Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage
Searchable encryption (SE) allows cloud tenants to retrieve encrypted data while preserving data confidentiality securely. Many SE solutions have been designed to improve efficiency and security, but most of them are still susceptible to insider Keyword-Guessing Attacks (KGA), which implies that the...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2022
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7259 https://ink.library.smu.edu.sg/context/sis_research/article/8262/viewcontent/VerifiableSearchable_2022_av.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-8262 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.sis_research-82622022-10-13T03:36:17Z Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage MIAO, Yinbin DENG, Robert H. CHOO, Kim-Kwang Raymond LIU, Ximeng LI, Hongwei Searchable encryption (SE) allows cloud tenants to retrieve encrypted data while preserving data confidentiality securely. Many SE solutions have been designed to improve efficiency and security, but most of them are still susceptible to insider Keyword-Guessing Attacks (KGA), which implies that the internal attackers can guess the candidate keywords successfully in an off-line manner. Also in existing SE solutions, a semi-honest-but-curious cloud server may deliver incorrect search results by performing only a fraction of retrieval operations honestly (e.g., to save storage space). To address these two challenging issues, we first construct the basic Verifiable SE Framework (VSEF), which can withstand the inside KGA and achieve verifiable searchability. Based on the basic VSEF, we then present the enhanced VSEF to support multi-keyword search, multi-key encryption and dynamic updates (e.g., data modification, data insertion, and data deletion) at the same time, which highlights the importance of practicability and scalability of SE in real-world application scenarios. We conduct extensive experiments using the Enron email dataset to demonstrate that the enhanced VSEF achieves high efficiency while resisting to the inside KGA and supporting the verifiability of search results. 2022-04-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7259 info:doi/10.1109/TCC.2020.2989296 https://ink.library.smu.edu.sg/context/sis_research/article/8262/viewcontent/VerifiableSearchable_2022_av.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Searchable encryption insider keyword-guessing attack multi-keyword search multi-key encryption dynamic update Data Storage Systems Information Security |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Searchable encryption insider keyword-guessing attack multi-keyword search multi-key encryption dynamic update Data Storage Systems Information Security |
spellingShingle |
Searchable encryption insider keyword-guessing attack multi-keyword search multi-key encryption dynamic update Data Storage Systems Information Security MIAO, Yinbin DENG, Robert H. CHOO, Kim-Kwang Raymond LIU, Ximeng LI, Hongwei Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
description |
Searchable encryption (SE) allows cloud tenants to retrieve encrypted data while preserving data confidentiality securely. Many SE solutions have been designed to improve efficiency and security, but most of them are still susceptible to insider Keyword-Guessing Attacks (KGA), which implies that the internal attackers can guess the candidate keywords successfully in an off-line manner. Also in existing SE solutions, a semi-honest-but-curious cloud server may deliver incorrect search results by performing only a fraction of retrieval operations honestly (e.g., to save storage space). To address these two challenging issues, we first construct the basic Verifiable SE Framework (VSEF), which can withstand the inside KGA and achieve verifiable searchability. Based on the basic VSEF, we then present the enhanced VSEF to support multi-keyword search, multi-key encryption and dynamic updates (e.g., data modification, data insertion, and data deletion) at the same time, which highlights the importance of practicability and scalability of SE in real-world application scenarios. We conduct extensive experiments using the Enron email dataset to demonstrate that the enhanced VSEF achieves high efficiency while resisting to the inside KGA and supporting the verifiability of search results. |
format |
text |
author |
MIAO, Yinbin DENG, Robert H. CHOO, Kim-Kwang Raymond LIU, Ximeng LI, Hongwei |
author_facet |
MIAO, Yinbin DENG, Robert H. CHOO, Kim-Kwang Raymond LIU, Ximeng LI, Hongwei |
author_sort |
MIAO, Yinbin |
title |
Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
title_short |
Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
title_full |
Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
title_fullStr |
Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
title_full_unstemmed |
Verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
title_sort |
verifiable searchable encryption framework against insider keyword-guessing attack in cloud storage |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2022 |
url |
https://ink.library.smu.edu.sg/sis_research/7259 https://ink.library.smu.edu.sg/context/sis_research/article/8262/viewcontent/VerifiableSearchable_2022_av.pdf |
_version_ |
1770576293078761472 |