SQL Ledger: Cryptographically Verifiable Data in Azure SQL Database

被引:10
|
作者
Antonopoulos, Panagiotis [1 ]
Kaushik, Raghav [1 ]
Kodavalla, Hanuma [1 ]
Aceves, Sergio Rosales [1 ]
Wong, Reilly [1 ]
Anderson, Jason [1 ]
Szymaszek, Jakub [1 ]
机构
[1] Microsoft, Redmond, WA 98052 USA
关键词
Database Security; Integrity Protection; Data Verifiability; Ledger; Blockchain; Cryptographic Verifiability;
D O I
10.1145/3448016.3457558
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
SQL Ledger is a new technology that allows cryptographically verifying the integrity of relational data stored in Azure SQL Database and SQL Server. This is achieved by maintaining all historical data in the database and persisting its cryptographic (SHA-256) digests in an immutable, tamper-evident ledger. Digests representing the overall state of the ledger can then be extracted and stored outside of the RDBMS to protect the data from any attacker or high privileged user, including DBAs, system and cloud administrators. The ledger and the historical data are managed transparently, offering protection without any application changes. Historical data is maintained in a relational form to support SQL queries for auditing, forensics and other purposes. SQL Ledger provides cryptographic data integrity guarantees while maintaining the power, flexibility and performance of a commercial RDBMS. In contrast to Blockchain solutions that aim for full integrity, SQL Ledger offers a form of integrity protection known as Forward Integrity. The proposed technology is significantly cheaper and more secure than traditional solutions that establish trust based on audits or mediators, but also has substantial advantages over Blockchain solutions that are complex to deploy, lack data management capabilities and suffer in terms of performance due to their decentralized nature.
引用
收藏
页码:2437 / 2449
页数:13
相关论文
共 50 条
  • [1] Technique for Searching Data in a Cryptographically Protected SQL Database
    Yesin, Vitalii
    Karpinski, Mikolaj
    Yesina, Maryna
    Vilihura, Vladyslav
    Kozak, Ruslan
    Shevchuk, Ruslan
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (20):
  • [2] Support of temporal data on the MS SQL Server and Azure SQL Database platform
    Lachecinski, Sebastian
    [J]. PRZEGLAD ELEKTROTECHNICZNY, 2020, 96 (12): : 95 - 101
  • [3] Microsoft Azure SQL Database Telemetry
    Lang, Willis
    Bertsch, Frank
    DeWitt, David J.
    Ellis, Nigel
    [J]. ACM SOCC'15: PROCEEDINGS OF THE SIXTH ACM SYMPOSIUM ON CLOUD COMPUTING, 2015, : 189 - 194
  • [4] Azure SQL Database Always Encrypted
    Antonopoulos, Panagiotis
    Arasu, Arvind
    Singh, Kunal D.
    Eguro, Ken
    Gupta, Nitish
    Jain, Rajat
    Kaushik, Raghav
    Kodavalla, Hanuma
    Kossmann, Donald
    Ogg, Nikolas
    Ramamurthy, Ravi
    Szymaszek, Jakub
    Trimmer, Jeffrey
    Vaswani, Kapil
    Venkatesan, Ramarathnam
    Zwilling, Mike
    [J]. SIGMOD'20: PROCEEDINGS OF THE 2020 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2020, : 1511 - 1525
  • [5] Automatic Database Troubleshooting of Azure SQL Databases
    Dundjerski, Dejan
    Tomasevic, Milo
    [J]. IEEE TRANSACTIONS ON CLOUD COMPUTING, 2022, 10 (03) : 1604 - 1619
  • [6] Constant Time Recovery in Azure SQL Database
    Antonopoulos, Panagiotis
    Byrne, Peter
    Chen, Wayne
    Diaconu, Cristian
    Kodandaramaih, Raghavendra Thallam
    Kodavalla, Hanuma
    Purnananda, Prashanth
    Radu, Adrian-Leonard
    Ravella, Chaitanya Sreenivas
    Venkataramanappa, Girish Mittur
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2019, 12 (12): : 2143 - 2154
  • [7] Improving Schema Issue Advisor in the Azure SQL Database
    Dundjerski, Dejan
    Lazic, Stefan
    Tomasevic, Milo
    Bojic, Dragan
    [J]. 2017 25TH TELECOMMUNICATION FORUM (TELFOR), 2017, : 733 - 736
  • [8] Self-Managing Database Capabilities in SQL Azure
    Kodavalla, Hanuma
    [J]. 2023 IEEE 39TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS, ICDEW, 2023, : 92 - 92
  • [9] Advanced mechanisms of data exchange and processing in the SQL Server and Azure SQL Database environment with the use JSON']JSON standard
    Drzymala, Pawel
    Welfle, Henryk
    [J]. PRZEGLAD ELEKTROTECHNICZNY, 2019, 95 (01): : 25 - 28
  • [10] Automatically Indexing Millions of Databases in Microsoft Azure SQL Database
    Das, Sudipto
    Grbic, Miroslav
    Ilic, Igor
    Jovandic, Isidora
    Jovanovic, Andrija
    Narasayya, Vivek R.
    Radulovic, Miodrag
    Stikic, Maja
    Xu, Gaoxiang
    Chaudhuri, Surajit
    [J]. SIGMOD '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2019, : 666 - 679