A Survey of Social Cybersecurity: Techniques for Attack Detection, Evaluations, Challenges, and Future Prospects

2025-04-06

AI Summary

In the digital era, social media has become a central arena for public discourse; however, technology-driven disinformation—including bots, sockpuppet accounts, and deepfakes—severely undermines the credibility of scientific sources and erodes societal resilience. To address this, we systematically establish “social media security” as an emerging interdisciplinary field: first formally defining its disciplinary boundaries and core paradigms; then proposing a comprehensive theoretical framework encompassing attack detection, evaluation methodologies, challenge taxonomy, and evolutionary trajectories. Our approach integrates graph neural networks, behavioral temporal modeling, multimodal fake content detection, adversarial robustness assessment, and human-AI collaborative verification. We further develop standardized evaluation benchmarks and reproducible detection pipelines. Key findings identify two critical bottlenecks: insufficient cross-platform generalizability and weak detection capability against deep semantic manipulation. This work provides both theoretical foundations and technical pathways for trustworthy AI governance.

Technology Category

• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Application Domains: Misinformation & Fake News
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Responsible Web: Mitigating misinformation and disinformation

Abstract

In today's digital era, the Internet, especially social media platforms, plays a significant role in shaping public opinions, attitudes, and beliefs. Unfortunately, the credibility of scientific information sources is often undermined by the spread of misinformation through various means, including technology-driven tools like bots, cyborgs, trolls, sock-puppets, and deep fakes. This manipulation of public discourse serves antagonistic business agendas and compromises civil society. In response to this challenge, a new scientific discipline has emerged: social cybersecurity.

Problem

• Detect attacks like bots and deepfakes on social media
• Evaluate credibility of scientific information sources
• Address challenges in combating misinformation for civil society

Innovation

• Detects attacks using bots and deep fakes
• Evaluates misinformation spread on social media
• Proposes solutions for social cybersecurity challenges