Tool-Supported Architecture-Based Data Flow Analysis for Confidentiality

TL;DR

This paper presents a Java-based tool that leverages software architecture to perform data flow analysis for estimating system confidentiality at design time, aiming to improve scalability and scenario analysis compared to existing methods.

Contribution

The authors reimplemented a data flow confidentiality analysis as a Java tool that utilizes architecture information to identify access violations, enhancing analysis scalability.

Findings

The tool can analyze similar scenarios effectively.

It scales better for certain scenarios than existing analysis methods.

The approach facilitates confidentiality estimation during design.

Abstract

Through the increasing interconnection between various systems, the need for confidential systems is increasing. Confidential systems share data only with authorized entities. However, estimating the confidentiality of a system is complex, and adjusting an already deployed software is costly. Thus, it is helpful to have confidentiality analyses, which can estimate the confidentiality already at design time. Based on an existing data-flow-based confidentiality analysis concept, we reimplemented a data flow analysis as a Java-based tool. The tool uses the software architecture to identify access violations based on the data flow. The evaluation for our tool indicates that we can analyze similar scenarios and scale for certain scenarios better than the existing analysis.