Dissertation/Thesis
Προβολή σε EDS

The Future of Human-AI Security: How IntraCavi Prevents Destructive AI Self-Replication

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: The Future of Human-AI Security: How IntraCavi Prevents Destructive AI Self-Replication
Συγγραφείς: Dzikowski, Ryszard
Στοιχεία εκδότη: Zenodo
Έτος έκδοσης: 2025
Συλλογή: Zenodo
Θεματικοί όροι: 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
Περιγραφή: 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.
Τύπος εγγράφου: Thesis
Γλώσσα: English
Relation: https://zenodo.org/records/14773971; oai:zenodo.org:14773971; https://doi.org/10.5281/zenodo.14773971
DOI: 10.5281/zenodo.14773971
Διαθεσιμότητα: 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
Αριθμός Καταχώρησης: edsbas.2B9475DF
Βάση Δεδομένων: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://doi.org/10.5281/zenodo.14773971#
    Name: EDS - BASE (ns324271)
    Category: fullText
    Text: View record from BASE
Header DbId: edsbas
DbLabel: BASE
An: edsbas.2B9475DF
RelevancyScore: 892
AccessLevel: 3
PubType: Dissertation/Thesis
PubTypeId: unknown
PreciseRelevancyScore: 891.935607910156
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Future of Human-AI Security: How IntraCavi Prevents Destructive AI Self-Replication
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dzikowski%2C+Ryszard%22">Dzikowski, Ryszard</searchLink>
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: Zenodo
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2025
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Zenodo
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22AI+Cybersecurity%22">AI Cybersecurity</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+Authentication%22">Neural Authentication</searchLink><br /><searchLink fieldCode="DE" term="%22Biometric+Security%22">Biometric Security</searchLink><br /><searchLink fieldCode="DE" term="%22AI+Self-ReplicationAI+Self-Replication%22">AI Self-ReplicationAI Self-Replication</searchLink><br /><searchLink fieldCode="DE" term="%22Cyber+Threat+Prevention%22">Cyber Threat Prevention</searchLink><br /><searchLink fieldCode="DE" term="%22AI+Governance%22">AI Governance</searchLink><br /><searchLink fieldCode="DE" term="%22IntraCavi%22">IntraCavi</searchLink><br /><searchLink fieldCode="DE" term="%22AI+Ethics%22">AI Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Human-AI+Integration%22">Human-AI Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Wearable+Security%22">Wearable Security</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+Device+Cybersecurity%22">Medical Device Cybersecurity</searchLink><br /><searchLink fieldCode="DE" term="%22SiWamed+Project%22">SiWamed Project</searchLink><br /><searchLink fieldCode="DE" term="%22Haixus%22">Haixus</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: 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.
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Thesis
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: https://zenodo.org/records/14773971; oai:zenodo.org:14773971; https://doi.org/10.5281/zenodo.14773971
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.5281/zenodo.14773971
– Name: URL
  Label: Availability
  Group: URL
  Data: https://doi.org/10.5281/zenodo.14773971<br />https://zenodo.org/records/14773971<br />https://www.researchgate.net/publication/388518059_Enhancing_Cybersecurity_Preventing_Unauthorized_AI_Self-_Replication_through_IntraCavi's_Biometric_and_Neural_Safeguards
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: © 2025 Ryszard Dzikowski, licensed under CC BY-SA 4.0
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.2B9475DF
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.2B9475DF
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5281/zenodo.14773971
    Languages:
      – Text: English
    Subjects:
      – SubjectFull: AI Cybersecurity
        Type: general
      – SubjectFull: Neural Authentication
        Type: general
      – SubjectFull: Biometric Security
        Type: general
      – SubjectFull: AI Self-ReplicationAI Self-Replication
        Type: general
      – SubjectFull: Cyber Threat Prevention
        Type: general
      – SubjectFull: AI Governance
        Type: general
      – SubjectFull: IntraCavi
        Type: general
      – SubjectFull: AI Ethics
        Type: general
      – SubjectFull: Human-AI Integration
        Type: general
      – SubjectFull: Wearable Security
        Type: general
      – SubjectFull: Medical Device Cybersecurity
        Type: general
      – SubjectFull: SiWamed Project
        Type: general
      – SubjectFull: Haixus
        Type: general
    Titles:
      – TitleFull: The Future of Human-AI Security: How IntraCavi Prevents Destructive AI Self-Replication
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Dzikowski, Ryszard
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
ResultId 1