The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Human–AI Collaboration in Security Operations: Measuring Alert Trust, Automation Bias, and Analyst Upskilling in AI-Augmented SOC Environments
Open accessAbstract
The rapid integration of artificial intelligence (AI) in Security Operations Centers (SOCs) has created both opportunities and challenges for cybersecurity teams. This paper explores the effects of the levels of AI automation on trust of the analysts, decision-making quality, and skill development. The study delves into three main areas: alert trust, automation bias, and skill adaptation. Using an experimental SOC simulator, participants had to use AI detection tools that generated alerts with varied prediction accuracy to examine the effects on trust and performance. Findings suggest that moderate automation promotes healthy trust and improved decision-making accuracy, while high automation could induce excessive reliance and less alertness. Feedback also aids independent detection skill and confidence in analysts. These studies illustrate the imperative to design trust-sensitive adaptive training systems that can allow for better analyst-AI collaboration in cybersecurity.
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“These Gen-1 AI agents can perform natural language processing efficiently: they summarize long cyber reports in accessible language to summarize unstructured security warnings, help the analyst make sense of them, and respond to analyst queries with contextual reasoning and the like [7], [24].”
From The Evolution of Agentic AI in Cybersecurity: From Single LLM Reasoners to Multi-Agent Systems and Autonomous Pipelines (2026) · cites this paper as [24]
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Vinay, V. (2026) · 2026 IEEE 5th International Conference on AI in Cybersecurity (ICAIC) · doi:10.1109/icaic67076.2026.11395809 · Cited by 15
AI-Based Asynchronous Alert Enrichment Framework for Scalable Security Operations Centers
Karki, D., Ranga, V., & Sisaudia, V. (2026) · International Conference on Smart Futuristic Technology (SMARTTECH) · doi:10.1109/icsft66733.2026.11507831
Vinay, V., & Bhardwaj, A. (2026) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai68641.2026.11536537
Guntha, A. (2026) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac70384.2026.11747296
Metadata
- Authors
- Dept. of Cybersecurity, B. C., & Mathew, A.
- Venue
- International Journal of Computer Technology and Electronics Communication
- Publisher
- Ess & Ess Research Publications
- Published
- 2025-10-30
- Volume
- 08
- Issue
- 05
- ISSN
- 2320-0081 (ISSN-L)
- OpenAlex
- W4415487189
- Cited by
- 3
- References
- 0
- Citations by year
- 2026: 3
- FWCI
- 3.30
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Computer Technology and Electronics Communication (publishedVersion, cc-by)
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- human-AI collaboration, security operations center, automation bias, cybersecurity decision-making, prediction accuracy, alertness, feedback, adaptive training systems
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- CoChat. (2026). Citation check: Human–AI Collaboration in Security Operations: Measuring Alert Trust, Automation Bias, and Analyst Upskilling in AI-Augmented SOC Environments. https://app.cochat.ai/papers/10.15680/ijctece.2025.0805010
- The paper
- Dept. of Cybersecurity, B. C., & Mathew, A. (2025). Human–AI Collaboration in Security Operations: Measuring Alert Trust, Automation Bias, and Analyst Upskilling in AI-Augmented SOC Environments. International Journal of Computer Technology and Electronics Communication. https://doi.org/10.15680/ijctece.2025.0805010
