The Semantic Web is envisioned as the future of the current web, where the information is enriched with machine understandable semantics. According to the World Wide Web Consortium (W3C), "The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries". Among the various technologies that empower Semantic Web, the most significant ones are Resource Description Framework (RDF) and SPARQL, which facilitate data integration and a means to query respectively. Although Semantic Web is elegantly and effectively equipped for data sharing and integration via RDF, lack of efficient means to securely share data pose limitations in practice. In order to make data sharing and integration pragmatic for Semantic Web, we present a query language based secure data sharing mechanism. We extend SPARQL with a new query form called SANITIZE which comprises a set of sanitization operations that are used to sanitize or mask sensitive data within an RDF graph. The sanitization operations can be further leveraged towards RDF access control and anonymization, thus enabling secure sharing of RDF data.

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Abstract. In this paper we describe the design and implementation of cloudbased assured information sharing systems. In particular, we will describe our current implementation of a centralized cloud-based assured information sharing system and the design of a decentralized hybrid cloud-based assured information sharing system of the future. Our goal is for coalition organizations to share information stored in multiple clouds and enforce appropriate policies. IntroductionThe advent of cloud computing and the continuing movement toward software as a service (SaaS) paradigms has posed an increasing need for assured information sharing (AIS) as a service in the cloud. The urgency of this need has been voiced as recently as April 2011 by NSA CIO Lonny Anderson in describing the agency's focus on a "cloud-centric" approach to information sharing with other agencies [1]. Likewise, the DoD has been embracing cloud computing paradigms to more efficiently, economically, flexibly, and scalably meet its vision of "delivering the power of information to ensure mission success through an agile enterprise with freedom of maneuverability across the information environment" [2][3][4][5]. Both agencies therefore have a tremendous need for effective AIS technologies and tools for cloud environments. Although a number of AIS tools have been developed over the past five years for policy-based information sharing [5][6][7][8], to our knowledge none of these tools operate in the cloud and hence do not provide the scalability needed to support large numbers of users utilizing massive amounts of data. Recent prototype systems for supporting cloud-based AIS have applied cloud-centric engines that query large amounts of data in relational databases via non-cloud policy engines that enforce policies expressed in XACML [9][10]. While this is a significant improvement over prior efforts (and has given us insights into implementing cloud-based solutions), it nevertheless has at least three significant limitations. First, XACML-based policy specifications are not expressive enough to support many of the complex policies needed for AIS missions like those of the NSA and DoD. Second, to meet the scalability and efficiency requirements of mission-critical tasks, the policy engine needs to operate in the cloud rather than externally. Third, secure query processing based on relational technology has limitations in representing and processing unstructured data needed for command and control applications.

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