A5052116574- Network Security and Intrusion Detection
- Advanced Malware Detection Techniques
- Anomaly Detection Techniques and Applications
- Internet Traffic Analysis and Secure E-voting
- Vehicular Ad Hoc Networks (VANETs)
- AI in cancer detection
- Machine Learning in Bioinformatics
- User Authentication and Security Systems
- Video Surveillance and Tracking Methods
- Digital Imaging for Blood Diseases
- Face and Expression Recognition
- Gene expression and cancer classification
- Image Retrieval and Classification Techniques
- Advanced Authentication Protocols Security
- Advanced Image and Video Retrieval Techniques
- Software System Performance and Reliability
- IoT and Edge/Fog Computing
- Autonomous Vehicle Technology and Safety
- Biometric Identification and Security
- UAV Applications and Optimization
- Remote Sensing in Agriculture
- Model-Driven Software Engineering Techniques
- Multimodal Machine Learning Applications
- Radiomics and Machine Learning in Medical Imaging
- Viral Infections and Vectors
King Abdulaziz University
2019-2024
University of Washington
2024
Abdul Wali Khan University Mardan
2016-2023
University of Swat
2023
University of Glasgow
2023
Tieto (Finland)
2022
Anhui Agricultural University
2020-2022
University of Swabi
2021
Ayub Medical College
2020
University of Engineering and Technology Taxila
2006-2018
Insect pests are a major element influencing agricultural production. According to the Food and Agriculture Organization (FAO), an estimated 20–40% of pest damage occurs each year, which reduces global production becomes challenge crop These insect cause sooty mold disease by sucking sap from crop’s organs, especially leaves, fruits, stems, roots. To control these pests, pesticides frequently used because they fast-acting scalable. Due environmental pollution health awareness, less use is...
Cybersecurity has been widely used in various applications, such as intelligent industrial systems, homes, personal devices, and cars, led to innovative developments that continue face challenges solving problems related security methods for IoT devices. Effective methods, deep learning intrusion detection, have introduced. Recent research focused on improving algorithms improved IoT. This explores detection implemented using learning, compares the performance of different identifies best...
Intrusion detection in computer networks is of great importance because its effects on the different communication and security domains. The network intrusion a challenge. Moreover, remains challenging task as massive amount data required to train state-of-the-art machine learning models detect threats. Many approaches have already been proposed recently detection. However, they face critical challenges owing continuous increase new threats that current systems do not understand. This paper...
A solo attack may cause a big loss in computer and network systems, its prevention is, therefore, very inevitable. Precise detection is important to prevent such losses. Such pivotal part of any security tools like intrusion system, firewalls etc. Therefore, an approach provided this paper analyze denial service by using supervised neural network. The methodology used sampled data from Kddcup99 dataset, database that standard for judgment tools. system uses multiple layered perceptron...
As a crucial security problem, anti-spoofing in biometrics, and particularly for the face modality, has achieved great progress recent years. Still, new threats arrive inform of better, more realistic sophisticated spoofing attacks. The objective 2nd Competition on Counter Measures to 2D Face Spoofing Attacks is challenge researchers create counter measures effectively detecting variety submitted propositions are evaluated Replay-Attack database results presented this paper.
Last few years, vehicular network has been taken more attention of researchers and automotive industries due to life saving factor. Vehicular Ad hoc Network (VANET) needs security implement the wireless environment serves users with safety non applications. Attackers generate different attacks in this network. In paper, we propose five classes every class is expected provide better perspective for VANET security. The main contribution paper proposed solution classification identification VANET.
Real-time security requirements continue to increase due the occurrence of various suspicious activities in open and closed environments. Day-to-day threats may seriously affect everyone lives. Many techniques have been introduced this regard, but still some issues remain unaddressed. The work presented paper provides video surveillance with improved accuracy less computational complexity. most significant part system consists face localization, detection recognition. obtains underlined...
Social distancing is crucial to restrain the spread of diseases such as COVID-19, but complete adherence safety guidelines not guaranteed. Monitoring social through mass surveillance paramount develop appropriate mitigation plans and exit strategies. Nevertheless, it a labor-intensive task that prone human error tainted with plausible breaches privacy. This paper presents privacy-preserving adaptive distance estimation crowd monitoring solution for camera systems. We novel person...
Artificial intelligence (AI) has provided significant help in many fields of life. This study proposed a framework that helped understanding customers’ attitudes about the adoption Robo-advisors. The role Technology Readiness Index moderated as one primary relationships. A total 208 potential users Robo-advisor services data confirmed validity model. model input for structural equation modeling and analysis hypotheses. results indicated consumers showed positive services, with moderating...
It is crucial to ensure proper surveillance for the safety and security of people their assets. The development an aerial system might be very effective in catering challenges systems. Current systems are expensive complex. A cost-effective efficient solution required, which easily accessible anyone with a moderate budget. In surveillance, quadcopters equipped state-of-the-art image processing technology that captures detailed photographs every object underneath. quadcopter-based proposed...
Recently, the number of Internet Things (IoT)-connected devices has increased daily. Consequently, cybersecurity challenges have due to natural diversity IoT, limited hardware resources, and security capabilities. Intrusion detection systems (IDSs) play a substantial role in securing IoT networks. Several researchers focused on machine learning (ML) deep (DL) develop intrusion techniques. Although ML is good for classification, other methods perform better feature transformation. However, at...
The possibility of medical image segmentation within the domain a federated learning, Federated Learning (FL) may transform situation and help solve critical challenges that exist in common centralized machine learning models. While effective, traditional models are limited by issues like need huge surveys, high costs data assignment, privacy concerns over sensible wellbeing data. Since improvements imaging field continue, adoption FL is strategic response to such limitations can be...
Abstract Cell classification refers to detecting normal and diseased cells from small amount of data. Sometimes, becomes difficult because some fall into more than one categories/classes. Current state‐of‐the‐art cell methods have been developed on the bases tumor but these cannot classify or cells. This study investigated performance two traditional machine learning deep (normal classification) categorize Millions undergo controlled growth uncontrolled may be involved in disease causation...
The prevention of any type cyber attack is indispensable because a single may break the security computer and network systems. hindrance such attacks entirely dependent on their detection. detection major part tool as Intrusion Detection System (IDS), Prevention (IPS), Adaptive Security Alliance (ASA), check points firewalls. Consequently, in this paper, we are contemplating feasibility an approach to probing that basis others Our adopts supervised neural phenomenon majorly used for...
Essential Proteins are demonstrated to exert vital functions on cellular processes and indispensable for the survival reproduction of organism. Traditional centrality methods perform poorly complex protein-protein interaction (PPI) networks. Machine learning approaches based high-throughput data lack exploitation temporal spatial dimensions biological information.We put forward a deep framework predict essential proteins by integrating features obtained from PPI network, subcellular...
Cardiac disease diagnosis and identification is problematic mostly by inaccurate segmentation of the cardiac left ventricle (LV). Besides, LV challenging since it involves complex variable structures in terms components intricacy time-based crescendos. In addition, full quantification myocardium border even more because different shapes sizes zone. The foremost purpose this research to design a precise automatic technique employing deep learning models for using magnetic resonance imaging...
Haemaphysalis ticks are globally distributed with the greatest diversity in Oriental region. This study aimed to primarily provide information on morphology, host record, and preliminary phylogenetic position of a poorly known tick danieli. Herds comprised goats sheep were examined for this species Upper Dir, Khyber Pakhtunkhwa, Pakistan. A total 127 ticks, including males (n = 15, 11.8%) females 112, 88.2%), collected, morphologically identified as H. The morphological identification was...
In this study we address the problem of face segmentation in thumbnail images. While there have been several approaches for detection, none performs detection such low resolution and with pixel accuracy. paper, propose convolutional networks (CSNs) that can be trained to learn human faces. Unlike deep classifiers as Convolutional Neural Network (CNNs), CSNs unique design solely minimal complexity. Furthermore, a self-data organization (SDO) order create "expert" each which is specialized...
Sensing plays a vital role in enabling smart cities. The mobile surveillance of different sectors, the retransmission radio signals, and package delivery are main applications conducted by unmanned vehicles Multiple or miniaturized real-time flying machines with onboard sensors, whether land- air-based, communicate each other to form sensor network. Almost all these battery-operated. Therefore, power preservation is an extremely important factor be taken into consideration. This paper...
Detecting cyber intrusions in network traffic is a tough task for cybersecurity. Current methods struggle with the complexity of understanding patterns data. To solve this, we present Hybrid Deep Learning Intrusion Detection Model (HD-IDM), new way that combines GRU and LSTM classifiers. good at catching quick patterns, while handles long-term ones. HD-IDM blends these models using weighted averaging, boosting accuracy, especially complex patterns. We tested on four datasets:...