Browsing by Author "Qadir, Junaid"
Now showing items 1-6 of 6
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Consistent Valid Physically-Realizable Adversarial Attack Against Crowd-Flow Prediction Models
( IEEE , 2024 , Article)Recent works have shown that deep learning (DL) models can effectively learn city-wide crowd-flow patterns, which can be used for more effective urban planning and smart city management. However, DL models have been known ... -
How to program autonomous vehicle (AV) crash algorithms: an Islamic ethical perspective
( Emerald Publishing Limited , 2023 , Article)Purpose: Fully autonomous self-driving cars not only hold the potential for significant economic and environmental advantages but also introduce complex ethical dilemmas. One of the highly debated issues, known as the ... -
Jamming Detection in IoT Wireless Networks: An Edge-AI Based Approach
( ACM Digital Library , 2022 , Conference)Wireless enabling technologies in critical infrastructures are increasing the efficiency of communications. In the era of 5G and beyond, more technologies will be allowed to connect to mobile networks, enabling the Internet ... -
Navigating Privacy Challenges in the Metaverse: A Comprehensive Examination of Current Technologies and Platforms
( IEEE , 2024 , Article)The metaverse's rise brings unique privacy challenges. While existing research has broadly surveyed security and privacy in this domain, our article provides a targeted analysis of user privacy within notable VR/MR devices ... -
Pathway to Prosocial AI-XR Metaverses: A Synergy of Technical and Regulatory Approaches
( IEEE , 2023 , Conference)AI-XR metaverses leverage artificial intelligence (AI) and extended reality (XR) technology to create immersive environments that replicate and enhance the real world. The transformative impact of the metaverse as an ... -
Trust-Based Cloud Machine Learning Model Selection for Industrial IoT and Smart City Services
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)With machine learning (ML) services now used in a number of mission-critical human-facing domains, ensuring the integrity and trustworthiness of ML models becomes all important. In this work, we consider the paradigm where ...
