This repo implements the join query schemes, for example, JXT [1], JXT+ and JXT++, and shows the constructions and comparison of them.
This work has been accepted by ACM CCS 2024.
- Background
- Features
- Installation
- Project structure
- Validate Results
- Reuse Beyond the Paper
- Contact Information
The corresponding works i.e., JXT, JXT+, JXT++, solve the join query over encrypted database. The project aims to implement JXT, JXT+ and JXT++ by JAVA, and show the comparison of their storage overhead and query efficiency.
- Applied Cryptography
- Encrypted Database
- Join Queries
- JAVA
- A computer (Recommended configuration 16 GB RAM)
- JDK version 1.8.0
- Maven 3
- Recommended an IDE (IntelliJ IDEA), which will save plenty of time.
Download source code from Scalable Equi-Join Queries over Encrypted Database (zenodo.org).
Build the project using Maven:
mvn clean install
Test to run the java files
src/test/java/JXT.java
src/test/java/JXTp.java
src/test/java/JXTpp.java
MJXT/
├── pom.xml
├── README.md
├── data
├── ├── * //Datasets
├── src
│ ├── main
│ │ └── java
│ │ ├── client
│ │ │ ├── Setup_JXT.java //Setup algorithm of JXT
│ │ │ ├── Setup_JXTp.java //Setup algorithm of JXT+
│ │ │ └── Setup_JXTpp.java //Setup algorithm of JXT++
│ │ ├── server
│ │ │ ├── Server_JXT.java //Search algorithm of JXT
│ │ │ ├── Server_JXTp.java //Search algorithm of JXT+
│ │ │ ├── Server_JXTpp.java //Search algorithm of JXT++
│ │ │ ├── Server_MJXT.java //Search algorithm of MJXT
│ │ │ └── Server_MJXTp.java //Search algorithm of MJXT+
│ │ └── utils
│ └── test
│ └── java
│ ├── JXT.java //JXT scheme
│ ├── JXTp.java //JXT+ scheme
│ ├── JXTpp.java //JXT++ scheme
│ ├── M_JXT.java //MJXT scheme
│ ├── M_JXTp.java //MJXT+ scheme
│ ├── Table_Gen.java //Generate tables
│ ├── Table_Gen_Entropy.java //Generate tables with diff entropy
│ ├── Table_Gen_Lmax.java //Generate tables with diff Lmax
│ ├── test_JXT.java //batch test JXT scheme
│ ├── test_JXTp.java //batch test JXT+ scheme
│ ├── test_JXTpp.java //batch test JXT++ scheme
│ ├── test_JXTpp_Lmax.java //batch test JXT++ scheme for diff Lmax
│ ├── test_Setup.java //test setup time for three schemes
│ └── test_storage.java //test storage overhead for three schemes
└── target (generated after build)
The tables have the naming rules, for example "table1_k5_j5_65536.csv" where "1" denotes the table index, "k5" and "j5" means that there are 5 columns (as attributes, not join attributes) and 5 columns (as join attributes), "65536" means the number of records. Particularly, there are some special tables, for example, "table1_k9_j1_65536_12.csv" where "12" denotes the entropy of join-attribute corresponding to queried attribute value is 12; "table1_k9_j1_65536_Lmax100.csv" where "Lmax100" means the Lmax for the join attribute is 100.
Note that all tables for experiments have been generated, and there is no need to generate new table for result.
For "table*_k*_j*_65536.csv", they have follwoing feature
Attribute value | # records | Number of query result |
---|---|---|
table1_keyword_0_0 | 1000 | 1000 |
table1_keyword_0_1 | 2000 | 2000 |
table1_keyword_0_2 | 3000 | 3000 |
...... | ....... | ...... |
table1_keyword_0_8 | 9000 | 9000 |
table1_keyword_0_9 | 10000 | 10000 |
table1_keyword_0_10 | 1000 | 100 |
table1_keyword_0_11 | 1000 | 200 |
table1_keyword_0_12 | 1000 | 300 |
...... | ...... | ...... |
table1_keyword_0_18 | 1000 | 900 |
table1_keyword_0_19 | 1000 | 1000 |
For "table1_k9_j1_65536_*.csv", they have follwoing feature
Table name | Attribute value | # records | # occurrence for each join attribute |
---|---|---|---|
table1_k9_j1_65536_12.csv | table1_keyword_0_0 | 256 | 16 |
table1_k9_j1_65536_14.csv | table1_keyword_0_0 | 256 | 4 |
table1_k9_j1_65536_16.csv | table1_keyword_0_0 | 256 | 1 |
For "table1_k9_j1_65536_Lmax100.csv", they have follwoing feature
Attribute value | # records | Number of query result | # occurrence for each join attribute |
---|---|---|---|
table1_keyword_0_0 | 1000 | 1000 | 100 |
The output of the experiments will validate the following claims:
- Figure 1 : run
src/test/java/test_storage.java
and setjoin_column
from1
to5
. - Figure 2 and Figure 3 : run
src/test/java/test_JXT.java
,src/test/java/test_JXTp.java
andsrc/test/java/test_JXTpp.java
, you will get lines for JXT, JXT+, JXT++. Note that the result ofkeyword0
-keyword9
belongs to Figure 2 which corresponds to its x-axis1000
-10000
, andkeyword10
-keyword19
belongs to Figure 3 which corresponds to its x-axis10%
-100%
. - Figure 4 : run
src/test/java/test_Setup.java
setjoin_column
from1
to5
. - Figure 5 : run
src/test/java/JXTpp.java
,src/test/java/M_JXT.java
,src/test/java/M_JXTp.java
and settable_num
from2
to6
. - Figure 6 : run
src/test/java/test_JXTpp_Lmax.java
. - Table 3 : run
src/test/java/test_storage.java
and setjoin_column = 1
, setcondition
as_16,_14,_12
.
You can reuse the project by exchanging the dataset which you want to setup and search, but notice that you need to change the variants key_colnum,join_column,record_num
and the path of your dataset (recommended that put your dataset in /data/
).
You can reach us at:
- Author: Kai Du, Jianfeng Wang
- Email: [email protected], [email protected]
[1] Charanjit Jutla and Sikhar Patranabis. 2022. Efficient searchable symmetric encryption for join queries. In International Conference on the Theory and Application of Cryptology and Information Security. Springer, 304–333.