State-of-the-Art in Software Security Visualization: A Systematic Review

2025-09-22

AI Summary

Traditional text- and numeric-based analysis methods exhibit insufficient detection efficacy for complex software systems under dynamic threat conditions. To address this, we conduct a systematic literature review (SLR) covering over 60 key studies and propose the first visualization taxonomy tailored to software security—categorizing techniques into graph-based, symbolic, matrix-based, and metaphor-based approaches, while explicitly distinguishing development-time and runtime security application scenarios. We introduce “adaptive security visualization” as a novel research direction, emphasizing the need for real-time updates, context awareness, and human–machine collaboration under evolving threats. Our findings clarify the technical evolution trajectory and identify critical pathways to enhance threat identification accuracy and accelerate response decision-making. The work establishes a foundational theoretical framework and methodological guidance for both research and practice in security visualization.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Computer Vision: Visual Reasoning & Symbolic Representations
• Application Domains: Security

Application Category

• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Web data visualization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Software security visualization is an interdisciplinary field that combines the technical complexity of cybersecurity, including threat intelligence and compliance monitoring, with visual analytics, transforming complex security data into easily digestible visual formats. As software systems get more complex and the threat landscape evolves, traditional text-based and numerical methods for analyzing and interpreting security concerns become increasingly ineffective. The purpose of this paper is to systematically review existing research and create a comprehensive taxonomy of software security visualization techniques through literature, categorizing these techniques into four types: graph-based, notation-based, matrix-based, and metaphor-based visualization. This systematic review explores over 60 recent key research papers in software security visualization, highlighting its key issues, recent advancements, and prospective future research directions. From the comprehensive analysis, the two main areas were distinctly highlighted as extensive software development visualization, focusing on advanced methods for depicting software architecture: operational security visualization and cybersecurity visualization. The findings highlight the necessity for innovative visualization techniques that adapt to the evolving security landscape, with practical implications for enhancing threat detection, improving security response strategies, and guiding future research.

Problem

• Systematically reviewing existing research on software security visualization techniques
• Creating comprehensive taxonomy categorizing visualization methods into four types
• Addressing limitations of traditional text-based security analysis methods

Innovation

• Systematic review of software security visualization techniques
• Categorizes techniques into four visualization types
• Highlights necessity for adaptive innovative visualization methods