Dissertation/Thesis
The Future of Human-AI Security: How IntraCavi Prevents Destructive AI Self-Replication
| Title: | The Future of Human-AI Security: How IntraCavi Prevents Destructive AI Self-Replication |
|---|---|
| Authors: | Dzikowski, Ryszard |
| Publisher Information: | Zenodo |
| Publication Year: | 2025 |
| Collection: | Zenodo |
| Subject Terms: | AI Cybersecurity, Neural Authentication, Biometric Security, AI Self-ReplicationAI Self-Replication, Cyber Threat Prevention, AI Governance, IntraCavi, AI Ethics, Human-AI Integration, Wearable Security, Medical Device Cybersecurity, SiWamed Project, Haixus |
| Description: | The rapid advancement of AI technologies has introduced significant cybersecurity challenges, particularly concerning unauthorized AI self-replication and cyber threats targeting medical wearables. Traditional security mechanisms, such as passwords and cryptographic keys, are increasingly vulnerable to AI-driven intrusions. This research explores IntraCavi, an innovative security framework that integrates neural authentication, biological sensing, and AI-driven real-time threat analysis to establish an impenetrable barrier against unauthorized AI replication. Furthermore, this paper incorporates findings from the SiWamed project, a German cybersecurity initiative that identified security vulnerabilities in wearables with medical functionalities. Devices that monitor heart rate, blood oxygen saturation, and other biometric data are at risk of unauthorized data access and sensor manipulation, which could impact medical treatment decisions. IntraCavi’s authentication mechanisms provide an additional security layer by ensuring that only verified human users and authorized systems can access and modify sensor data. By combining AI security strategies with biometric and neural safeguards, this paper presents a multi-layered security paradigm that strengthens human-AI governance and medical device protection, setting new standards for cybersecurity in AI-driven and healthcare applications. |
| Document Type: | Thesis |
| Language: | English |
| Relation: | https://zenodo.org/records/14773971; oai:zenodo.org:14773971; https://doi.org/10.5281/zenodo.14773971 |
| DOI: | 10.5281/zenodo.14773971 |
| Availability: | https://doi.org/10.5281/zenodo.14773971 https://zenodo.org/records/14773971 https://www.researchgate.net/publication/388518059_Enhancing_Cybersecurity_Preventing_Unauthorized_AI_Self-_Replication_through_IntraCavi's_Biometric_and_Neural_Safeguards |
| Rights: | © 2025 Ryszard Dzikowski, licensed under CC BY-SA 4.0 |
| Accession Number: | edsbas.2B9475DF |
| Database: | BASE |
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