
Ali Kashif BashirManchester Metropolitan University | MMU · Computing and Mathematics
Ali Kashif Bashir
PhD
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413
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Introduction
Publications
Publications (413)
Cognitive networks with the integration of smart and physical devices are rapidly utilized for the development of smart cities. They are explored by many real-time applications such as smart homes, healthcare, safety systems, and other unpredictable environments to gather data and process network requests. However, due to the external conditions an...
In the increasingly digitized world, the privacy and security of sensitive data shared via IoT devices are paramount. Traditional privacy-preserving methods like k-anonymity and ldiversity are becoming outdated due to technological advancements. In addition, data owners often worry about misuse and unauthorized access to their personal information....
With the rapid evolution toward data-intensive applications and sustainable urban mobility, upcoming sixth-generation (6G) wireless networks must deliver enhanced coverage, high spectral efficiency, and energy optimization across densely populated areas. However, achieving these requirements poses significant challenges due to the dynamic nature of...
The demand for real-time, high-quality services (QoS) is increasing with the proliferation of the resource-constrained nature of edge devices that facilitate the Internet of Things (IoT) and wireless sensor network (WSN) applications. Several existing multi-objective algorithms, such as MOPSO, Elitism MOGA, MODE, and others, are capable of balancin...
The Internet of Vehicles (IoV) presents significant opportunities for enhancing traffic management and vehicle coordination, but it also faces challenges related to traffic congestion, data privacy, and efficient computational resource allocation. Traffic congestion remains a critical problem, impacting travel time, fuel consumption, and emissions....
Ensuring the smooth operation of road traffic is a momentous target in Intelligent Transportation Systems, which can be expedited by a secure and reliable Internet of Vehicles (IoV). As prominent carriers of the IoV, intelligent vehicles (IVs), that bear the promising potential for alleviating traffic congestion, have become the core road traffic p...
Given the severity of air pollution, air quality monitoring has become a crucial aspect of Artificial Intelligence of Things (AIoT) applications, providing essential information for forecasting air pollution. However, the training process for air quality monitoring models heavily relies on high-performance computing resources, leading to significan...
The technology of the Internet of Vehicles (IoV) and digital twins (DTs) is driving deeper connectivity between vehicles and road infrastructure. Through the data exchange of IoV and the simulation of DT technology, vehicle driving decisions, traffic management, and road planning are optimized. However, DT models contain a large amount of private v...
The rise of e-commerce and the adoption of cloud servers have revolutionized retail by providing greater convenience and selection to online shoppers. However, personalizing the customer experience also poses important challenges regarding privacy, security, and trust. To tackle this issue, the public key encryption with equality test (PKEET) is em...
Consumer electronics products are widely used in the agricultural field, but traditional consumer electronics products are limited to specific environmental applications and are susceptible to external attacks. The next generation of imaging technology is driving the widespread application of electronic consumer products. We propose a novel multi-s...
Recently, there has been a rise in the use of Unmanned Areal Vehicles (UAVs) in consumer electronics, particularly for the critical situations. Internet of Things (IoT) technology and the accessibility of inexpensive edge computing devices present novel prospects for enhanced functionality in various domains through the utilization of IoT-based UAV...
In this study, we predict inventory for an IoT-enabled vending machine warehouse servicing approximately 1,500 vending machines with the goal of timely replenishing, achieving cost effectiveness, reducing stock waste, optimising the available resources and ensuring fulfilment of consumer demand. The study deploys four different ML algorithms, namel...
The increase in popularity of vehicles encourages the development of smart cities. With this advancement, vehicular ad-hoc networks, or VANETs, are now frequently utilized for inter-vehicular communication to gather data regarding traffic congestion, vehicle location, speed, and road conditions. Such a public network is open to various security ris...
Digital Twin for Vehicular Networks (DTVN) continuously simulates and optimizes vehicle behaviors to support emerging 6G Internet-of-Vehicle (IoV) applications such as DT-assisted autonomous driving. To meet Quality of Service (QoS), resource scheduling for distributed vehicle DTs is carried out. However, existing works mainly respond to service de...
The Internet of Medical Things (IoMT) and Artificial Intelligence (AI) models have transformed healthcare by enabling wireless communication for Remote Patient Health Monitoring (RPHM) services. Wireless technologies such as Wi-Fi and 6G support reliable and low-latency communication between AI models and IoMT devices. IoMT devices allow individual...
The COVID-19 pandemic has disrupted people’s lives and caused significant economic damage around the world, but its impact on people’s mental health has not been paid due attention by the research community. According to anecdotal data, the pandemic has raised serious concerns related to mental health among the masses. However, no systematic invest...
Development in internet technology made consumer electronics growth to another extent where several consumers from all over the world utilize various essentials through recent development. However, consumer electronics based devices could be vulnerable to cyber attacks if it is not appropriately secured. In this research work, we proposed AI-enable...
Unmanned aerial vehicles (UAVs) with AI-enabled logistics are gradually demonstrating their special benefits for upcoming smart cities. However, current research on logistics UAV path planning fails to take into account the limits on UAV energy consumption, customer time windows, and the effects of wind direction and speed at the same time. As a re...
Deep learning (DL) is increasingly recognized for its effectiveness in analyzing and forecasting complex economic systems, particularly in the context of Pakistan's evolving economy. This paper investigates DL's transformative role in managing and interpreting increasing volumes of intricate economic data, leading to more nuanced insights. DL model...
The unforeseen events of natural disasters often devastate critical infrastructure and disrupt communication. The use of unmanned aerial vehicles (UAVs) in emergency response scenarios offers significant potential for delivering real-time information and assisting emergency response efforts. However, challenges such as physical barriers to communic...
Graph contrastive learning (GCL) aims to contrast positive-negative counterparts to learn the node embeddings, whereas graph data augmentation methods are employed to generate these positive-negative samples. The variation, quantity, and quality of negative samples compared to positive samples play crucial roles in learning meaningful embeddings fo...
Artificial intelligence (AI) is on the verge of reshaping the healthcare and biomedical sectors, presenting unparalleled prospects for improved patient care. As we embark on this transformational path, incorporating AI algorithms into healthcare systems presents intricate issues in terms of privacy and security. This special issue is dedicated to e...
The concept of smart houses has grown in prominence in recent years. Major challenges linked to smart homes are identification theft, data safety, automated decision-making for IoT-based devices, and the security of the device itself. Current home automation systems try to address these issues but there is still an urgent need for a dependable and...
The widespread use of cloud storage enables users to access their resources remotely via a self-service model. Utilizing pay-per-use storage services provided by cloud service providers (CSPs) requires users to commit financially to their resources. This paper introduces an SCS framework that provides a secure architecture for cloud storage using a...
In the next generation of consumer electronics, bitcoin mixing scheme is an essential part to realize decentralized anonymous payment. However, there are still some challenges in existing decentralized schemes. First, existing schemes necessitate broadcast of sensitive information for group construction and lack of machine learning models to make a...
With the rising adoption of Tactile Internet-driven Consumer Healthcare IoT, ensuring the security and reliability of sensitive healthcare data has become a paramount concern. Threat detection and mitigation in such dynamic and critical environments pose unique challenges. In this context, the main focus of this research is to propose a novel model...
In the colloquy concerning human rights, equality, and human health, mental illness and therapy regarding mental health have been condoned. Mental disorder is a behavioral motif that catalyzes the significant anguish or affliction of personal functioning. The symptoms of a mental disorder may be tenacious, degenerative, or transpire as a single epi...
Distributed learning empowers social media platforms to handle massive data for image sentiment classification and deliver intelligent services. However, with the increase of privacy threats and malicious activities, three major challenges are emerging: securing privacy, alleviating straggler problems, and mitigating Byzantine attacks. Although rec...
This paper explores how deep learning enhances Internet of Things (IoT) cybersecurity, examining advanced methods like convolutional and recurrent neural networks for detailed IoT data analysis. It highlights the importance of real-time threat detection and classification, focusing on innovative Graph Neural Networks and Transformer Models for bett...
Ensuring robustness against adversarial attacks is imperative for Machine Learning (ML) systems within the critical infrastructures of the Industrial Internet of Things (IIoT). This paper addresses vulnerabilities in IIoT systems, particularly in distributed environments like Federated Learning (FL) by presenting a resilient framework - Secure Fede...
The advent of 6G-enabled networks marks a transformative era in the Internet of Things (IoT), promising unparalleled connectivity and innovation. These networks are set to revolutionize the IoT landscape by offering remarkable capabilities, including ultra-high data speeds, ultra-low latency, and extensive network coverage and connectivity. However...
The Consumer Internet of Things (CIoT) integrates the advantage of Internet of Things (IoT) technologies to provide convenience in consumers’ daily lives. With the rapid development of the CIoT, data collected from consumer smart devices has increased exponentially. In the CIoT, web pages, as internet information carriers, offer spammers opportunit...
Le Yu Lina Wang Jijing Cai- [...]
Wei Wang
As consumer electronics become more ubiquitous and Generative Artificial Intelligence (GenAI) technologies advance rapidly, processing and analyzing semantic information collected from users to enhance their experiences becomes especially important. Traditionally, monitoring students' educational and psychological health has relied primarily on tea...
The terahertz band, spanning from 100 GHz to 10 THz, has garnered significant attention for its potential to support ultra-high transmissions. Moreover, the Internet of Nano Things (IoNT) offers efficient data collection and analysis mechanisms to optimize nano systems performance for enhance users' experiences and comfort in daily life. In this pa...
The use of 3D point clouds (3DPCs) in deep learning (DL) has recently gained popularity due to several applications in fields such as computer vision, autonomous systems, and robotics. DL, as a dominant artificial intelligence approach, has been effectively applied to handle a variety of 3D vision challenges. However, building strong discriminative...
Pine Wilt Disease (PWD) poses a severe threat to the health of pine trees and has resulted in substantial losses to global pine forest resources. Due to the minute size of the pathogens and the concealed symptoms of PWD, early detection through remote sensing image technology is essential. However, in practical applications, remote sensing images a...
With the rapid development of distributed edge intelligence (DEI) within Internet of vehicle (IoV) network, it is required to support heterogeneous rapid, reliable and lightweight authentication which prevents eavesdropping, tampering and replay attacks. Radio Frequency Fingerprinting (RFF), which leverages unique and tamper-proof hardware characte...
Routing protocol for low-power and lossy network (RPL) is a routing protocol for resource-constrained Internet of Things (IoT) network devices. RPL has become a widely adopted protocol for routing in low-powered device networks. However, it lacks essential security features, including end-to-end security, robust authentication, and intrusion detect...
The heterogeneous environment of next-generation Consumer Internet of Things (CIoT) demands efficient resource utilization and reliable network services. On the contrary, the proliferation in the diverse nature of smart consumer IoT devices is causing spectrum scarcity and uneven utilization of available resources. Cognitive Radios (CRs) provide th...
Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles (IoV). However, intricate security challenges are intertwined with technological progress: Vehicular ad hoc Networks (VANETs), a core component of IoV, face security issues, particularly the Black Hole Attack (BHA). This malicious at...
Medical imaging informatics play an important role in the effectiveness of present-day healthcare systems. Advancement of artificial intelligence, big data analytics, and internet of things technologies contribute greatly to various healthcare applications. Artificial intelligence techniques are contributing to improvements with traditionally human...
Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves as a prevalent diagnostic tool in prenatal care for monitoring fetal growth and development. Nevertheless, acq...
Article citation creates a link between the cited and citing articles and is used as a basis for several parameters like author and journal impact factor, H-index, i10 index, etc ., for scientific achievements. Citations also include self-citation which refers to article citation by the author himself. Self-citation is important to evaluate an auth...
Intelligent health monitoring systems are becoming more important and popular as technology advances. Nowadays, online services are replacing physical infrastructure in several domains including medical services as well. The COVID-19 pandemic has also changed the way medical services are delivered. Intelligent appliances, smart homes, and smart med...
Network Function Virtualization (NFV) is an approach to virtualizing network services that traditionally run on proprietary hardware, such as firewalls, routers, and load balancers. The NFV cloud is a data center network built to host, deploy, and service Virtual Network Functions (VNFs). Currently, the Virtualized Infrastructure Manager (VIM) spen...
The need for networking in smart industries known as Industry 5.0 has grown critical, and it is especially important for the security and privacy of the applications. To counter threats to important consumers devices’ sensitive data, various applications of smart industries require intelligent schemes and architectures. The data which is recorded a...
The rapid growth and increasing demand for Internet of Things (IoT) devices in our everyday lives create exciting opportunities for human involvement, data integration, and seamless automation. This fully interconnected ecosystem considerably impacts crucial aspects of our lives, such as transportation, healthcare, energy management, and urban infr...
Due to its simple installation and connectivity, the internet of things (IoT) is susceptible to malware attacks. As IoT devices have become more prevalent, they have become the most tempting targets for malware. In this chapter, the authors propose a novel detection and analysis method that harnesses the power and simplicity of decision trees. The...
Predicting attacks in Android malware devices using machine learning for recommender systems-based IoT can be a challenging task. However, it is possible to use various machine-learning techniques to achieve this goal. An internet-based framework is used to predict and recommend Android malware on IoT devices. As the prevalence of Android devices g...
The rumors in the healthcare system have the attributes of fast spread and severe social influence. Even worse, it may cause the collapse of medical services and the death of many patients. To prevent its serious impact on society, the target of rumor suppression for the healthcare system is to restrain the spread of rumors (negative opinions) and...
Federated learning (FL) is receiving much attention in the Healthcare Internet of Things (H-IoT) to support various instantaneous E-health services. Today, the deployment of FL suffers from several challenges, such as high training latency and data privacy leakage risks, especially for resource-constrained medical devices. In this paper, we develop...
As city boundaries expand and the vehicles continues to proliferate, the transportation system is increasingly overloaded, greatly increasing people’s commuting burden and extending the resulting negative effects to all areas of work and life. It is a big issue that needs to be solved urgently. However, due to the development of infrastructure and...
As the number of passengers at border entry points such as airports and rail stations increases, so does the demand for seamless, secure, and fast biometric technologies for verification purposes. Although fingerprints are currently useful biometric technologies, they are intrusive and slow down the end-to-end verification process, increasing the c...
Parkinson is a neurodegenerative disorder which affects a considerable fraction of the global population. Early and accurate diagnosis of Parkinson is essential for proper treatment and disease management. Artificial intelligence (AI) has emerged as a promising tool in the field of medical diagnosis, including PD. AI algorithms can analyze large da...
The Vehicular ad-Hoc Network (VANET) is envisioned to ensure wireless transmission with ultra-high reliability. In the presence of fading and mobility of vehicles, error-free information between Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) requires extensive investigation. The current literature lacks in designing an ultra-reliable...
Wireless Body Area Networks (WBANs) is a specialized field with applications both in medical and non-medical domains. In WBAN, nodes' (both wearable and implanted) may vary in capabilities , hence, carrying data at various rates. Propagating such data reliably and efficiently is challenging and results in increased delay and poor service. In sensit...