Enabling Compressed Encryption for Cloud Based Big Data Stores

被引:3
|
作者
Zhang, Meng [1 ,2 ]
Qi, Saiyu [1 ]
Miao, Meixia [3 ]
Zhang, Fuyou [1 ]
机构
[1] Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
[2] State Key Lab Cryptol, POB 5159, Beijing 100878, Peoples R China
[3] Xian Univ Posts & Telecommun, Natl Engn Lab Wireless Secur, Xian 710121, Peoples R China
来源
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Encryption; Compression; Key-value store; OUTSOURCED DATABASE; ALGORITHMS; SEARCH;
D O I
10.1007/978-3-030-31578-8_15
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We propose a secure yet efficient data query system for cloud-based key-value store. Our system supports encryption and compression to ensure confidentiality and query efficiency simultaneously. To reconcile encryption and compression without compromising performance, we propose a new encrypted key-value storage structure based on the concept of horizontal-vertical division. Our storage structure enables fine-grained access to compressed yet encrypted key-value data. We further combine several cryptographic primitives to build secure search indexes on the storage structure. As a result, our system supports rich types of queries including key-value query and range query. We implement a prototype of our system on top of Cassandra. Our evaluation shows that our system increases the throughput by up to 7 times and compression ratio by up to 1.3 times with respect to previous works.
引用
收藏
页码:270 / 287
页数:18
相关论文
共 50 条
  • [1] TinyEnc: Enabling Compressed and Encrypted Big Data Stores With Rich Query Support
    Qi, Saiyu
    Wang, Jianfeng
    Miao, Meixia
    Zhang, Meng
    Chen, Xiaofeng
    IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2023, 20 (01) : 176 - 192
  • [2] MiniCrypt: Reconciling Encryption and Compression for Big Data Stores
    Zheng, Wenting
    Li, Frank
    Popa, Raluca Ada
    Stoica, Ion
    Agarwal, Rachit
    PROCEEDINGS OF THE TWELFTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS 2017), 2017, : 191 - 204
  • [3] An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud
    Lopes, Claudivan Cruz
    Cesario-Times, Valeria
    Matwin, Stan
    de Aguiar Ciferri, Cristina Dutra
    Ciferri, Ricardo Rodrigues
    INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 2018, 14 (04) : 38 - 66
  • [4] Enabling Big Data Query with Modern CAD Systems Redundant Data Stores
    Brazhenenko, Maksym
    Petrivskyi, Volodymyr
    Bychkov, Oleksiy
    Sinitcyn, Igor
    Shevchenko, Victor
    2021 IEEE 16TH INTERNATIONAL CONFERENCE ON THE EXPERIENCE OF DESIGNING AND APPLICATION OF CAD SYSTEMS (CADSM), 2021,
  • [5] Attribute Based Encryption Using Quadratic Residue for the Big Data in Cloud Environment
    Chandrasekaran, Balaji
    Balakrishnan, Ramadoss
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATICS AND ANALYTICS (ICIA' 16), 2016,
  • [6] Research on Data Integrity Encryption Method of Cloud Storage Users Based on Big Data Analysis
    Zhang, Lu
    Shen, Yi
    ADVANCED HYBRID INFORMATION PROCESSING, ADHIP 2019, PT II, 2019, 302 : 162 - 170
  • [7] Efficient Pairing Computation for Attribute Based Encryption Using MBNR for Big Data in Cloud
    Chandrasekaran, Balaji
    Balakrishnan, Ramadoss
    PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON APPLIED AND THEORETICAL COMPUTING AND COMMUNICATION TECHNOLOGY (ICATCCT), 2016, : 243 - 247
  • [8] A Big Data Deduplication Using HECC Based Encryption With Modified Hash Value in Cloud
    Shrivastava, Ankit
    Tiwary, Abhigyan
    PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS), 2018, : 484 - 489
  • [9] Fusion-based advanced encryption algorithm for enhancing the security of Big Data in Cloud
    Vidhya, A.
    Kumar, P. Mohan
    CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, 2022, 30 (02): : 171 - 180
  • [10] Enabling efficient and verifiable secure search on cloud-based encrypted big data
    Du, Ruizhong
    Yu, Chenghao
    Li, Mingyue
    PEER-TO-PEER NETWORKING AND APPLICATIONS, 2023, 16 (05) : 2574 - 2590