time embedded devices to be connected to the Internet. This gives rise to the real-time Internet-of-things (RT-IoT) that promises a better user experience through stronger connectivity and efficient use of next-generation embedded devices. However RT- IoT are also increasingly becoming targets for cyber-attacks which is exacerbated by this increased connectivity. This paper gives an introduction to RT-IoT systems, an outlook of current approaches and possible research challenges towards secure RT- IoT frameworks

Moving in next door: Network flooding as a side channel in cloud environments

The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-48965-0_56Co-locating multiple tenants' virtual machines (VMs) on the same host underpins public clouds' affordability, but sharing physical hardware also exposes consumer VMs to side channel attacks from adversarial co-residents. We demonstrate passive bandwidth measurement to perform traffic analysis attacks on co-located VMs. Our attacks do not assume a privileged position in the network or require any communication between adversarial and victim VMs. Using a single feature in the observed bandwidth data, our algorithm can identify which of 3 potential YouTube videos a co-resident VM streamed with 66% accuracy. We discuss defense from both a cloud provider's and a consumer's perspective, showing that effective defense is difficult to achieve without costly under-utilization on the part of the cloud provider or over-utilization on the part of the consumer.We would like to acknowledge the MIT PRIMES program and thank in particular Dr. Slava Gerovitch and Dr. Srini Devadas for their support. We are also grateful to Boston University, the Hariri Institute, and the Massachusetts Open Cloud. This paper is based upon work supported by the National Science Foundation under Grants No. 1414119 and 1413920