29,378 research outputs found

    Efficient and secure document similarity search cloud utilizing mapreduce

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    Document similarity has important real life applications such as finding duplicate web sites and identifying plagiarism. While the basic techniques such as k-similarity algorithms have been long known, overwhelming amount of data, being collected such as in big data setting, calls for novel algorithms to find highly similar documents in reasonably short amount of time. In particular, pairwise comparison of documents sharing a common feature, necessitates prohibitively high storage and computation power. The wide spread availability of cloud computing provides users easy access to high storage and processing power. Furthermore, outsourcing their data to the cloud guarantees reliability and availability for their data while privacy and security concerns are not always properly addressed. This leads to the problem of protecting the privacy of sensitive data against adversaries including the cloud operator. Generally, traditional document similarity algorithms tend to compare all the documents in a data set sharing same terms (words) with query document. In our work, we propose a new filtering technique that works on plaintext data, which decreases the number of comparisons between the query set and the search set to find highly similar documents. The technique, referred as ZOLIP algorithm, is efficient and scalable, but does not provide security. We also design and implement three secure similarity search algorithms for text documents, namely Secure Sketch Search, Secure Minhash Search and Secure ZOLIP. The first algorithm utilizes locality sensitive hashing techniques and cosine similarity. While the second algorithm uses the Minhash Algorithm, the last one uses the encrypted ZOLIP Signature, which is the secure version of the ZOLIP algorithm. We utilize the Hadoop distributed file system and the MapReduce parallel programming model to scale our techniques to big data setting. Our experimental results on real data show that some of the proposed methods perform better than the previous work in the literature in terms of the number of joins, and therefore, speed

    Practical and fully secure multi keyword ranked search over encrypted data with lightweight client

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    Cloud computing offers computing services such as data storage and computing power and relieves its users of the burden of their direct management. While being extremely convenient, therefore immensely popular, cloud computing instigates concerns of privacy of outsourced data, for which conventional encryption is hardly a solution as the data is meant to be accessed, used and processed in an efficient manner. Multi keyword ranked search over encrypted data (MRSE) is a special form of secure searchable encryption (SSE), which lets users to privately find out the most similar documents to a given query using document representation methods such as tf-idf vectors and metrics such as cosine similarity. In this work, we propose a secure MRSE scheme that makes use of both a new secure k-NN algorithm and somewhat homomorphic encryption (SWHE). The scheme provides data, query and search pattern privacy and is amenable to access pattern privacy. We provide a formal security analysis of the secure k-NN algorithm and rely on IND-CPA security of the SWHE scheme to meet the strong privacy claims. The scheme provides speedup of about two orders of magnitude over the privacy-preserving MRSE schemes using only SWHE while its overall performance is comparable to other schemes in the literature with weaker forms of privacy claims. We present implementations results including one from the literature pertaining to response times, storage and bandwidth requirements and show that the scheme facilitates a lightweight client implementation

    SoK: Cryptographically Protected Database Search

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    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

    Preserving Trustworthiness and Confidentiality for Online Multimedia

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    Technology advancements in areas of mobile computing, social networks, and cloud computing have rapidly changed the way we communicate and interact. The wide adoption of media-oriented mobile devices such as smartphones and tablets enables people to capture information in various media formats, and offers them a rich platform for media consumption. The proliferation of online services and social networks makes it possible to store personal multimedia collection online and share them with family and friends anytime anywhere. Considering the increasing impact of digital multimedia and the trend of cloud computing, this dissertation explores the problem of how to evaluate trustworthiness and preserve confidentiality of online multimedia data. The dissertation consists of two parts. The first part examines the problem of evaluating trustworthiness of multimedia data distributed online. Given the digital nature of multimedia data, editing and tampering of the multimedia content becomes very easy. Therefore, it is important to analyze and reveal the processing history of a multimedia document in order to evaluate its trustworthiness. We propose a new forensic technique called ``Forensic Hash", which draws synergy between two related research areas of image hashing and non-reference multimedia forensics. A forensic hash is a compact signature capturing important information from the original multimedia document to assist forensic analysis and reveal processing history of a multimedia document under question. Our proposed technique is shown to have the advantage of being compact and offering efficient and accurate analysis to forensic questions that cannot be easily answered by convention forensic techniques. The answers that we obtain from the forensic hash provide valuable information on the trustworthiness of online multimedia data. The second part of this dissertation addresses the confidentiality issue of multimedia data stored with online services. The emerging cloud computing paradigm makes it attractive to store private multimedia data online for easy access and sharing. However, the potential of cloud services cannot be fully reached unless the issue of how to preserve confidentiality of sensitive data stored in the cloud is addressed. In this dissertation, we explore techniques that enable confidentiality-preserving search of encrypted multimedia, which can play a critical role in secure online multimedia services. Techniques from image processing, information retrieval, and cryptography are jointly and strategically applied to allow efficient rank-ordered search over encrypted multimedia database and at the same time preserve data confidentiality against malicious intruders and service providers. We demonstrate high efficiency and accuracy of the proposed techniques and provide a quantitative comparative study with conventional techniques based on heavy-weight cryptography primitives

    Supporting service discovery, querying and interaction in ubiquitous computing environments.

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    In this paper, we contend that ubiquitous computing environments will be highly heterogeneous, service rich domains. Moreover, future applications will consequently be required to interact with multiple, specialised service location and interaction protocols simultaneously. We argue that existing service discovery techniques do not provide sufficient support to address the challenges of building applications targeted to these emerging environments. This paper makes a number of contributions. Firstly, using a set of short ubiquitous computing scenarios we identify several key limitations of existing service discovery approaches that reduce their ability to support ubiquitous computing applications. Secondly, we present a detailed analysis of requirements for providing effective support in this domain. Thirdly, we provide the design of a simple extensible meta-service discovery architecture that uses database techniques to unify service discovery protocols and addresses several of our key requirements. Lastly, we examine the lessons learnt through the development of a prototype implementation of our architecture
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