022-practical-cloud-storage-auditing-using-serverless-computing

https://github.com/szu-advtech-2024/022-practical-cloud-storage-auditing-using-serverless-computing

Repository

https://github.com/SZU-AdvTech-2024/022-Practical-Cloud-Storage-Auditing-using-Serverless-Computing/blob/main/

# Cloud Storage Auditing System Using Serverless Computing

Cloud storage auditing research is dedicated to solving the data integrity problem of outsourced storage on the cloud. In recent years, researchers have proposed various cloud storage auditing schemes using different techniques. While these work are elegant in theory, they assume an ideal cloud storage model, i.e., the cloud provides the storage and compute interfaces as required by the proposed schemes. However, this does not hold for mainstream cloud storage system because these systems only provide read and write interfaces,but not compute interface. To bridge this gap, this work proposes a serverless computing-based cloud storage auditing system for existing mainstream cloud object storage. The proposed system leverages exiting cloud storage auditing schemes as a basic building block. Leveraging the characteristics of serverless computing, the proposed system realizes economical, pay-as-you-go cloud storage auditing. The proposed system also supports mainstream cloud storage upper layer applications (e.g., file preview) by not modifying the data formats when embedding authentication tags for latter auditing. Experimental results show that the
proposed scheme is efficient and promising for practical usage.

To better reveal the possibility of cloud storage auditing protocols becoming practical, we also designed a cost model to portray the economic performance. This work has been published by the [SCIS](http://scis.scichina.com/) , and refer to this [online-published version](https://www.sciengine.com/SCIS/doi/10.1007/s11432-022-3597-3) for more details.



In the implementation, we also provide a [python script](https://github.com/jquanC/IntegrityCheckingUsingSCF/blob/master/challenge_length.py) to compute the challenge length `l` that is used by PDP scheme.

## Build

We use java 1.8.0_202, tencentcloud-sdk-java 3.1.210  to develop this project and use IntelliJ IDEA and Maven to compile it. For more configuration details, please refer to [pom.xml](https://github.com/jquanC/IntegrityCheckingUsingSCF/blob/master/pom.xml).

Please note that when packaging serverless cloud functions, you need to modify the  configuration in pom.xml. 



## Usage

Firstly, please import this project into IntelliJ IDEA and it will automatically import all dependencies in pom.xml.

Secondly, you have to prepare the cloud-object-storage service and serverless cloud-function service in the Tencent Cloud or other  cloud service provider.

Upload the packaged jar file to the serverless cloud function, select the API gateway as the trigger and configure accordingly.
For the details of the configuration and use of cloud services, please refer to the [Tencent Cloud documentation](https://intl.cloud.tencent.com/document/product) or the instructions of the cloud service provider you use.

Thus, we have prepared the basis for the operation of the system.

You can start the audit system in IDEA as follows:

1. Replace the string "filePath" with your destination directory which stores the data that is to be outsourced.
2. Replace the string "cosConfigFilePath" which provide the COS configuration, including secretId, ecretKey, regionName, bucketName.
3. Replace the string "reqPath" which provide the request link to trigger the execution of the cloud function.
4. Locate the class com.fchen_group.TPDSInScf.Run.Benchmark,  which is the entrance of the whole program.

It is important to note that the serverless cloud function also need to obtain cloud storage configuration. Because hard-coding the key in the program is not secure,  the most secure way is to read from the environment variable. However, there is a bug with the corresponding API. We have confirmed this bug with Tencent Cloud and gave feedback to them.

If you are used to compile the java program in the command line, you can compile the project by yourself. Then, you can execute the following command in the command line to start the system:

````shell
java -jar TPDSInSCF-1.0-SNAPSHOT_Benchmark-jar-with-dependencies.jar
````

One needs to specify the AUDIT_TASK_NUM, BLOCK_SHARDS and DATA_SHARDS after the program starts.



## Contributing

Please feel free to hack on  our integrity checking system! We're happy to accept contributions.

Owner

Citation (citation.txt)

@article{REPO022,
    author = "Chen, Fei and Cai, Jianquan and Xiang, Tao and Liao, Xiaofeng",
    journal = "Science China Information Sciences",
    number = "3",
    pages = "132102",
    publisher = "Springer",
    title = "{Practical cloud storage auditing using serverless computing}",
    volume = "67",
    year = "2024"
}

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