Keyword based Search over Semantic Data in Polynomial Time

Abstract-In pursuing the development of Yanii, a novel keyword based search system on graph structures, in this paper we present the computational complexity study of the approach, highlighting a comparative study with actual PTIME state-ofthe-art solutions. The comparative study focuses on a theoretical analysis of different frameworks to define complexity ranges, which they correspond to, in the polynomial time class. We characterize such systems in terms of general measures, which give a general description of the behavior of these frameworks according to different aspects that are more general and informative than mere benchmark tests on a few test cases. We show that Yanii holds better performance than others, confirming itself as a promising approach deserving further practical investigation and improvement

Revisit the Concept of PEKS: Problems and a Possible Solution

Since Boneh et al. propose the concept, non-interactive\ud Public-key Encryption with Keyword Search (PEKS) has attracted lots of attention from cryptographers. Non-interactive PEKS enables a third party to test whether or not a tag, generated by the message sender, and a trapdoor, generated by the receiver, contain the same keyword without revealing further information. In this paper we investigate a non-interactive PEKS application proposed by Boneh et al. and show our observations, especially that privacy is\ud not protected against a curious server. We propose the notion of interactive PEKS, which, in contrast to non-interactive PEKS, requires the tag to be generated interactively by the message sender and the receiver. For this new primitive, we identify two types of adversaries, namely a curious user and a curious server, and provide\ud security formulations for the desirable properties. We propose a construction for interactive PEKS and prove its security in the proposed security model

Keyword Search on RDF Graphs - A Query Graph Assembly Approach

Keyword search provides ordinary users an easy-to-use interface for querying RDF data. Given the input keywords, in this paper, we study how to assemble a query graph that is to represent user's query intention accurately and efficiently. Based on the input keywords, we first obtain the elementary query graph building blocks, such as entity/class vertices and predicate edges. Then, we formally define the query graph assembly (QGA) problem. Unfortunately, we prove theoretically that QGA is a NP-complete problem. In order to solve that, we design some heuristic lower bounds and propose a bipartite graph matching-based best-first search algorithm. The algorithm's time complexity is $O(k^{2l} \cdot l^{3l})$, where $l$ is the number of the keywords and $k$ is a tunable parameter, i.e., the maximum number of candidate entity/class vertices and predicate edges allowed to match each keyword. Although QGA is intractable, both $l$ and $k$ are small in practice. Furthermore, the algorithm's time complexity does not depend on the RDF graph size, which guarantees the good scalability of our system in large RDF graphs. Experiments on DBpedia and Freebase confirm the superiority of our system on both effectiveness and efficiency

Adaptively Secure Computationally Efficient Searchable Symmetric Encryption

Searchable encryption is a technique that allows a client to store documents on a server in encrypted form. Stored documents can be retrieved selectively while revealing as little information as\ud possible to the server. In the symmetric searchable encryption domain, the storage and the retrieval are performed by the same client. Most conventional searchable encryption schemes suffer\ud from two disadvantages.\ud First, searching the stored documents takes time linear in the size of the database, and/or uses heavy arithmetic operations.\ud Secondly, the existing schemes do not consider adaptive attackers;\ud a search-query will reveal information even about documents stored\ud in the future. If they do consider this, it is at a significant\ud cost to updates.\ud In this paper we propose a novel symmetric searchable encryption\ud scheme that offers searching at constant time in the number of\ud unique keywords stored on the server. We present two variants of\ud the basic scheme which differ in the efficiency of search and\ud update. We show how each scheme could be used in a personal health\ud record system

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF