Maazen Alsabaan

• PhD
• Professor (Assistant) at King Saud University

The multi-choice rough bi-level multi-objective nonlinear programming problem (MR-BLMNPP) has noticeably risen in various real applications. In the current model, the objective functions have a multi-choice parameter, and the constraints are represented as a rough set. In the first phase, Newton divided differences (NDDs) are utilized to formulate...

Smart power grids (SGs) enhance efficiency, reliability, and sustainability by integrating distributed energy resources (DERs) such as solar panels and wind turbines. A key challenge in SGs is managing home battery charging during periods of insufficient renewable energy generation to ensure fairness, efficiency, and customer satisfaction. This pap...

Accurate classification of power quality disturbances (PQD) is essential for ensuring the reliability and safety of modern power systems. However, deep learning (DL) models used for PQD classification can be compromised by trojan attacks—malicious modifications that alter model behavior only in the presence of specific triggers. Motivated by the ur...

Reinforcement learning (RL) is proven effective in optimizing home battery charging coordination within smart grids. However, its vulnerability to adversarial behavior poses a significant challenge to the security and fairness of the charging process. In this study, we, first, craft five stealthy false data injection (FDI) attacks that under-report...

LoRa networks, widely adopted for low-power, long-range communication in IoT applications, face critical security concerns as radio-frequency transmissions are increasingly vulnerable to tampering. This paper addresses the dual challenges of privacy-preserving detection of tampered transmissions and the identification of unknown attacks in LoRa-bas...

Association Rule Mining (ARM) relies on concept lattices as an effective knowledge representation structure. However, classical ARM methods face significant limitations, including the generation of misleading rules during data-to-formal-context mapping and poor handling of heterogeneous data types such as linguistic, continuous, and imprecise data....

Remote diagnosis enables healthcare professionals to evaluate and diagnose patients from a distance using telecommunication technologies, enhancing healthcare delivery by improving accessibility, especially for those in remote or underserved areas. One of the significant sustainability challenges in remote medical diagnostics is offering timely ass...

A cost-effective IoT-based real-time data acquisition and analysis hardware system was developed to enhance the performance of the mobile harbor cranes using a combination of a cost-effective quality control monitoring sensor dashboard (proximity sensors, angle position sensor, weight sensor, vibration sensor, and wind sensor), embedded microcontro...

In the realm of smart grids, machine learning (ML) detectors—both binary (or supervised) and anomaly (or unsupervised)—have proven effective in detecting electricity theft (ET). However, binary detectors are designed for specific attacks, making their performance unpredictable against new attacks. Anomaly detectors, conversely, are trained on benig...

In the realm of smart grids, smart meters can be hacked to report false data to lower the consumers’ electricity bills. While machine learning (ML) techniques have shown promise in detecting false data, they are also prone to adversarial attacks such as evasion attacks. This paper investigates the impact of gradient-ensemble-based evasion attacks o...

Long-range networks, renowned for their long-range, low-power communication capabilities, form the backbone of many Internet of Things systems, enabling efficient and reliable data transmission. However, detecting tampered frequency signals poses a considerable challenge due to the vulnerability of LoRa devices to radio-frequency interference and s...

The advanced metering infrastructure (AMI) of the smart grid plays a critical role in energy management and billing by enabling the periodic transmission of consumers’ power consumption readings. To optimize data collection efficiency, AMI employs a “change and transmit” (CAT) approach. This approach ensures that readings are only transmitted when...

This paper presents a novel framework for 3D face reconstruction from single 2D images and addresses critical limitations in existing methods. Our approach integrates modified adversarial neural networks with graph neural networks to achieve state-of-the-art performance. Key innovations include (1) a generator architecture based on Graph Convolutio...

This paper describes a revolutionary design paradigm for monitoring aquatic life. This unique methodology addresses issues such as limited memory, insufficient bandwidth, and excessive noise levels by combining two approaches to create a comprehensive predictive filtration system, as well as multiple-transfer route analysis. This work focuses on pr...

The explosive growth of the Internet of Things (IoT) has highlighted the urgent need for strong network security measures. The distinctive difficulties presented by Internet of Things (IoT) environments, such as the wide variety of devices, the intricacy of network traffic, and the requirement for real-time detection capabilities, are difficult for...

The integration of renewable energy sources, such as rooftop solar panels, into smart grids poses significant challenges for managing customer-side battery storage. In response, this paper introduces a novel reinforcement learning (RL) approach aimed at optimizing the coordination of these batteries. Our approach utilizes a single-agent, multi-envi...

In smart grids, smart meters (SMs) transmit power consumption data to utilities for billing and energy management. However, compromised SMs can report low consumption to reduce electricity bills. Deep reinforcement learning (DRL) detectors have recently been proposed to detect these attacks due to their adaptability to new attacks and changes in po...

Existing literature confirms the ability of machine learning to identify fraudulent smart grid power consumers who report false consumption readings to pay less electricity bills. Additionally, federated learning (FL) shows promise as a way to train the detection model without requiring data sharing, thereby safeguarding consumer privacy. However,...

In smart power grid, consumers can hack their smart meters to report low electricity consumption readings to reduce their bills launching electricity theft cyberattacks. This study investigates a Trojan attack in federated learning of a detector for electricity theft. In this attack, dishonest consumers train the detector on false data to later byp...

Machine learning, powered by cloud servers, has found application in medical diagnosis, enhancing the capabilities of smart healthcare services. Research literature demonstrates that the support vector machine (SVM) consistently demonstrates remarkable accuracy in medical diagnosis. Nonetheless, safeguarding patients’ health data privacy and preser...

With the increased use of automated systems, the Internet of Things (IoT), and sensors for real-time water quality monitoring, there is a greater requirement for the timely detection of unexpected values. Technical faults can introduce anomalies, and a large incoming data rate might make the manual detection of erroneous data difficult. This resear...

In the smart grid, malicious consumers can hack their smart meters to report false power consumption readings to steal electricity. Developing a machine-learning based detector for identifying these readings is a challenge due to the unavailability of malicious datasets. Most of the existing works in the literature assume attacks to compute malicio...

Alzheimer’s disease (AD) is a progressive illness with a slow start that lasts many years; the disease’s consequences are devastating to the patient and the patient’s family. If detected early, the disease’s impact and prognosis can be altered significantly. Blood biosamples are often employed in simple medical testing since they are cost-effective...

In order to obtain high precision image identification results of transmission line ice thickness, an image identification method of transmission line ice thickness based on visual sensing was proposed. The ice-covered images of transmission lines are collected by visual sensors, and we take the non-local self-similarity information of the images a...

Road maintenance systems (RMS) are crucial for maintaining safe and efficient road networks. The impact of climate change on road maintenance systems is a concern as it makes them more susceptible to weather events and subsequent damages. To tackle this issue, we propose an RMSDC (Road Maintenance Systems Using Deep Learning and Climate Adaptation)...

The current traditional paper ballot voting schemes suffer from several limitations such as processing delays due to counting paper ballots, lack of transparency, and manipulation of the ballots. To solve these limitations, an electronic voting (e-voting) scheme has received massive interest from both governments and academia. In e-voting, individu...

This study presents an improved data augmentation technique for the classification of remote sensing (RS) scenes. The method is called Quality-based Sample Selection (QSS) data augmentation technique. It is based on generating a large number of samples using geometric transformations and then selecting the best ones based on a quality criterion. Sa...

Schizophrenia is a severe mental illness that impairs the way a person perceives reality. It causes a variety of issues related to behavior, emotions, and thinking (cognition). Patients experience auditory hallucinations, delusion, and sleep deprivation. Although the Diagnostic and Statistical Manual (DSM) IV version helps in diagnosis, the lack of...

In smart power grids, smart meters (SMs) are deployed at the end side of customers to report fine-grained power consumption readings periodically to the utility for energy management and load monitoring. However, electricity theft cyber-attacks can be launched by fraudulent customers through compromising their SMs to report false readings to pay le...

Charging coordination mechanisms have been adopted to avoid overloading the power grid and long waiting times for electric vehicles’ (EVs) drivers at charging stations. However, adversaries could launch distributed denial of charge (DDoC) attacks against charging stations by submitting fake charging requests to reserve charging time slots. The curr...

Fraudulent customers in smart power grids employ cyber-attacks by manipulating their smart meters and reporting false consumption readings to reduce their bills. To combat these attacks and mitigate financial losses, various machine learning-based electricity theft detectors have been proposed. Unfortunately, these detectors are vulnerable to serio...

In smart power grids, electricity theft causes huge economic losses to electrical utility companies. Machine learning (ML), especially deep neural network (DNN) models hold state-of-the-art performance in detecting electricity theft cyberattacks. However, DNN models are vulnerable to adversarial attacks, i.e., evasion attacks. In this work, we, fir...

In the advanced metering infrastructure (AMI) of the smart grid, smart meters (SMs) are deployed to collect fine-grained electricity consumption data, enabling billing, load monitoring, and efficient energy management. However, some consumers engage in fraudulent behavior by hacking their meters, leading to either traditional electricity theft or m...

Medical image segmentation aims to identify important or suspicious regions within medical images. However, many challenges are usually faced while developing networks for this type of analysis. First, preserving the original image resolution is of utmost importance for this task where identifying subtle features or abnormalities can significantly...

In this paper we propose an accurate and privacy-preserving scheme that enables a law enforcement agency to locate persons of interest using the camera surveillance systems of public places. Comparing to the existing schemes that measure the Euclidean distance to locate persons using their embedding vectors storing facial features, we use a more ac...

COVID-19 pandemic has revealed a pressing need for an effective surveillance system to control the spread of infection. However, the existing systems are run by the people’s smartphones and without a strong participation from the people, the systems become ineffective. Moreover, these systems can be misused to spy on people and breach their privacy...

Surveillance systems provide continual coverage of target area(s) using several cameras through different angles. Conventionally, a central unit controls the system by adjusting the coverage rate of the cameras. However, in large-scale environments, such a centralized system is costly and energy inefficient, as the central unit should exchange a lo...

Understanding node mobility is critical for the proper simulation of mobile devices in a wireless network. However, current mobility models often do not reflect the realistic movements of users within their environments. They also do not provide the freedom to adjust their degrees of randomness or adequately mimic human movements by injecting possi...

Given a large number of online video viewers, video streaming, over various networks, is important communication technology. The multitude of viewers makes it challenging for service providers to provide a good viewing experience for subscribers. Video streaming capabilities are designed based on concepts including quality, viewing flexibility, cha...

Non-profit organizations mitigate the problem of food insecurity by collecting surplus food from donors and delivering it to underprivileged people. In this paper, we focus on a single non-profit organization located in Makkah city (Saudi Arabia), referred to as Ekram. The current surplus food pickup/delivery and operational routing model of Ekram...

Advances in localization-based technologies and the increase in ubiquitous computing have led to a growing interest in location-based applications and services. High accuracy of the position of a wireless device is still a crucial requirement to be satisfied. Firstly, the rapid development of wireless communication technologies has affected the loc...

A basic need for cloud computing services is to provide them with sound ”Information Security Risk Management (ISRM)” solutions. The initial essential step toward providing such solutions is to identify a context that determines all security issues. This paper introduces a management framework that targets modularity and comprehensiveness. The fram...

Given the ongoing concerns on the emissions of greenhouse gases that contribute to global warming, electric vehicle is considered as a promising technology solution for the reduction of these emissions in the transportation sector. Despite the numerous advantages of electric vehicle, the limited driving range is one of the prominent drawbacks that...

Machine-to-Machine (M2M) communication is a promising technology for next generation communication systems. This communication paradigm facilitates ubiquitous communications with full mechanical automation, where a large number of intelligent devices connected by wired/wireless links, interact with each other without direct human intervention. As a...

Economical and environmentally friendly geocast (EEFG) uses traffic signals to communicate with approaching vehicles. The communication can be signal-to-vehicle (TLS2V) and vehicle-to-vehicle (V2V). Based on the information sent, the vehicle receiving the message adapts its speed to a recommended speed , which helps the vehicle reduce fuel consumpt...

Due to the need to reduce greenhouse gas emissions, and concerns about increasing oil prices, vehicles manufacturers have produced vehicles with either hybrid technology or full electric vehicles (FEVs). However, power plants that energize EVs generate emissions. Also, electricity prices are increasing. Therefore, more efforts in different technolo...

In a smart power grid, collecting data from a large number of smart meters and sensors over the conventional one-hop transmission control protocol (TCP) communication is prone to a high packet loss rate and degraded throughput due to the ineffectiveness of the TCP congestion control mechanism. The Split and Aggregated TCP (SA-TCP) proposes upgradin...

This paper introduces our proposed Split- and Aggregated-TCP (SA-TCP) scheme's enhanced TCP performance in a smart metering infrastructure (SMI). The scheme is based on upgrading intermediate devices (e.g., regional collectors) to aggregate TCP connections. An SA-TCP aggregator collects data packets from smart meters in a certain region over separa...

Vehicular communication networks are increasingly being considered as a means to conserve fuel and reduce emissions within transportation systems. This paper focuses on using traffic light signals to communicate with approaching vehicles. The communication can be traffic-light-signal-to-vehicle (TLS2V) and vehicle-to-vehicle (V2V). Based on the inf...

Researchers are looking for solutions that save the environment and money. Vehicular ad-hoc networks (VANETs) offer promising technology for safety communications. Thus, researchers try to integrate certain applications into existing research. The current survey critically examines the use of vehicular communication networks to provide green soluti...

This paper investigates the TCP's congestion control mechanism effectiveness for smart meters. We show that the classic congestion control causes a high loss rate for metered data and disrupts competing traffic flows in a shared network. The paper introduces the performance analysis of our proposed Splitand Aggregated-TCP (SA-TCP). SA-TCP complies...

The volatile world economy has greatly affected fuel prices, while pollution and gas emissions are increasing to negatively impact global warming. Vehicular networks offer a promising approach that can be applied in transportation systems to reduce fuel consumption and emissions. One of the interesting applications involves a traffic light signal s...

With recent advances in the development of wireless communication networks, wireless mesh networks (WMNs) have been receiving considerable research interests in recent years. The need to support integrated services and ensure quality of service (QoS) satisfaction for various applications is one of the fundamental challenges for successful WMN deplo...

Transport protocol design for supporting smart metering applications poses certain challenges because of unique issues. The issues stem from the need to deploy a significantly large number of meters (e.g., hundreds of thousands). Each meter generates small reports at a fixed low rate. All meters' reports are destined to the same data collection cen...

Pollution and gas emissions are increasing and negatively impacting global warming. Consequently, researchers are looking for solutions that save environment. Greenhouse gas (GHG) emissions from vehicles are considered to be one of the main contributing sources. Carbon dioxide (CO2) is the largest component of GHG emissions. Vehicular networks offe...

With recent advances in the development of wireless communication networks, vehicular networks have been receiving considerable research interest. One of the major applications of vehicular networks is Intelligent Transportation Systems (ITS). To exchange and distribute messages, geocast routing protocols have been proposed for ITS applications. Al...

There is an emerging class of applications in which there is a need to reliably transport data from a large number of low rate devices (e.g., hundreds of thousands) to a central server. Atop the list of such applications is smart grid infrastructure. Other applications include meteorological applications, such as monitoring of weather, pollution, a...

With recent advances in the development of wireless communication networks, Vehicular Ad hoc Networks (VANETs) have been receiving considerable research interest. One of the major applications of VANETs is Intelligent Transportation Systems (ITS). To exchange and distribute messages, geocast protocols have been proposed for ITS. Almost all of these...

The need to support integrated services and provide quality of service (QoS) for various applications is one of the fundamental challenges for successful wireless mesh network (WMN) deployment. In order to provide differentiated services, medium access control (MAC) should have priority management at the link layer. In code division multiple access...

Pollution and gas emissions are increasing and negatively impacting global warming. Consequently, researchers are looking for solutions that save environment. Greenhouse gas (GHG) emissions from vehicles are considered to be one of the main contributing sources. Carbon dioxide (CO 2) is the largest component of GHG emissions. Vehicular networks off...