IECE - Institute of Emerging and Computer Engineers

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    Author 2
    ORCID
    0009-0008-7612-2211
    Babar Zeb
    National University of Science and Tecnology
    Summary
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    2
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    Free Access | Review Article | 04 January 2025
    Futuristic Metaverse: Security and Counter Measures
    by
    Nidhi Ramolia
    ,
    Pranav Piyushbhai Tank
    ,
    Ravikumar R N
    ,
    Babar Zeb
    ,
    Manish Kumar
    ,
    Sushil Kumar Singh
    IECE Transactions on Intelligent Systematics | Volume 2, Issue 1: 49-65, 2025 | DOI:10.62762/TIS.2024.194631
    Abstract
    This paper presents a comprehensive analysis of the security and privacy challenges in the Metaverse, introducing a novel framework for evaluating and addressing these emerging threats. Our research makes three key contributions: (1) a systematic classification of Metaverse-specific security vulnerabilities across interconnected virtual and physical environments, (2) a framework for assessing privacy risks in AR/VR-enabled social interactions, and (3) targeted solutions for securing blockchain-based digital assets and identity management in the Metaverse. Our analysis highlights how traditional cybersecurity approaches must evolve to address the unique challenges posed by the fusion of physi... More >
    Graphical Abstract
    Futuristic Metaverse: Security and Counter Measures
    Free Access | Review Article | 09 November 2024 | Cited: 1
    Comprehensive Evaluation of Artificial Intelligence Applications in Forensic Odontology: A Systematic Review and Meta-Analysis
    by
    Muhammad Salman Khan
    ,
    Urooj Afridi
    ,
    Muhammad Jamal Ahmed
    ,
    Babar Zeb
    ,
    Irfan Ullah
    ,
    Muhammad Zain Hassan
    IECE Transactions on Intelligent Systematics | Volume 1, Issue 3: 176-189, 2024 | DOI:10.62762/TIS.2024.818917
    Abstract
    This systematic review and meta-analysis examine the transformative impact of artificial intelligence (AI) applications on forensic odontology, specifically focusing on the enhancement of identification accuracy and operational efficiency. Traditionally, forensic odontology depends on detailed dental records for human identification purposes. However, with the integration of AI-driven advancements, including machine learning algorithms and image recognition systems, the field is undergoing significant evolution. These AI technologies offer notable improvements in the precision of complex tasks such as bite mark analysis, dental age estimation, and dental record matching, while simultaneously... More >
    Graphical Abstract
    Comprehensive Evaluation of Artificial Intelligence Applications in Forensic Odontology: A Systematic Review and Meta-Analysis