Visible to the public Biblio

Filters: Author is Kwiat, Kevin  [Clear All Filters]
2020-06-01
Tang, Yuzhe, Zou, Qiwu, Chen, Ju, Li, Kai, Kamhoua, Charles A., Kwiat, Kevin, Njilla, Laurent.  2018.  ChainFS: Blockchain-Secured Cloud Storage. 2018 IEEE 11th International Conference on Cloud Computing (CLOUD). :987–990.
This work presents ChainFS, a middleware system that secures cloud storage services using a minimally trusted Blockchain. ChainFS hardens the cloud-storage security against forking attacks. The ChainFS middleware exposes a file-system interface to end users. Internally, ChainFS stores data files in the cloud and exports minimal and necessary functionalities to the Blockchain for key distribution and file operation logging. We implement the ChainFS system on Ethereum and S3FS and closely integrate it with FUSE clients and Amazon S3 cloud storage. We measure the system performance and demonstrate low overhead.
2018-05-30
Mohaisen, Aziz, Al-Ibrahim, Omar, Kamhoua, Charles, Kwiat, Kevin, Njilla, Laurent.  2017.  Rethinking Information Sharing for Threat Intelligence. Proceedings of the Fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies. :6:1–6:7.

In the past decade, the information security and threat landscape has grown significantly making it difficult for a single defender to defend against all attacks at the same time. This called for introducing information sharing, a paradigm in which threat indicators are shared in a community of trust to facilitate defenses. Standards for representation, exchange, and consumption of indicators are proposed in the literature, although various issues are undermined. In this paper, we take the position of rethinking information sharing for actionable intelligence, by highlighting various issues that deserve further exploration. We argue that information sharing can benefit from well-defined use models, threat models, well-understood risk by measurement and robust scoring, well-understood and preserved privacy and quality of indicators and robust mechanism to avoid free riding behavior of selfish agents. We call for using the differential nature of data and community structures for optimizing sharing designs and structures.