Nauman Aslam
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View article: Detection of AI generated images using combined uncertainty measures and particle swarm optimised rejection mechanism
Detection of AI generated images using combined uncertainty measures and particle swarm optimised rejection mechanism Open
As AI-generated images become increasingly photorealistic, distinguishing them from natural images poses a growing challenge. This paper presents a robust detection framework that leverages multiple uncertainty measures to decide whether t…
View article: Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks
Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks Open
View article: Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks
Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks Open
View article: A Swarm Path Decision-making Method for Intelligent Connected Vehicles at Consecutive Signalized Intersections
A Swarm Path Decision-making Method for Intelligent Connected Vehicles at Consecutive Signalized Intersections Open
View article: Unraveling the Smart Charging Technologies, Energy Sources, and Regulatory Standards for EVs
Unraveling the Smart Charging Technologies, Energy Sources, and Regulatory Standards for EVs Open
Electric vehicles (EVs) are anticipated to be pivotal contributors to the global energy transformation in the automobile industry, ignited by their rapid proliferation. However, the widespread integration of EVs requires rigorous research …
View article: A Trustworthy and Untraceable Centralised Payment Protocol for Mobile Payment
A Trustworthy and Untraceable Centralised Payment Protocol for Mobile Payment Open
Current mobile payment schemes gather detailed information about purchases customers make. This data can then be used to infer a customer’s spending behaviour, potentially violating their privacy. To tackle this problem, we propose an untr…
View article: Reinforcement Learning for EV Fleet Smart Charging with On-Site Renewable Energy Sources
Reinforcement Learning for EV Fleet Smart Charging with On-Site Renewable Energy Sources Open
In 2020, the transportation sector was the second largest source of carbon emissions in the UK and in Newcastle upon Tyne, responsible for about 33% of total emissions. To support the UK’s target of reaching net zero emissions by 2050, ele…
View article: Bridge to Real Environment with Hardware-in-the-loop for Wireless Artificial Intelligence Paradigms
Bridge to Real Environment with Hardware-in-the-loop for Wireless Artificial Intelligence Paradigms Open
Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared…
View article: Optimizing QoS in HD Map Updates: Cross-Layer Multi-Agent with Hierarchical and Independent Learning
Optimizing QoS in HD Map Updates: Cross-Layer Multi-Agent with Hierarchical and Independent Learning Open
The data collected by autonomous vehicle (AV) sensors such as LiDAR and cameras is crucial for creating high-definition (HD) maps to provide higher accuracy and enable a higher level of automation. Nevertheless, offloading this large volum…
View article: Multi-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network
Multi-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network Open
Reinforcement Learning (RL) algorithms have been used to address the challenging problems in the offloading process of vehicular ad hoc networks (VANET). More recently, they have been utilized to improve the dissemination of high-definitio…
View article: Coverage-Aware and Reinforcement Learning Using Multi-Agent Approach for HD Map QoS in a Realistic Environment
Coverage-Aware and Reinforcement Learning Using Multi-Agent Approach for HD Map QoS in a Realistic Environment Open
One effective way to optimize the offloading process is by minimizing the\ntransmission time. This is particularly true in a Vehicular Adhoc Network\n(VANET) where vehicles frequently download and upload High-definition (HD) map\ndata whic…
View article: Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning
Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning Open
High-definition (HD) Map systems will play a pivotal role in advancing autonomous driving to a higher level, thanks to the significant improvement over traditional two-dimensional (2D) maps. Creating an HD Map requires a huge amount of on-…
View article: Deep reinforcement learning based Evasion Generative Adversarial Network for botnet detection
Deep reinforcement learning based Evasion Generative Adversarial Network for botnet detection Open
View article: Enhancing Small Medical Dataset Classification Performance Using GAN
Enhancing Small Medical Dataset Classification Performance Using GAN Open
Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The researc…
View article: Data-Driven EV Charging Load Forecasting and Smart Charging
Data-Driven EV Charging Load Forecasting and Smart Charging Open
Electrical Vehicles (EVs) have been proposed as a solution for decarbonizing road transport. Smart charging is essential to coordinate EV energy demand with the requisite peak power supply. The performance of smart charging highly depends …
View article: Void Avoiding Opportunistic Routing Protocols for Underwater Wireless Sensor Networks: A Survey
Void Avoiding Opportunistic Routing Protocols for Underwater Wireless Sensor Networks: A Survey Open
One of the most challenging issues in the routing protocols for underwater wireless sensor networks (UWSNs) is the occurrence of void areas (communication void). That is, when void areas are present, the data packets could be trapped in a …
View article: Deep reinforcement learning-based long-range autonomous valet parking for smart cities
Deep reinforcement learning-based long-range autonomous valet parking for smart cities Open
In this paper, to reduce the congestion rate at the city center and increase the traveling quality of experience (QoE) of each user, the framework of long-range autonomous valet parking is presented. Here, an Autonomous Vehicle (AV) is dep…
View article: AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems
AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems Open
View article: A Novel Approach to Improve the Adaptive-Data-Rate Scheme for IoT LoRaWAN
A Novel Approach to Improve the Adaptive-Data-Rate Scheme for IoT LoRaWAN Open
The long-range wide-area network (LoRaWAN) uses the adaptive-data-rate (ADR) algorithm to control the data rate and transmission power. The LoRaWAN ADR algorithm adjusts the spreading factor (SF) to allocate the appropriate transmission ra…
View article: Deep Reinforcement Learning based Evasion Generative Adversarial Network for Botnet Detection
Deep Reinforcement Learning based Evasion Generative Adversarial Network for Botnet Detection Open
Botnet detectors based on machine learning are potential targets for adversarial evasion attacks. Several research works employ adversarial training with samples generated from generative adversarial nets (GANs) to make the botnet detector…
View article: Physical Activity Monitoring and Classification Using Machine Learning Techniques
Physical Activity Monitoring and Classification Using Machine Learning Techniques Open
Physical activity plays an important role in controlling obesity and maintaining healthy living. It becomes increasingly important during a pandemic due to restrictions on outdoor activities. Tracking physical activities using miniature we…
View article: A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations
A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations Open
Due to recent developments in electric mobility, public charging infrastructure will be essential for modern
\ntransportation systems. As the number of electric vehicles
\n(EVs) increases, the public charging infrastructure needs to
\nadop…
View article: An Investigation on Fragility of Machine Learning Classifiers in Android Malware Detection
An Investigation on Fragility of Machine Learning Classifiers in Android Malware Detection Open
Machine learning (ML) classifiers have been increasingly used in Android malware detection and countermeasures for the past decade. However, ML-based solutions are vulnerable to adversarial evasion attacks. An attacker can craft a maliciou…
View article: Towards On-Device AI and Blockchain for 6G enabled Agricultural Supply-chain Management
Towards On-Device AI and Blockchain for 6G enabled Agricultural Supply-chain Management Open
6G envisions artificial intelligence (AI) powered solutions for enhancing the quality-of-service (QoS) in the network and to ensure optimal utilization of resources. In this work, we propose an architecture based on the combination of unma…
View article: A Local Differential Privacy based Hybrid Recommendation Model with BERT and Matrix Factorization
A Local Differential Privacy based Hybrid Recommendation Model with BERT and Matrix Factorization Open
Many works have proposed integrating sentiment analysis with collaborative filtering algorithms to improve the accuracy of recommendation systems. As a result, service providers collect both reviews and ratings, which is increasingly causi…
View article: Private and Utility Enhanced Recommendations With Local Differential Privacy and Gaussian Mixture Model
Private and Utility Enhanced Recommendations With Local Differential Privacy and Gaussian Mixture Model Open
Recommendation systems rely heavily on users behavioural and preferential data (e.g. ratings, likes) to produce accurate recommendations. However, users experience privacy concerns due to unethical data aggregation and analytical practices…
View article: Learning-Based Path Planning for Long-Range Autonomous Valet Parking.
Learning-Based Path Planning for Long-Range Autonomous Valet Parking. Open
In this paper, to reduce the congestion rate at the city center and increase the quality of experience (QoE) of each user, the framework of long-range autonomous valet parking (LAVP) is presented, where an Electric Autonomous Vehicle (EAV)…
View article: Deep Reinforcement Learning-Based Long-Range Autonomous Valet Parking for Smart Cities
Deep Reinforcement Learning-Based Long-Range Autonomous Valet Parking for Smart Cities Open
In this paper, to reduce the congestion rate at the city center and increase the quality of experience (QoE) of each user, the framework of long-range autonomous valet parking (LAVP) is presented, where an Autonomous Vehicle (AV) is deploy…
View article: EVAGAN: Evasion Generative Adversarial Network for Low Data Regimes
EVAGAN: Evasion Generative Adversarial Network for Low Data Regimes Open
A myriad of recent literary works has leveraged generative adversarial networks (GANs) to generate unseen evasion samples. The purpose is to annex the generated data with the original train set for adversarial training to improve the detec…
View article: Void Avoidance Opportunistic Routing Protocol for Underwater Wireless Sensor Networks
Void Avoidance Opportunistic Routing Protocol for Underwater Wireless Sensor Networks Open
Much attention has been focused lately on the Opportunistic Routing technique (OR) that can overcome the restrictions of the harsh underwater environment and the unique structures of the Underwater Sensor Networks (UWSNs). OR enhances the …