Leveraging Digital Twin-as-a-Service Towards Continuous and Automated Cybersecurity Certification
- URL: http://arxiv.org/abs/2509.07649v1
- Date: Tue, 09 Sep 2025 12:15:46 GMT
- Title: Leveraging Digital Twin-as-a-Service Towards Continuous and Automated Cybersecurity Certification
- Abstract summary: This work presents Security Digital Twinas-a-Service (SDT) for automated, non-intrusive security compliance.<n>SDT enables real-time security assessments by mirroring real-world assets, collecting compliance artifacts, and creating machine-readable evidence.
- Score: 0.7477522997354328
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Traditional risk assessments rely on manual audits and system scans, often causing operational disruptions and leaving security gaps. To address these challenges, this work presents Security Digital Twin-as-a-Service (SDT-aaS), a novel approach that leverages Digital Twin (DT) technology for automated, non-intrusive security compliance. SDT-aaS enables real-time security assessments by mirroring real-world assets, collecting compliance artifacts, and creating machine-readable evidence. The proposed work is a scalable and interoperable solution that supports open standards like CycloneDX and Web of Things (WoT), facilitating seamless integration and efficient compliance management. Empirical results from a moderate-scale infrastructure use case demonstrate its feasibility and performance, paving the way for efficient, on-demand cybersecurity governance with minimal operational impact.
Related papers
- REPOSE: Quantifying the Price of Security in Weakly-Hard Real-Time Cyber-Physical Systems [2.589700903743416]
This study introduces an analytical framework -- REPOSE -- for evaluating the security feasibility of real-time control systems at runtime.<n>In contrast to imposing additional (pessimistic) design-time overhead, REPOSE performs security operations in both textitproactive and textitreactive manners.<n>Our evaluations show that REPOSE can effectively add security operations to RT-CPS with a feasibility overhead of $0.06%$ at $80%$ utilization, compared to a $ 29%$ overhead observed in systems with hard constraints.
arXiv Detail & Related papers (2026-06-12T12:29:11Z) - CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities [66.48570184296857]
CyberGym-E2E is a large-scale and realistic end-to-end cybersecurity benchmark.<n>It comprehensively evaluates AI agents' abilities across the full lifecycle of vulnerability discovery, PoC generation, and patch generation.<n>The benchmark consists of 920 real-world vulnerabilities across 139 different open-source projects.
arXiv Detail & Related papers (2026-06-03T05:06:37Z) - SeClaw: Spec-Driven Security Task Synthesis for Evaluating Autonomous Agents [87.26967184869198]
SeClaw is a framework that combines specification-driven security task synthesis with execution-based security evaluation for Autonomous agents.<n> benchmark covers risks arising from resources, user tasks, environments, and intrinsic agent behaviors.
arXiv Detail & Related papers (2026-06-01T14:23:42Z) - ORCA -- An Automated Threat Analysis Pipeline for O-RAN Continuous Development [57.61878484176942]
Open-Radio Access Network (O-RAN) integrates numerous software components in a cloud-like deployment, opening the radio access network to previously unconsidered security threats.<n>Current vulnerability assessment practices often rely on manual, labor-intensive, and subjective investigations, leading to inconsistencies in the threat analysis.<n>We propose an automated pipeline that leverages Natural Language Processing (NLP) to minimize human intervention and associated biases.
arXiv Detail & Related papers (2026-01-20T07:31:59Z) - A Survey of Security Challenges and Solutions for UAS Traffic Management (UTM) and small Unmanned Aerial Systems (sUAS) [25.67972631925627]
Small Unmanned Aerial Systems (sUAS) for civil and commercial missions are vulnerable to cyber-security threats.<n>This paper presents a comprehensive survey of cyber-security vulnerabilities and defenses tailored to the sUAS and UTM ecosystem.
arXiv Detail & Related papers (2026-01-13T05:18:49Z) - Agentic AI Microservice Framework for Deepfake and Document Fraud Detection in KYC Pipelines [0.0]
Synthetic media, presentation attacks, and document forgeries have created significant vulnerabilities in Know Your Customer (KYC)<n>This paper proposes an Agentic AI Microservice Framework that integrates vision models, liveness assessment, deepfake detection, OCR-based document forensics, multimodal identity linking, and a policy driven risk engine.
arXiv Detail & Related papers (2026-01-09T17:01:40Z) - OS-Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows [77.95511352806261]
Computer-using agents powered by Vision-Language Models (VLMs) have demonstrated human-like capabilities in operating digital environments like mobile platforms.<n>We propose OS-Sentinel, a novel hybrid safety detection framework that combines a Formal Verifier for detecting explicit system-level violations with a Contextual Judge for assessing contextual risks and agent actions.
arXiv Detail & Related papers (2025-10-28T13:22:39Z) - SafeAgent: Safeguarding LLM Agents via an Automated Risk Simulator [77.86600052899156]
Large Language Model (LLM)-based agents are increasingly deployed in real-world applications.<n>We propose AutoSafe, the first framework that systematically enhances agent safety through fully automated synthetic data generation.<n>We show that AutoSafe boosts safety scores by 45% on average and achieves a 28.91% improvement on real-world tasks.
arXiv Detail & Related papers (2025-05-23T10:56:06Z) - Enforcing Cybersecurity Constraints for LLM-driven Robot Agents for Online Transactions [0.0]
The integration of Large Language Models (LLMs) into autonomous robotic agents for conducting online transactions poses significant cybersecurity challenges.<n>This study aims to enforce robust cybersecurity constraints to mitigate the risks associated with data breaches, transaction fraud, and system manipulation.
arXiv Detail & Related papers (2025-03-17T01:01:10Z) - Leveraging Security Observability to Strengthen Security of Digital Ecosystem Architecture [0.0]
complexity poses significant challenges for both observability and security in a digital ecosystem.<n>Observability allows organizations to diagnose performance issues and detect anomalies in real time.<n>Security is focused on protecting sensitive data and ensuring service integrity.<n>This paper examines the interconnections between observability and security within digital ecosystem architectures.
arXiv Detail & Related papers (2024-12-07T11:17:29Z) - In-Context Experience Replay Facilitates Safety Red-Teaming of Text-to-Image Diffusion Models [104.94706600050557]
Text-to-image (T2I) models have shown remarkable progress, but their potential to generate harmful content remains a critical concern in the ML community.<n>We propose ICER, a novel red-teaming framework that generates interpretable and semantic meaningful problematic prompts.<n>Our work provides crucial insights for developing more robust safety mechanisms in T2I systems.
arXiv Detail & Related papers (2024-11-25T04:17:24Z) - ACRIC: Securing Legacy Communication Networks via Authenticated Cyclic Redundancy Integrity Check [98.34702864029796]
Recent security incidents in safety-critical industries exposed how the lack of proper message authentication enables attackers to inject malicious commands or alter system behavior.<n>These shortcomings have prompted new regulations that emphasize the pressing need to strengthen cybersecurity.<n>We introduce ACRIC, a message authentication solution to secure legacy industrial communications.
arXiv Detail & Related papers (2024-11-21T18:26:05Z) - Enhancing Enterprise Security with Zero Trust Architecture [0.0]
Zero Trust Architecture (ZTA) represents a transformative approach to modern cybersecurity.
ZTA shifts the security paradigm by assuming that no user, device, or system can be trusted by default.
This paper explores the key components of ZTA, such as identity and access management (IAM), micro-segmentation, continuous monitoring, and behavioral analytics.
arXiv Detail & Related papers (2024-10-23T21:53:16Z) - Scaling #DNN-Verification Tools with Efficient Bound Propagation and
Parallel Computing [57.49021927832259]
Deep Neural Networks (DNNs) are powerful tools that have shown extraordinary results in many scenarios.
However, their intricate designs and lack of transparency raise safety concerns when applied in real-world applications.
Formal Verification (FV) of DNNs has emerged as a valuable solution to provide provable guarantees on the safety aspect.
arXiv Detail & Related papers (2023-12-10T13:51:25Z) - Digital Twins and the Future of their Use Enabling Shift Left and Shift Right Cybersecurity Operations [15.061739314361871]
Digital Twins (DTs) optimize operations and monitor performance in Smart Critical Systems (SCS) domains like smart grids and manufacturing.
This vision paper outlines intelligent SDT design through innovative techniques, exploring hybrid intelligence with data-driven and rule-based semantic SDT models.
arXiv Detail & Related papers (2023-09-24T11:20:58Z) - ESASCF: Expertise Extraction, Generalization and Reply Framework for an Optimized Automation of Network Security Compliance [0.11249583407496218]
Vulnerability assessment (VA) and Penetration Testing (PT) are widely adopted methods to identify security gaps and anticipate security breaches.<n>Despite the use of autonomous tools and systems, security compliance remains highly repetitive and resources consuming.<n>This paper proposes a novel method to tackle the ever-growing problem of efficiency and effectiveness in network infrastructures security auditing.
arXiv Detail & Related papers (2023-07-20T15:51:23Z) - When Authentication Is Not Enough: On the Security of Behavioral-Based Driver Authentication Systems [53.2306792009435]
We develop two lightweight driver authentication systems based on Random Forest and Recurrent Neural Network architectures.
We are the first to propose attacks against these systems by developing two novel evasion attacks, SMARTCAN and GANCAN.
Through our contributions, we aid practitioners in safely adopting these systems, help reduce car thefts, and enhance driver security.
arXiv Detail & Related papers (2023-06-09T14:33:26Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.