Dynamic Searchable Encryption via Blind Storage
- Naveed Muhammad | University of Illinois at Urbana Champaign
Dynamic Searchable Symmetric Encryption allows a client to store a dynamic collection of encrypted documents with a server, and later quickly carry out keyword searches on these encrypted documents, while revealing minimal information to the server. In this paper we present a new dynamic SSE scheme that is simpler and more efficient than existing schemes while revealing less information to the server than prior schemes, achieving fully adaptive security against honest-but-curious servers.
We implemented a prototype of our scheme and demonstrated its efficiency on datasets from prior work. Apart from its concrete efficiency, our scheme is also simpler: in particular, it does not require the server to support any operation other than upload and download of data. Thus the server in our scheme can be based solely on a cloud storage service, rather than a cloud computation service as well, as in prior work.
In building our dynamic SSE scheme, we introduce a new primitive called Blind Storage, which allows a client to store a set of files on a remote server in such a way that the server does not learn how many files are stored, or the lengths of the individual files; as each file is retrieved, the server learns about its existence (and can notice the same file being downloaded subsequently), but the file’s name and contents are not revealed. This is a primitive with several applications other than SSE, and is of independent interest.
Speaker Details
Muhammad Naveed is a third year PhD student in computer science at the University of Illinois at Urbana-Champaign. He is interested in cryptography, security, and privacy. His current research focuses on secure cloud storage, secure multiparty computation, functional encryption, smartphone security and genomics privacy.
-
-
Jeff Running
-
Series: Microsoft Research Talks
-
Decoding the Human Brain – A Neurosurgeon’s Experience
- Dr. Pascal O. Zinn
-
-
-
-
-
-
Challenges in Evolving a Successful Database Product (SQL Server) to a Cloud Service (SQL Azure)
- Hanuma Kodavalla,
- Phil Bernstein
-
Improving text prediction accuracy using neurophysiology
- Sophia Mehdizadeh
-
Tongue-Gesture Recognition in Head-Mounted Displays
- Tan Gemicioglu
-
DIABLo: a Deep Individual-Agnostic Binaural Localizer
- Shoken Kaneko
-
-
-
-
Audio-based Toxic Language Detection
- Midia Yousefi
-
-
From SqueezeNet to SqueezeBERT: Developing Efficient Deep Neural Networks
- Forrest Iandola,
- Sujeeth Bharadwaj
-
Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
- Ashique Khudabukhsh
-
-
-
Towards Mainstream Brain-Computer Interfaces (BCIs)
- Brendan Allison
-
-
-
-
Learning Structured Models for Safe Robot Control
- Subramanian Ramamoorthy
-