Cluster Computing

, Volume 21, Issue 2, pp 1189–1202 | Cite as

SearchaStore: fast and secure searchable cloud services

  • Wai-Kong LeeEmail author
  • Raphael C.-W. Phan
  • Geong-Sen Poh
  • Bok-Min Goi


The emergence of Cloud Computing is revolutionizing the way we store, query, analyze and consume data, which also bring forward other development that fundamentally changed our life style. For example, Industry 4.0 and Internet of Things (IoT) can improve the quality of manufacturing and many aspects in our daily life; both of them rely heavily on the cloud computing platform to develop. Central to this paradigm shift is the need to keep any common data, often held at remote outsourced locations and usually to be accessed by different authorized parties, secure from being leaked to unauthorized entities. When using the cloud services, consumer may want to encrypt sensitive data before uploading it to the cloud, but this will also eliminate the possibility to search the data efficiently in the cloud storage. A more practical solution to this is to employ a searchable encryption scheme in the cloud storage, so that user can query the encrypted data efficiently without revealing the sensitive data to the service provider. Besides the security and search features, performance of searchable encryption schemes is also very important when it comes to practical applications. In this paper, we propose several techniques to accelerate the search performance of encrypted data stored on the cloud. Notably, our techniques include massively parallel file encryption, multi-array keyword red black tree (KRBT) implementation, batched keyword search and enhanced parallel search in KRBT. To the best of our knowledge, SearchaStore is the first work that attempts to accelerate searchable encryption using GPU technology.


Cloud service Secure outsourcing Keyword Red Black Tree Searchable symmetric encryption 



This work was supported partially by Universiti Tunku Abdul Rahman Research Fund (UTARRF) under Grant IPSR/RMC/UTARRF/2016-C1/G1.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Faculty of Information and Communication TechnologyUniversiti Tunku Abdul RahmanKamparMalaysia
  2. 2.Faculty of EngineeringMultimedia UniversityCyberjayaMalaysia
  3. 3.MIMOS BerhadKuala LumpurMalaysia
  4. 4.Lee Kong Chian Faculty of Engineering and ScienceUniversiti Tunku Abdul RahmanSungai LongMalaysia

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