Farsite is a secure, scalable file system that logically functions as a centralized file server but is physically distributed among a set of untrusted computers. Farsite provides file availability and reliability through randomized replicated storage; it ensures the secrecy of file contents

In this dissertation, I study privacy, integrity, and incentive compatibility in computations with untrusted parties. The study of privacy and integrity belongs to the research area of secure multi-party computation, while incentive compatibility is a natural extension of the research on secure

Data are often stored at untrusted database servers. The lack of trust arises naturally when the database server is owned by a third party, as in the case of cloud computing. It also arises if the server may have been compromised, or there is a malicious insider. Ensuring the trustworthiness

the level of trust necessary in order to establish the authenticity and integrity of data at an untrusted server. Earlier work on this problem is limited to situations where there are no updates to the database, or all updates are authorized and vetted by a central trusted entity. This is an unreasonable

the confidentiality and integrity of a program and its data from the platform on which it runs (i.e., the cloud operator's OS, VM and firmware). Our prototype, Haven, is the first system to achieve shielded execution of unmodified legacy applications, including SQL Server and Apache, on a commodity OS (Windows

, content has to be folded in the join operation. We quantify approximate match in structure and content using well defined notions of distance. For structure, we propose computationally inexpensive lower and upper bounds for the tree edit distance metric between two trees. We then show how the tree edit

bandwidth allocation. As this problem is NP-hard, we devise algorithms that achieve constant-factor approximation. In particular, we present a 2-approximation algorithm for unweighted users and a 3-approximation algorithm for weighted users. In our algorithms, we first compute a fractional association

Abstract—We present a general methodology for protecting the confidentiality and integrity of user data for a class of on-line editing applications. The key insight is that many of these applications are designed to perform most of their data-dependent computation on the client side, so

Abstract- In data integration applications, a join matches elements that are common to two data sources. Often, however, elements are represented slightly different in each source, so an approximate join must be used. For XML data, most approximate join strategies are based on some ordered tree

policies to enforce semantic integrity involve intolerable network load, and are therefore not practically feasible. We present a new semantic integrity protocol based on cryptographic primitives which enables the server system to audit the local computations of the clients on demand. Our approach