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Journal articles on the topic 'AI-Powered Security'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Poongodi, R. K. "Zero Trust AI Authentication and Blockchain Powered Secure AI." International Journal for Research in Applied Science and Engineering Technology 13, no. 2 (2025): 52–56. https://doi.org/10.22214/ijraset.2025.66800.

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The integration of Zero Trust (ZT) security models with Artificial Intelligence (AI) authentication mechanisms, along with the utilization of blockchain technology, offers a novel paradigm for securing digital interactions and data exchanges in increasingly decentralized and complex networks. Zero Trust, a security framework that assumes no implicit trust and enforces strict identity verification, is well-suited for AI-driven authentication systems that require robust, real-time, and adaptive security measures Blockchain technology further enhances this framework by providing a transparent, im

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Gudimetla, Sandeep Reddy, and Niranjan Reddy Kotha. "AI-POWERED THREAT DETECTION IN CLOUD ENVIRONMENTS." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 1 (2018): 638–42. http://dx.doi.org/10.61841/turcomat.v9i1.14730.

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This study assesses the effectiveness of artificial intelligence (AI) technologies in enhancing threat detection within cloud environments, a critical component given the escalating security challenges in cloud computing. Leveraging various AI methodologies, including machine learning models, deep learning, and anomaly detection techniques, the research aims to improve the accuracy and efficiency of security systems. These AI methods were applied to a series of simulated threat scenarios across diverse cloud platforms to evaluate their capability in real-time threat identification and mitigati

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Sohaib uz Zaman, Erum Parveen, and Syed Hasnain Alam. "AI to Enhance the Transactional Security in Digital Banking." Journal of Management & Social Science 2, no. 2 (2025): 1–22. https://doi.org/10.63075/2apb3z22.

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The integration of artificial intelligence (AI) has enhanced banking operations by providing improved customer service, security, and efficiency. For data privacy and security, Banks must implement robust data security measures to gain customer trust as well as comply with regulatory requirements. Therefore, this study examined whether AI-based security systems can augment transactional safety, secure pay systems, and strengthen customer trust in digital banks. Quantitative research design and stratified random sampling technique is used for data collection. Questionnaire is filled up with dig

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Dongare, Chinmay, Shubham Jha, Akshara Raul, and Maya Patil. "GUARDIANWATCH: AI-POWERED PUBLIC SAFETY SURVEILLANCE." ICTACT Journal on Data Science and Machine Learning 6, no. 1 (2024): 724–28. https://doi.org/10.21917/ijdsml.2024.0148.

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Nowadays, public safety is a key concern, particularly in fast urbanizing areas, urban development plans, and “smart city” projects where strong security measures have been implemented due to new security threats. The increasing trend of urbanization should be reflected in a coordinated approach to establishing efficient urban security systems. Current security systems have numerous constraints, including threat identification, on-the-spot analysis, and communication. These limitations become particularly emphasized in extremely complex urban areas with high populations and a broad range of ac

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Akhtar, Zarif Bin, and Ahmed Tajbiul Rawol. "Enhancing Cybersecurity through AI-Powered Security Mechanisms." IT Journal Research and Development 9, no. 1 (2024): 50–67. http://dx.doi.org/10.25299/itjrd.2024.16852.

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In the rapidly evolving landscape of digital technology, the proliferation of interconnected systems has brought unprecedented opportunities and challenges. Among these challenges, the escalating frequency and sophistication of cyberattacks pose significant threats to individuals, organizations, and nations. In response, the fusion of Cybersecurity and Artificial Intelligence (AI) has emerged as a pivotal paradigm, offering proactive, intelligent, and adaptable defense mechanisms. This research explores the transformative impacts of AI-powered security on cybersecurity, demonstrating how AI te

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Abubakar, Ruqayyah Abdullahi, Ahmed Abubakar Aliyu, Zahra B. Yashe, et al. "Enhanced AI-Powered Customer Experience Model." Science World Journal 20, no. 1 (2025): 17–21. https://doi.org/10.4314/swj.v20i1.3.

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This journal will focus on the intersection of artificial intelligence (AI) and customer experience (CX), highlighting how emerging technologies enhance customer interactions, personalization and satisfaction.AI- powered customer experience models are revolutionizing how business interact with customers by offering real-time, personalized and data-driven interactions. Today’s customers expect brands to anticipate their needs, resolve issues instantly, and provide seamless interactions across all channels. The enhanced AI- powered customer experience model aims to transform traditional customer

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Gandham, Deepak. "AI-POWERED API SECURITY: REVOLUTIONIZING DIGITAL DEFENSE." INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY AND MANAGEMENT INFORMATION SYSTEMS 16, no. 1 (2025): 358–69. https://doi.org/10.34218/ijitmis_16_01_027.

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khan, Emad, MD Hafizullah, MD Saif, MD Ashraf Ansari, and Neha Kumari. "AI powered: Election voting system." International Journal of Research in Engineering and Innovation 09, no. 04 (2025): 199–204. https://doi.org/10.36037/ijrei.2025.9408.

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In democratic countries, free and fair elections are essential for representative governance. Traditional voting systems, whether manual or electronic, face challenges in security, accuracy, and efficiency. This paper proposes an AI-powered Voting System developed using Java and a relational database, focusing on secure voter authentication, intelligent vote management, and automated result processing. The system integrates AI concepts like data validation and anomaly detection alongside a robust Java-based backend and database for reliable data handling. The system aims to enhance electoral p

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Arun Kumar Soumya, Akash. "AI-Powered Strategies for Enhanced Email Security and Phishing Defense." International Journal of Science and Research (IJSR) 13, no. 12 (2024): 1335–37. https://doi.org/10.21275/sr241220090939.

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Swapna Reddy Anugu. "AI in Financial Services: Revolutionizing Fraud Detection and Risk Management." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 208–17. https://doi.org/10.32628/cseit25112354.

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This comprehensive article examines the transformative impact of artificial intelligence and machine learning technologies on financial institutions' approaches to fraud detection, risk management, and regulatory compliance. The article explores how cloud-powered AI solutions are revolutionizing security measures and operational efficiency in the financial sector. From advanced fraud detection systems to automated regulatory compliance, the article demonstrates how AI-driven solutions are enabling financial organizations to enhance their security posture while streamlining operations. The arti

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Arefin, Sabira. "Strengthening Healthcare Data Security with Ai-Powered Threat Detection." International Journal of Scientific Research and Management (IJSRM) 12, no. 10 (2024): 1477–83. http://dx.doi.org/10.18535/ijsrm/v12i10.ec02.

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As the healthcare industry undergoes rapid digital transformation, the need for robust cybersecurity measures has never been more critical. AI-driven solutions, such as Machine Learning (ML) and anomaly detection, are proving to be pivotal in securing healthcare data. These technologies enable healthcare organizations to identify cyber threats proactively, automate incident response, and enhance data security. Furthermore, AI's ability to provide continuous network monitoring, predictive analytics, and real-time anomaly detection offers healthcare providers the tools needed to mitigate risks b

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Sudheer Obbu. "Zero trust architecture for AI-powered cloud systems: Securing the future of automated workloads." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 1315–39. https://doi.org/10.30574/wjarr.2025.26.1.1173.

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Zero Trust Architecture (ZTA) offers a critical security framework for AI-powered cloud systems, replacing traditional perimeter-based defenses with the principle of "never trust, always verify." As organizations deploy increasingly sophisticated AI workloads in distributed cloud environments, they face unique and acute security challenges including model poisoning, adversarial attacks, and extraction attempts targeting valuable intellectual property. ZTA addresses these challenges through continuous authentication, least privilege access, micro-segmentation, and ongoing monitoring specificall

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Alok, Anand, Kumar Anish, Babu NJ Akash, Kumar Deepak, and M. K. Varshitha. "AI Powered Code Review Assistant." International Journal of Innovative Science and Research Technology (IJISRT) 9, no. 12 (2024): 458–63. https://doi.org/10.5281/zenodo.14533537.

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With the increasing complexity of software systems, maintaining high code quality is essential to ensure reliability, maintainability, and security.  Traditionally, code reviews havebeen a manual and time- consuming process, often resulting in inconsistencies and  missed issues due to human error. Recent advance- ments in artificial intelligence, specifically generative AI models like OpenAI’s Chat- GPT and Google Gemini, have opened new possibilities for automating code reviews by providing real-time, intelligent feedback on code quality.  This survey paper explores the c

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Sandeep, Phanireddy. "AI-Powered Zero Trust Architecture for Web App Security." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 11, no. 4 (2023): 1–6. https://doi.org/10.5281/zenodo.14945119.

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Traditional perimeter-based security models fail to protect against advanced cyber threats, so organizations need a better security framework which implements Zero Trust principles. Zero Trust Architecture (ZTA) uses the verification principle of "never trust always verify" to deliver a real-time security solution with authentication along with authorization and monitoring. The deployment of Artificial Intelligence (AI) within Zero Trust security operations delivers automatic threat identification along with behavior analysis services and adaptive policy implementations to boost protection mea

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Gaddam, Narayana. "AI-POWERED KEY DISTRIBUTION MECHANISM FOR IOT SECURITY." INTERNATIONAL JOURNAL OF INTERNET OF THINGS 1, no. 1 (2023): 16–28. https://doi.org/10.34218/ijiot_01_01_003.

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Husnain, Ali. "Artificial Intelligence and Deep Learning in Healthcare, Cyber security, and Food Systems: A Comprehensive Review of Applications, Challenges, and Future Directions." Global Journal of Emerging AI and Computing 1, no. 2 (2025): 95–126. https://doi.org/10.70445/gjeac.1.2.2025.95-126.

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The implementation of Artificial Intelligence in healthcare alongside cyber security and food systems produces enhanced efficiency and security functions together with automated processes. Healthcare organizations use AI-powered diagnostic instruments together with predictive data tools and individualized medical approaches to enhance therapeutic results while shortening drug development cycles. AI applications need proper solution to algorithmic biases while protecting data privacy and respecting ethical values for the sake of transparent and fair implementation. Security frameworks which are

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MADHURI, BODIGARI, and SMT.A.KALPANA. "The AI-Powered Cybersecurity: Identifying A Threats in Digital Banking." Journal of Engineering Sciences 16, no. 04 (2025): 153–58. https://doi.org/10.36893/jes.2025.v16i04.025.

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With the rapid adoption of digital banking, cybersecurity threats have also evolved, posing significant risks to financial institutions and their customers. AI-powered cybersecurity solutions have emerged as an effective approach to detect and mitigate cyber threats in real-time. This paper explores the role of artificial intelligence in enhancing digital banking security, focusing on anomaly detection, fraud prevention, and threat intelligence. We analyze how machine learning algorithms, behavioral analysis, and predictive analytics contribute to securing financial transactions. Furthermore,

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Mohsin, Zainab Rustum. "AI-Powered Encryption Revolutionizing Cybersecurity with Adaptive Cryptographic Algorithms." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 16, no. 1 (2025): 44–62. https://doi.org/10.61841/turcomat.v16i1.14976.

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This paper proposes a state-of-the-art encryption technique that integrates artificial intelligence into a dynamic, content-aware security system. We introduce an AI-powered encryption framework that automatically adjusts cryptographic parameters based on message sensitivity, effectively balancing security requirements and computational efficiency. The system combines a DistilBERT-based neural network for real-time content sensitivity analysis with a flexible encryption mechanism that adapts key lengths, iteration counts, and entropy levels on the fly. Our implementation demonstrates significa

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Kolawole Joseph Ajiboye. "Ensuring data security and compliance in AI-powered business applications." Global Journal of Engineering and Technology Advances 15, no. 1 (2023): 125–42. https://doi.org/10.30574/gjeta.2023.15.1.0067.

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Artificial intelligence technologies revolutionized how firms make judgments while transforming both data automation and processing throughout company operations. The fast commercial adoption of artificial intelligence technology produced new demanding hurdles for data security coupled with regulatory compliance issues. The vast processing of secret data by AI systems makes them into key targets that cyber attackers and auditors both seek to access. Businesses must supply secure defenses for AI integration operations combined with full compliance standards because operational efficiency requir

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Kotte, Girish. "AI-Powered Automated Incident Response in Healthcare Cybersecurity Operations." International Journal of All Research Education & Scientific Methods 13, no. 05 (2025): 3369–75. https://doi.org/10.56025/ijaresm.2025.1210243369.

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This research evaluates the implementation of "Artificial Intelligence (AI)" within the automation of the "incident response" within the "healthcare cybersecurity operations". It evaluates recent AI solutions utilized for the "realtime threat" identification alongside mitigation, and assesses their performance against the traditional manual approaches, alongside recognized ethical, operational, and technical issues hindering embracement. The research also offers effective recommendations for adequate AI development. Integrating AI-associated "automated incident response" improves overall "heal

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21

Sutanto, Yulius. "Cybersecurity Challenges and AI-Powered Mitigation Strategies in CCTV Surveillance Systems." International Journal of Information System and Innovative Technology 3, no. 2 (2024): 17–24. https://doi.org/10.63322/fsk65573.

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CCTV surveillance systems are essential for security and crime prevention but are increasingly vulnerable to cyber threats such as unauthorized access, data breaches, and deep-fake manipulations. Traditional security measures often fail against sophisticated attacks, necessitating advanced protection mechanisms. This study explores cybersecurity challenges in CCTV networks and proposes an intelligent mitigation framework to enhance security. The research analyses existing vulnerabilities, including malware attacks and data interception, highlighting gaps in current security measures. To addres

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Khan, Prottoy, Md Zahirul Islam, and Sazib Hossain. "AI-Powered Cybersecurity: Revolutionizing Business Threat Detection and Response." American Journal of Smart Technology and Solutions 4, no. 1 (2025): 37–48. https://doi.org/10.54536/ajsts.v4i1.4488.

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The modern day enterprise infrastructure needs cybersecurity as a crucial element to protect against increasing cyber threats that have multiplied because of digital business expansion. Security technologies that exist conventionally manage certain threats decently but lose their effectiveness when new forms of sophisticated cyberattacks emerge. Machine learning together with deep learning using anomaly detection methods enables Artificial Intelligence to function as an advanced security technology that boosts detection and response functions. The paper investigates how Artificial Intelligence

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Upasana, Ranjan Singh Ashish, Raj Ritik, Raj Ritik, and Singh Satyarth. "Next Gen: AI Powered ERP." Recent Innovations in Wireless Network Security 7, no. 2 (2025): 26–35. https://doi.org/10.5281/zenodo.15300471.

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<em>Enterprise resource planning (ERP) systems have become essential tools for organizations looking to streamline, integrate, and improve decision-making. The program explores the development and implementation of an ERP system based on the organization’s needs, using technologies such as artificial intelligence (AI) to improve operations. The ERP system is intended to integrate key processes such as resource management, financial operations, human resources, student management, and educational planning into a user-friendly platform at its core. AI-enabled features such as process autom

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Kulkarni,, Srushti. "AI Powered Contactless Fingerprint Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35013.

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This comprehensive review delves into the realm of AI-powered contactless fingerprint recognition. We trace its evolution from traditional methods to modern contactless approaches, highlighting the pivotal role of AI and machine learning. Key topics include the principles of contactless fingerprint data acquisition, challenges like environmental variations, and privacy concerns. We examine the state-of-the-art AI techniques such as deep learning and convolutional neural networks, showcasing how they enhance accuracy and robustness in contactless fingerprint recognition. The paper also explores

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C, Vivek. "AI-Powered Patient Case Similarity." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40833.

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The developed AI-powered Patient Case Similarity software, to be presented here, aims at enhancing clinical decision-making and outcomes in patient treatment. This is based on a machine learning approach utilizing the Random Forest method, with an extensive database that compares a patient's demographic data, symptoms, and medical history with cases similar to that. The clinicians would be able to retrieve the appropriate information as soon as possible and predict possible diseases to offer tailor-made treatment options. The software includes a chatbot interface for real-time patient interact

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Chadrack, Irabaruta, and Dr Nyesheja Muhire Enan. "AI Powered Network Traffic Detection." Journal of Information and Technology 5, no. 2 (2025): 53–65. https://doi.org/10.70619/vol5iss2pp53-65.

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This study presents an AI-powered network traffic detection framework capable of recognizing anomalies and addressing cyber threats in real-time. Traditional detection systems struggle to keep pace with evolving threats, necessitating more adaptive and intelligent approaches. To this end, the research integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models to enhance detection accuracy and operational efficiency. The framework is evaluated using benchmark datasets such as UNSW-NB15 and CICIDS2017, focusing on performance metrics including accuracy, precision, re

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Shravan Kumar Amjala. "AI-Powered Cloud Automation: A Scholarly Perspective." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 2664–72. https://doi.org/10.30574/wjaets.2025.15.2.0845.

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This article explores the transformative integration of artificial intelligence and machine learning into cloud infrastructure, creating a paradigm shift in enterprise IT operations. As organizations increasingly migrate to distributed cloud environments, the inherent complexity demands sophisticated automation beyond traditional manual capabilities. AI-powered cloud automation addresses these challenges through intelligent orchestration, predictive resource scaling, and autonomous optimization mechanisms. The synergistic relationship between AI and cloud technologies enables self-optimizing s

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Kumar, Manish. "AIRA : AI-Powered Code Review & Bug Detection System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42592.

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The increasing complexity of software develop- ment presents significant challenges for developers, including bug detection, code inefficiencies, and security vulnerabilities. Traditional methods of code review and debugging often result in increased workload and reduced productivity. To address these issues, AI-powered tools are emerging as a solution to enhance code quality, streamline development, and minimize human error. Introducing AIRA (AI-powered Intelligent Review Assistant), an advanced AI-driven code review and bug detection system designed to assist developers in improving code qua

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Siva Krishna Jampani. "Revolutionizing Penetration Testing: AI-Powered Automation for Enterprise Security." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1562–69. https://doi.org/10.32628/cseit241061201.

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This article explores the transformative impact of artificial intelligence and machine learning technologies on enterprise security through automated penetration testing frameworks. The article presents a comprehensive article analysis of an AI-powered penetration testing system, examining its architecture, implementation methodology, and performance metrics in real-world enterprise environments. The article findings demonstrate significant improvements in testing efficiency, with automated systems achieving superior vulnerability detection rates while substantially reducing testing time and r

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Ivan, Mishchenko. "Biometric Authentication in Android: Enhancing Security with AI-Powered Solutions." Asian Journal of Research in Computer Science 18, no. 4 (2025): 416–26. https://doi.org/10.9734/ajrcos/2025/v18i4629.

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Aims: This study aims to analyze biometric authentication methods on the Android platform, focusing on enhancing security through ready-to-use AI solutions. The research evaluates existing biometric authentication techniques, their vulnerabilities, and the application of AI-driven approaches to mitigate security risks. Study Design: This is a review and analytical study that examines current biometric authentication mechanisms, AI-based enhancements, and their impact on security and accuracy. Place and Duration of Study: The study is based on literature review and practical analysis of AI-enha

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Jyoti Bolannavar, Divyashree R, and Dr. Sumati Ramakrishna Gowda. "Intelligent Safety: Revolutionizing Home Security with AI and IoT." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 2319–33. https://doi.org/10.32628/cseit2410481.

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The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has revolutionized home security systems, addressing modern security challenges by providing intelligent, adaptive, and real-time measures. Unlike traditional systems that rely on passive sensors and manual intervention, AI-powered IoT systems leverage advanced machine learning algorithms and interconnected smart devices to predict, detect, and respond to potential threats autonomously. This integration ensures a proactive approach to security, enabling real-time monitoring, anomaly detection, and seamless communi

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Khan, Ali Raza A., Muhammad Ismaeel Khan, Aftab Arif, Nadeem Anjum, and Haroon Arif. "Intelligent Defense: Redefining OS Security with AI." International Journal of Innovative Research in Computer Science and Technology 13, no. 1 (2025): 85–90. https://doi.org/10.55524/ijircst.2025.13.1.13.

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The escalating complexity and sophistication of cyber threats necessitate a paradigm shift in operating system (OS) security. Traditional security measures, while effective against known vulnerabilities, struggle to adapt to dynamic attack vectors. This paper introduces Intelligent Defense, an innovative approach to OS security powered by Artificial Intelligence (AI). By integrating advanced machine learning algorithms and neural network architectures, Intelligent Defense transforms an operating system into an adaptive, self-learning security platform capable of identifying, predicting, and mi

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Asst., Prof. Shraddhha Kulkarni. "AI -Powered Digital Marketing and its Vulnerabilities: A Cybersecurity Analysis." International Journal of Advance and Applied Research S6, no. 23 (2025): 188–90. https://doi.org/10.5281/zenodo.15195020.

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<em>Artificial intelligence has revolutionized the cyber security sector by allowing businesses to expand and standardize antiquated safety protocols. AI can improve compliance and governance, improve vulnerability management, and offer more potent threat detection and response capabilities. Machine learning, natural language processing, behavioral analytics, and deep learning are examples of AI technologies that can improve cyber security defenses and offer protection against a variety of online dangers, including malware, phishing scams, and insider threats. There is discussion of the theore

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Gifia S, Carolin, and Indhumathi S. "Gen AI-Powered Signature Identifier and Image Manipulation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44457.

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The rise of digital transactions has significantly increased risks related to fraudulent digital signatures and identity impersonation across financial, legal, corporate, and online services. Traditional verification methods are often manual, time-consuming, and prone to inaccuracies, making them vulnerable to sophisticated forgeries. AI-driven solutions leveraging Deep Learning and Generative Adversarial Networks (GANs) provide a transformative approach to automating digital signature verification and identity authentication. These models compare a user’s uploaded image with their registered

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Nze, Stella Udoka. "AI-Powered Chatbots." Global Journal of Human Resource Management 12, no. 6 (2024): 34–45. http://dx.doi.org/10.37745/gjhrm.2013/vol12n63445.

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Artificial Intelligence (AI)-powered chatbots have emerged as a transformative technology, fundamentally changing how businesses and organizations engage with their customers by providing real-time, personalized communication. These chatbots, driven by sophisticated algorithms, utilize Natural Language Processing (NLP) and Machine Learning (ML) to understand, interpret, and respond to human language in a manner that is contextually appropriate and relevant. As a result, AI-powered chatbots enhance both user experience and operational efficiency by automating routine interactions, reducing resp

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Harutyunyan, Gayane, Gyulnara Danielyan, and Khachatur Ghazeyan. "The effectiveness of ai-powered weapons from the standpoint of strategic decision-making (Case of Armenia)." International Journal of Innovative Research and Scientific Studies 8, no. 2 (2025): 2222–31. https://doi.org/10.53894/ijirss.v8i2.5650.

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The study explores the effectiveness and economic efficiency of AI-powered “smart” weapons production. It seeks to determine whether small countries facing significant security threats should allocate funds intended for arms imports toward developing an indigenous defense industry. This study employs a comprehensive analysis to evaluate key factors influencing the cost-effectiveness of AI-based weapons production. It separately examines the impact of AI-powered weapons in two scenarios: (1) importation and application and (2) domestic production. The analysis assesses their effects on national

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Sibin, Thomas. "AI-Powered Home Safety: The Next Generation of Security Systems." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 7, no. 2 (2019): 1–5. https://doi.org/10.5281/zenodo.14951146.

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This paper looks at how home security systems have changed over time, focused on the rise of smart video surveillance systems that have advanced features like AI-powered object detection, motion detection, and facial recognition. Traditional security cams mostly relied on passive surveillance, which didn't give much information and usually needed to be watched by a person all the time. Modern home security cams, on the other hand, use cutting-edge technologies to offer proactive security, including real-time alerts, automated event recording, and custom security measures.This paper highlights

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Krishnan, Mahendhiran. "API C4E Augmentation: AI-Powered Agent(AIPA) Framework." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 988–95. http://dx.doi.org/10.22214/ijraset.2024.65267.

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Abstract: In today’s rapidly evolving digital landscape, organizations increasingly rely on Application Programming Interface known as API for seamless integration and data exchange. API providers comprising consumers, developers, and project teams face several challenges in discovering, developing and mapping APIs in compliance with organizational enterprise architecture principles. This paper aims to address these challenges by proposing an AI-Powered Agent (AIPA) Framework that leverages Generative AI and AI Code Assistant tools to enhance API governance and streamline the API development c

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Sunday Adeola Oladosu, Adebimpe Bolatito Ige, Christian Chukwuemeka Ike, Peter Adeyemo Adepoju, Olukunle Oladipupo Amoo, and Adeoye Idowu Afolabi. "Next-generation network security: conceptualizing a Unified, AI-Powered Security Architecture for Cloud-Native and On-Premise Environments." International Journal of Science and Technology Research Archive 3, no. 2 (2022): 270–80. https://doi.org/10.53771/ijstra.2022.3.2.0143.

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The increasing complexity and interconnectivity of modern IT infrastructures, including both cloud-native and on-premise environments, present significant challenges for traditional network security models. As organizations adopt hybrid cloud architectures and expand their reliance on cloud-native technologies, ensuring robust security across diverse environments becomes essential. This review proposes a conceptual framework for next-generation network security, centered around a unified, AI-powered architecture that seamlessly integrates cloud-native and on-premise systems. By leveraging arti

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Thomas Aerathu Mathew. "AI-powered threat detection: Strengthening data platform security with LLMs." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 387–93. https://doi.org/10.30574/wjarr.2025.26.2.1604.

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This article explores how Large Language Models (LLMs) revolutionize data platform security by leveraging advanced metadata analytics for threat detection and mitigation. As organizations face increasingly complex security challenges in hybrid cloud environments, LLMs offer a paradigm shift in security approaches through their ability to analyze vast amounts of metadata, identify anomalous patterns, and correlate seemingly unrelated events across system layers. The article examines how these AI systems enhance real-time threat detection capabilities by identifying unusual access behaviors, pri

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B, Vivekanandam. "Surveillance 5.0: Next-Gen Security Powered by Quantum AI Optimization." June 2024 3, no. 1 (2024): 113–24. http://dx.doi.org/10.36548/rrrj.2024.1.008.

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Surveillance 5.0, powered by Quantum AI Optimization, represents the highpoint of next-generation security, transforming traditional surveillance paradigms through the fusion of quantum-powered technologies and advanced artificial intelligence. Quantum AI Optimization stands as the essential, revolutionizing security operations for enabling real-time threat detection, proactive response approaches, and adaptive risk mitigation measures. Moreover, privacy preservation and ethical governance plays a major role in ensuring that surveillance activities maintain higher security and privacy rights.

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Chetan Prakash Ratnawat. "AI-Powered Financial Reporting Chatbots: Transforming Insurance Industry Operations." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1779–86. https://doi.org/10.32628/cseit241061222.

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This comprehensive article examines the transformative impact of AI-powered financial chatbots in the insurance industry, focusing on the evolution from traditional manual processes to automated solutions. The article investigates technical architecture, role-specific functionality, security frameworks, and performance analytics across major insurance organizations worldwide. Through extensive research and analysis, this article demonstrates how intelligent automation addresses traditional inefficiencies in insurance operations while enhancing data accuracy, improving security protocols, and d

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Usta, Uygar, Sumer Erkan Kaya, and Savas Barış. "Using AI-Powered Vehicle Identification System in Gas Stations (AI-VIS)." Orclever Proceedings of Research and Development 3, no. 1 (2023): 255–63. http://dx.doi.org/10.56038/oprd.v3i1.330.

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In many countries around the world, retail fuel sales have to be recorded and monitored with specific vehicle information such as license plate by government institutions and station managers. Different hardware methods are utilized to achieve this goal such as UHF (Ultra high frequency) vehicle identification tags installed on the vehicles. To extract data from the tags, RFID-UHF antennas need to be installed on the nozzle for the recognition of vehicles today, which implies an increase in hardware costs per vehicle. Additionally, the electronic waste generated by the hardware used for vehicl

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Reddy Gopireddy, Ravindar. "AI-Powered Security in Cloud Environments: Enhancing Data Protection and Threat Detection." International Journal of Science and Research (IJSR) 10, no. 11 (2021): 1568–72. http://dx.doi.org/10.21275/sr24731135001.

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Garg, Chanchal. "AI-Powered Talent Acquisition Platform." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47414.

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Abstract -The fast-paced changing job market creates serious challenges in talent attraction, requiring more effective and data-centric methods to automate the recruitment process. This paper introduces JobPathway, a full-fledged MERN stack application to maximize talent attraction using AI-driven resume parsing and job and profile reminder personalization. Utilizing sophisticated machine learning algorithms, JobPathway processes candidate profiles, identifies them with suitable job openings, and provides timely alerts in order to increase interactions and avoid lost opportunities. Further, th

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Biju, Ashwin, Abijith K, and Mrs Sajitha A S. "Secure Flow AI-Powered Redirection Blocker for Safe Browsing." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44339.

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SecureFlow is a browser extension developed to enhance online security by preventing malicious redirections, phishing attempts, and tracking scripts. The system ensures safe browsing by using AI- powered threat analysis and third-party security APIs, including Google Safe Browsing. It provides real-time notifications, maintains a comprehensive history of blocked threats, and supports user customization through whitelisting and history management. The Admin Panel monitors browsing activities and maintains system settings. The Security Engine handles detection and prevention of harmful URLs usin

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Ayush, Kumar Jha Shahi Raza Khan. "AI-Powered Context-Aware Blockchain Explorer." Career Point International Journal of Research(CPIJR) 1, no. 4 (2025): 53–72. https://doi.org/10.5281/zenodo.15137907.

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The rapid evolution of blockchain technology necessitates advanced tools for efficient exploration and analysis of distributed ledger data. An <strong>AI-Powered Context-Aware Blockchain Explorer</strong> enhances traditional blockchain explorers by integrating artificial intelligence to provide contextual insights, anomaly detection, and predictive analytics. This system leverages<strong> </strong><strong>natural language processing (NLP)</strong><strong> </strong>and<strong> </strong><strong>machine learning algorithms</strong><strong> to </strong>enable intelligent querying, pattern recogni

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Olubusola Odeyemi, Chinwe Chinazo Okoye, Onyeka Chrisanctus Ofodile, Omotayo Bukola Adeoye, Wilhelmina Afua Addy, and Adeola Olusola Ajayi-Nifise. "INTEGRATING AI WITH BLOCKCHAIN FOR ENHANCED FINANCIAL SERVICES SECURITY." Finance & Accounting Research Journal 6, no. 3 (2024): 271–87. http://dx.doi.org/10.51594/farj.v6i3.855.

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Integrating artificial intelligence (AI) with blockchain technology presents a transformative approach to enhancing security in financial services. This fusion leverages the strengths of both AI and blockchain to mitigate various security risks, including fraud, data breaches, and identity theft, thereby bolstering trust and confidence in financial transactions. This abstract explores the synergies between AI and blockchain, highlighting their combined capabilities, applications, and potential benefits for the financial services industry. AI algorithms, including machine learning and natural l

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Varma, Jahith Sai Krishna. "EagleAI: AI Powered Real Time Restricted Area Surveillance." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 3499–506. https://doi.org/10.22214/ijraset.2025.70612.

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Abstract: Traditional security measures often fail to provide accurate and efficient monitoring, leading to vulnerabilities in restricted areas. This project implements an advanced real-time facial recognition-based surveillance system to enhance security and address these shortcomings. The system uses facial recognition technology for live monitoring, identifying authorized personnel and detecting unauthorized individuals. Attendance is recorded automatically in an Excel file, with timestamps for entry and exit. For unauthorized access, the system triggers multiple actions, including capturin

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Ayomide, Oluwaromika Olukoya, Asiimire Shallon, and Refus Adigun Damilare. "Evaluating the Effectiveness of AI-Powered Cloud Based Threat Intelligence in Mitigating Phishing Attacks." International Journal of Innovative Science and Research Technology (IJISRT) 10, no. 1 (2025): 855–63. https://doi.org/10.5281/zenodo.14737744.

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Phishing attacks remain a critical cyber security threat, with attackers continually refining their tactics to bypass traditional defense systems. This study evaluates the effectiveness of AI-powered cloud-based threat intelligence in mitigating phishing attacks, focusing on key metrics such as phishing detection accuracy, false positive rates, and incident response times. The research analyzes phishing  data from multiple organizations across diverse sectors, including finance, healthcare, and e-commerce, which have deployed AI- driven threat intelligence platforms. The study concludes t

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