Private Web Search with Constant Round Efficiency

Web search is increasingly becoming an essential activity as it is frequently the most effective and convenient way of finding information. However, it can be a threat for the privacy of users because their queries may reveal their sensitive information. Private web search (PWS) solutions allow users to find information in the Internet while preserving their privacy. In particular, cryptography-based PWS (CB-PWS) systems provide strong privacy guarantees. This paper introduces a constant-round CB-PWS protocol which remains computationally efficient, compared to known CB-PWS systems. Our construction is comparable to similar solutions regarding users\u27 privacy

Abstracts : policy research working paper series - numbers 2197 - 2261

This paper contains abstracts of Policy Research Working Paper series Numbers 2197-2261.Environmental Economics&Policies,Economic Theory&Research,Banks&Banking Reform,Health Economics&Finance,Health Monitoring&Evaluation

Data-Oblivious Graph Algorithms in Outsourced External Memory

Motivated by privacy preservation for outsourced data, data-oblivious external memory is a computational framework where a client performs computations on data stored at a semi-trusted server in a way that does not reveal her data to the server. This approach facilitates collaboration and reliability over traditional frameworks, and it provides privacy protection, even though the server has full access to the data and he can monitor how it is accessed by the client. The challenge is that even if data is encrypted, the server can learn information based on the client data access pattern; hence, access patterns must also be obfuscated. We investigate privacy-preserving algorithms for outsourced external memory that are based on the use of data-oblivious algorithms, that is, algorithms where each possible sequence of data accesses is independent of the data values. We give new efficient data-oblivious algorithms in the outsourced external memory model for a number of fundamental graph problems. Our results include new data-oblivious external-memory methods for constructing minimum spanning trees, performing various traversals on rooted trees, answering least common ancestor queries on trees, computing biconnected components, and forming open ear decompositions. None of our algorithms make use of constant-time random oracles.Comment: 20 page

Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

There has been significant recent interest in parallel graph processing due to the need to quickly analyze the large graphs available today. Many graph codes have been designed for distributed memory or external memory. However, today even the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) can fit in the memory of a single commodity multicore server. Nevertheless, most experimental work in the literature report results on much smaller graphs, and the ones for the Hyperlink graph use distributed or external memory. Therefore, it is natural to ask whether we can efficiently solve a broad class of graph problems on this graph in memory. This paper shows that theoretically-efficient parallel graph algorithms can scale to the largest publicly-available graphs using a single machine with a terabyte of RAM, processing them in minutes. We give implementations of theoretically-efficient parallel algorithms for 20 important graph problems. We also present the optimizations and techniques that we used in our implementations, which were crucial in enabling us to process these large graphs quickly. We show that the running times of our implementations outperform existing state-of-the-art implementations on the largest real-world graphs. For many of the problems that we consider, this is the first time they have been solved on graphs at this scale. We have made the implementations developed in this work publicly-available as the Graph-Based Benchmark Suite (GBBS).Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201

SoK: Cryptographically Protected Database Search

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly; systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions: 1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms. 2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality. 3) An analysis of attacks against protected search for different base queries. 4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac

Auctioning Bulk Mobile Messages

The search for enablers of continued growth of SMS traffic, as well asthe take-off of the more diversified MMS message contents, open up forenterprises the potential of bulk use of mobile messaging , instead ofessentially one-by-one use. In parallel, such enterprises or valueadded services needing mobile messaging in bulk - for spot use or foruse over a prescribed period of time - want to minimize totalacquisition costs, from a set of technically approved providers ofmessaging capacity.This leads naturally to the evaluation of auctioning for bulk SMS orMMS messaging capacity, with the intrinsic advantages therein such asreduction in acquisition costs, allocation efficiency, and optimality.The paper shows, with extensive results as evidence from simulationscarried out in the Rotterdam School of Management e-Auction room, howmulti-attribute reverse auctions perform for the enterprise-buyer, aswell as for the messaging capacity-sellers. We compare 1- and 5-roundauctions, to show the learning effect and the benefits thereof to thevarious parties. The sensitivity will be reported to changes in theenterprise's and the capacity providers utilities and prioritiesbetween message attributes (such as price, size, security, anddelivery delay). At the organizational level, the paper also considersalternate organizational deployment schemes and properties for anoff-line or spot bulk messaging capacity market, subject to technicaland regulatory constraints.MMS;EMS;Mobile commerce;SMS;multi-attribute auctions