Digital deception: generative artificial intelligence in social engineering and phishing

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(12)

Published: Oct. 12, 2024

Abstract The advancement of Artificial Intelligence (AI) and Machine Learning (ML) has profound implications for both the utility security our digital interactions. This paper investigates transformative role Generative AI in Social Engineering (SE) attacks. We conduct a systematic review social engineering capabilities use theory to identify three pillars where amplifies impact SE attacks: Realistic Content Creation, Advanced Targeting Personalization, Automated Attack Infrastructure. integrate these elements into conceptual model designed investigate complex nature AI-driven attacks—the Framework. further explore human potential countermeasures mitigate risks. Our study aims foster deeper understanding risks, implications, associated with this emerging paradigm, thereby contributing more secure trustworthy human-computer interaction.

Language: Английский

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GPT, ontology, and CAABAC: A tripartite personalized access control model anchored by compliance, context and attribute

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0310553 - e0310553

Published: Jan. 6, 2025

As digital healthcare evolves, the security of electronic health records (EHR) becomes increasingly crucial. This study presents GPT-Onto-CAABAC framework , integrating Generative Pretrained Transformer (GPT) medical-legal ontologies and Context-Aware Attribute-Based Access Control (CAABAC) to enhance EHR access security. Unlike traditional models, dynamically interprets policies adapts changing legal environments, offering customized control solutions. Through empirical evaluation, this is shown be effective in improving by accurately aligning decisions with complex regulatory situational requirements. The findings suggest its broader applicability sectors where must meet stringent compliance adaptability standards.

Language: Английский

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Innovative Applications of Large Language Models for Medical Record Access Audits

Published: March 22, 2024

This study explores the application of Mistral 8x7b, a state-of-the-art Large Language Model (LLM) with mixture experts architecture, in auditing access to medical records. By conducting comprehensive evaluation, including both quantitative and qualitative analyses, we demonstrate that 8x7b significantly outperforms traditional audit methods detecting unauthorized access, showcasing superior accuracy, precision, recall, F1 score metrics. Additionally, our findings reveal notable improvements computational efficiency, indicating model's potential enhance privacy security healthcare data systems significantly. The research addresses broader implications for privacy, AI ethics, responsible integration technologies sensitive domains. Despite acknowledging certain limitations necessity further validation real-world settings, this underscores transformative advanced models like improving protocols contributing safeguarding patient information an increasingly digital landscape.

Language: Английский

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Application of Enterprise Architecture to Guide the Integration of Health Information Systems in Namibia

Information Resources Management Journal, Journal Year: 2025, Volume and Issue: 38(1), P. 1 - 22

Published: Jan. 10, 2025

Namibia is characterized by a fragmented health-care system that has led to data inconsistencies and duplication of efforts. It also become costly institutions maintain these fragmented, standalone systems. This study examined how enterprise architecture (EA) can be applied guide the integration health information systems (HISs) in Namibian context. A qualitative approach was collect from two cases using semi structured interviews an interpretive analysis. From analysis, constructs requirements clarity, technology (IS/T) project management, documentation, communication were discovered influence development HISs. Applying constructs, developed EA for The recommends future studies consider developing similar quantitative possibly validating approach.

Language: Английский

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Digital technology's impact on knowledge management in the healthcare industry in the Middle East

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 211 - 228

Published: Jan. 1, 2025

Language: Английский

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Exploring the Transformative Impact of Blockchain Technology on Healthcare: Security, Challenges, Benefits, and Future Outlook

Transactions on Emerging Telecommunications Technologies, Journal Year: 2025, Volume and Issue: 36(3)

Published: March 1, 2025

ABSTRACT This study aims to methodically explore the diverse applications of blockchain technology (BT) within healthcare domain. Additionally, it seeks analyze inherent challenges integrating BT into systems. Furthermore, this elucidates blockchain's advantageous contributions The suggested research thoroughly reviews literature from various databases, using predetermined criteria, such as exclusion and inclusion, identify pertinent studies. It also demonstrates properties its functionality for patient, providers, or overall infrastructure assist industry in a contemporary direction. substantial advantages medical field are notable. However, is vital acknowledge security vulnerabilities by employing blockchain‐centered strategy mitigate these challenges, allowing creation robust streamlined system framework. importance that investigation navigates convergence BT, not only delineates multifaceted but meticulously examines associated challenges. findings chart course toward technologically advanced, secure, efficient ecosystem, improving patient outcomes reshaping future delivery worldwide.

Language: Английский

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Improving data transmission through optimizing blockchain sharding in cloud IoT based healthcare applications

Egyptian Informatics Journal, Journal Year: 2025, Volume and Issue: 30, P. 100661 - 100661

Published: March 23, 2025

Language: Английский

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ChainHealth: Blockchain-Based IoT-Edge Model for Secure Management of Health Data

Gazi University Journal of Science Part A Engineering and Innovation, Journal Year: 2025, Volume and Issue: 12(1), P. 72 - 95

Published: March 26, 2025

The Internet of Things (IoT) is rapidly expanding and seamlessly integrating into our daily lives, with an increasing number objects connecting to the Internet. It operates as a networked architecture that enables communication between connected devices. IoT applications span various domains, including smart homes, cities, transportation, healthcare. Among these, healthcare particularly important, allowing specialists monitor patients remotely, anytime, anywhere. In this system, patient data transmitted through systems, enabling remote health monitoring. However, significant challenges remain regarding privacy integrity data. This study addresses these by proposing model named ChainHealth leverages devices for collection, edge infrastructure processing, contracts on blockchain ensure integrity, store securely. Experimental results demonstrate significantly outperforms traditional models in terms transmission efficiency, scalability, overall system performance. enhances throughput, reduces latency even users increases, strengthens encryption processes. Additionally, contract mechanism evaluated shown be reliable managing integrity. As result, proposed ensures secure transfer across network critical information. By maintaining confidentiality, security, improves both quality reliability services compared approaches.

Language: Английский

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Confidentiality in the era of electronic health records: ethical challenges and solutions

International Journal of Community Medicine and Public Health, Journal Year: 2025, Volume and Issue: 12(4), P. 1904 - 1910

Published: March 28, 2025

The incorporation of electronic health records (EHRs) into healthcare systems has greatly enhanced medical data management efficiency and patient care. Concerning confidentiality, this digital transformation also raises ethical security issues. Sensitive information protection is a concern due to unauthorized access, cyber threats, legal complications. Ethical principles autonomy informed consent are usually breached when patients lack control over their use data, especially for secondary uses such as research commercial exploitation. For enhancing confidentiality EHRs, several technology alternatives have been suggested. Self-sovereign identity patient-controlled data-sharing models being explored enable more transparency empower with greater records. dilemmas surrounding EHR examined in literature review, which looks at privacy risks, frameworks, technological solutions. This review will delve the possibility blockchain, artificial intelligence (AI)-powered cybersecurity, role-based access control, encryption viable measures maintaining EHR. By incorporating latest research, aims provide providers, policymakers, researchers on how practices evolve.

Language: Английский

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Generation of Face Privacy-Protected Images Based on the Diffusion Model

Entropy, Journal Year: 2024, Volume and Issue: 26(6), P. 479 - 479

Published: May 31, 2024

In light of growing concerns about the misuse personal data resulting from widespread use artificial intelligence technology, it is necessary to implement robust privacy-protection methods. However, existing methods for protecting facial privacy suffer issues such as poor visual quality, distortion and limited reusability. To tackle this challenge, we propose a novel approach called Diffusion Models Face Privacy Protection (DIFP). Our method utilizes face generator that conditionally controlled reality-guided produce high-resolution encrypted faces are photorealistic while preserving naturalness recoverability original information. We employ two-stage training strategy generate protected with guidance on identity style, followed by an iterative technique improving latent variables enhance realism. Additionally, introduce diffusion model denoising recovery, which facilitates removal encryption restoration when required. Experimental results demonstrate effectiveness our in qualitative protection, achieving high success rates evading face-recognition tools enabling near-perfect occluded faces.

Language: Английский

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