Alyaa Al-Barrak

@en.uobaghdad.edu.iq

The University of Baghdad

Alyaa Al-Barrak


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https://researchid.co/dralyaa
Dr. Alyaa Al-Barrak is a lecturer in Computer Science at the University of Baghdad and Vice President of the Iraqi Society for Engineering Management (ISEM). She earned her PhD in Computing from the University of Northampton, UK, specializing in Wireless Communications, following her BSc and MSc in Computer Science from the University of Baghdad.

With extensive teaching experience, she has delivered courses in programming, AI, wireless communications, and mobile computing. She currently supervises four MSc students and two diploma students. Her research focuses on cryptography, wireless networks, IoT, blockchain, and AI applications, with publications in leading journals and conferences, including IEEE. She has also received recognition for her research, including a Best Paper Award in 2016.

EDUCATION

I obtained my PhD from the University of Northampton, UK, at the Faculty of Art, Science, and Technology, Department of Computing. My research focused on Wireless Communications. I pursued this degree from February 1, 2014, to May 18, 2018, and was officially awarded the PhD on July 4, 2018.

Prior to that, I completed my MSc at the University of Baghdad, Iraq, in the College of Science, Department of Computer. My specialization was in Computer Security. I pursued my MSc from October 1, 2001, to March 14, 2004, achieving an average score of 81.92% with a "Very Good" standard. I was awarded the degree on May 23, 2004.

My academic journey began with a BSc in Computer Science from the University of Baghdad, College of Science. I studied from October 1, 1997, to June 30, 2001, securing an average of 74.76% with a "Good" standard. I ranked 2nd out of 72 students across both trials and was awarded the degree on June 30, 2001.

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition
12

Scopus Publications

96

Scholar Citations

4

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Safety assessment model for DoS attacks detection in wireless communication and network OS environments
    Alyaa Al-Barrak, Sundos A Hameed Alazawi, Abbas A Abdulhameed
    Intelligent Decision Technologies, 2025
    Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicious attacks. In this manuscript, a correspondence model is designed to discuss the algorithm in the environment of wireless communication systems and distributed computing by adopting the protocol data enhancement to the network using structured construction and diversity algorithm to improve the effectiveness of the intrusion detection system. Next, a multi-label convolutional neural network model is used to detect business transactions. An CNN was trained on the WSN-DS dataset using 5-Fold in CV technique with three hidden layers. The highest Precision values 0.951 of Grayhole attack for multi-classification.
  • Prediction of COVID-19 Disease and Infection Rate Based on Dense Net
    Saja Ali, Alyaa Al-Barrak
    Iraqi Journal of Science, 2025
    Coronavirus is an RNA (Ribonucleic acid) virus in the coronaviridian family that causes zoonotic and infectious diseases transmitted between animals and evolved between humans. This class of pathogens is responsible for respiratory diseases. Coronavirus refers to the crown-like protrusions on the outside surface of the virus. Corona is an infection that causes breathing difficulties in humans. In epidemics, symptomatic techniques based on graphic design are essential for examining the causes of influence, which leads to better results than primary radioscopy mechanisms for identifying and diagnosing COVID-19 cases. The urgent need to employ artificial intelligence in disease detection arose from this standpoint. In this paper, a system is proposed to diagnose infected persons by building a deep learning model and preprocessing processes homogeneously to investigate CT (coronavirus-computed tomography) scan radiographs using the global SARS-Covid dataset, achieving a 99% accuracy rate in diagnosing and identifying COVID-19 or non-COVID-19.
  • Utilizing Palm Print to Identify People Based on the Resnet50 Approach
    Mathiq H. Yasir, Alyaa Al-Barrak
    Iraqi Journal of Science, 2025
    In person recognition, biometrics play an important role. Behavioral or physiological characteristics are utilized by biometrics to identify an individual. Palmprint is considered highly usable and represents a reliable and unique biometric characteristic. Nevertheless, the useful and deepest features extracted from palm prints are an essential point. The most recently developed techniques use creases, wrinkles, and principal line features. However, due to closeness, these features are not enough to distinguish two individuals. Recently, one of the most important techniques that is considered a major key to extracting deep features such as texture features is deep learning. This paper proposes a biometric palm print system using the Resnet50 pre-train model to extract deep features and identify individuals. COEP and PolyU-IITD datasets are used in the simulation; moreover, the merging of COEP and PolyU-IITD in one dataset is also used. In the evaluation process, precision, F1-score, and recall are employed. The proposed system developed three models; the first model resulted in precision = 0.967, recall = 0.97, and F1 = 0.97. In comparison, the second model got precision = 0.88, recall = 0.87, and F1 = 0.86. Finally, the third model obtained precision = 0.95, recall = 0.92, and F1 = 0.93. The proposed system efficiently performs palm print identification.
  • CT scan and deep learning for COVID-19 detection
    Saja A. Al-Janaby, Alyaa Al-Barrak
    Aip Conference Proceedings, 2024
  • Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
    Saja Majeed Mohammed, Alyaa Al-Barrak, Noof T. Mahmood
    Ingenierie Des Systemes D Information, 2024
    The need for faster and more dependable wireless communication networks has encouraged the development of 6G networks.This article explores the integration of Mobile Edge Computing (MEC) cloud architectures and the potential of self-driving Vehicle-to-Everything (V2X) communication to achieve ultra-low latency and high dependability in 6G networks.By integrating MEC into the 6G network fabric, latency is reduced by bringing data processing closer to end-users, particularly vehicles, thus enhancing computational capabilities at the network's edge.The fusion of MEC with self-driving V2X communication holds the key to realizing the potential of 6G networks, enabling seamless communication among vehicles, roadside infrastructure, and individuals.Extensive testing and simulations predict that the 6G network's latency for User Equipments (UEs) will fall within an impressive range of 4ms to 10ms, unlocking new opportunities for missioncritical services, augmented reality, and real-time applications.The paper substantiates the dependability of 6G networks under various scenarios, ensuring a stable and reliable communication infrastructure.The objectives of the study are twofold: firstly, to evaluate the potential of MEC integration in 6G networks and its impact on reducing latency for endusers, particularly in the context of self-driving V2X communication; and secondly, to predict and verify the ultra-low latency capabilities of 6G networks for UEs through extensive testing and simulations, thereby enabling new opportunities for mission-critical services, augmented reality, and real-time applications.The real network simulation carried in the MATLAB environment shows that for UEs in the 6G network, the predicted latency will be approximately 4ms to 10ms, which showcasing unprecedented opportunity of possibilities in communication and services.
  • Modeling and analysis of thermal contrast based on LST algorithm for Baghdad city
    Alyaa Al-Barrak, Hassan J. Alatta, Suhad Faisal Behadili, Baqer H. Sayyid, Ali Adham, Mustafa A. Mahmood
    Aip Conference Proceedings, 2024
    Land Surface Temperature (LST) is an important factor in global climate change, vegetation growth, and glacier. Its impact will be more in monsoon area because of monsoon failure and uncertainty and unpredictable in rainfall. In this article we perform LST estimation using LST algorithm on Landsat 8 Operational Land Imager (OLI) Sensor and Thermal Infrared Sensor (TIRS) dataset of Baghdad city for the period June 2021-2022. TIRS sensor exhibits two thermal Band 10 and 11. LST algorithm require brightness temperature value of both band 10 or 11 as well as land surface emissivity calculated from OLI bands (NIR and RED) for estimation of LST. However, the estimated emissivity values over few land use/land cover of Landsat-8 OLI have been compared with the literature values. The results show that the satellite derived emissivity values are in the acceptable range and the NDVI is effective in deriving surface emissivity. The derived surface temperature values are found to be in good agreement with the field measured values, indicating that the methodology can be adopted for the study over urban areas. As well as, these results shown that there is a thermal contrast in LST of June 2022 is higher than June 2021 by approximately 0.5 C°.
  • Utilizing Deep Learning Techniques to Identify People by Palm Print
    Mathiq Hassan Yasir, Alyaa Al-Barrak
    Journal of Engineering Iraq, 2024
    Person recognition systems have been applied for several years, as fingerprint recognition has been experimented with different image resolutions for 15 years. Fingerprint recognition and biometrics for security are becoming commonplace. Biometric systems are emerging and evolving topics seen as fertile ground for researchers to investigate more deeply and discover new approaches. Among the most prominent of these systems is the palm printing system, which identifies individuals based on the palm of their hands because of the advantages that the palm possesses that cannot be replicated among humans, as in its theory of other fingerprints. This paper proposes a biometric system to identify people by handprint, especially palm area, using deep learning technology via a pre-trained model on the PolyU-IITD dataset. The proposed system goes through several basic stages, namely data pruning, processing, training, and prediction, and the results were promising, as the system's accuracy reached 90% based on the confusion matrix measures.
  • Text image secret sharing with hiding based on color feature
    Nuha Jameel Ibrahim, Yossra H. Ali, Alyaa Al-Barrak, Tarik A. Rashid
    Periodicals of Engineering and Natural Sciences, 2022
    The Secret Sharing is a scheme for sharing data into n pieces using (k, n) threshold method. Secret Sharing becomes an efficient method to ensure secure data transmission. Some visual cryptography techniques don’t guarantee security transmission because the secret information can be retrieved if the hackers obtain the number of shares. This study present a secret sharing method with hiding based on YCbCr color space. The proposed method is based on hiding the secret text file or image into a number of the cover image. The proposed method passes through three main steps: the first is to convert the secret text file or image and all cover images from RGB to YCbCr, the second step is to convert each color band to binary vector, then divide this band in the secret image into four-part, each part is appended with a binary vector of each cover image in variable locations, the third step is converting the color space from YCbCr to RGB color space and the generated shares, hidden with covers, are ready for transmission over the network. Even if the hackers get a piece of data or even all, they cannot retrieve the whole picture because they do not know where to hide the information. The results of the proposed scheme guarantee sending and receiving data of any length. The proposed method provides more security and reliability when compared with others. It hides an image of size (234x192) pixels with four covers. The MSE result is 3.12 and PSNR is 43.74. The proposed method shows good results, where the correlation between secret and retrieved images is strong ranging from (0.96 to 0.99). In the proposed method the reconstructed image quality is good, where original and reconstructed images Entropy are 7.224, 7.374 respectively.
  • Impact of Alamouti Space-Time Block Coding on the Performance of Vehicle-to-Vehicle Communication
    Alyaa Al-Barrak, Ahmad Baheej Al-Khalil
    Icoase 2018 International Conference on Advanced Science and Engineering, 2018
    A network that has recently received a lot of interest is the Vehicular Ad hoc Network VANET. Vehicle – to – Vehicle V2V communication is the conventional method in VANET communication, where vehicles can share information regarding the road status such as a warning message related to the incidence of an accident. The aim of this paper is the use of Multiple – Input – Multiple – Output MIMO diversity technique called Alamouti Space-Time Block Coding STBC as a channel coding in V2V communication. The simulation tests were constructed according to the conditions of vehicles speeds, modulations and the distances between the vehicles. These tests included both symmetric and asymmetric channels. The results showed that Alamouti STBC is suitable for slow fading channel communication rather than for mobility communication such as V2V.
  • Performance of BCH and RS Codes in MIMO System Using MPFEC Diversity Technique
    Ahmad Baheej Al-Khalil, Alyaa Al-Barrak
    Icoase 2018 International Conference on Advanced Science and Engineering, 2018
    Multipath propagation phenomenon often causes Inter-Symbol Interference (ISI) because several copies from the originally transmitted signal travel in different directions and reach the destination with different time delays. This paper offers a new diversity technique to eliminate the effect and utilise multipath propagation phenomenon. The new diversity technique is known as MultiPath Forward Error Correction (MPFEC) technique. The MPFEC technique considers some of the multipath copies as an existing resource (redundant copies of the transmitted signal) which can be utilised to enhance the performance of Forward Error Correction coding (FEC) techniques, hence saving significant channel resources otherwise given to a feedback channel, without adding redundancy. Two different coding techniques BCH and RS coding are used in the simulation to perform the Bit Error Rate (BER) analysis. The result reveals that BCH and RS codes performance can be enhanced by utilising the MPFEC technique without increasing the number of redundancy. This paper is implemented by using MATLAB. The results are analysed and compared.
  • Enhancing BER performance limit of BCH and RS codes using multipath diversity
    Alyaa Al-Barrak, Ali Al-Sherbaz, Triantafyllos Kanakis, Robin Crockett
    Computers, 2017
  • Utilisation of multipath phenomenon to improve the performance of BCH and RS codes
    Alyaa Al-Barrak, Ali Al-Sherbaz, Triantafyllos Kanakis, Robin Crockett
    2016 8th Computer Science and Electronic Engineering Conference Ceec 2016 Conference Proceedings, 2017

RECENT SCHOLAR PUBLICATIONS

  • Safety assessment model for DoS attacks detection in wireless communication and network OS environments
    A Al-Barrak, SA Hameed Alazawi, AA Abdulhameed
    Intelligent Decision Technologies 19 (5), 3360-3368 , 2025
    2025
  • Utilizing Palm Print to Identify People Based on the Resnet50 Approach
    MH Yasir, A Al-Barrak
    Iraqi Journal of Science, 2071-2085 , 2025
    2025
  • Prediction of COVID-19 Disease and Infection Rate Based on Dense Net
    S Ali, A Al-Barrak
    Iraqi Journal of Science, 1664-1678 , 2025
    2025
    Citations: 1
  • Validating the Channel Capacity in V2V Communication based on SCME Channel Model with Turbo-BLAST Coding
    A Al-Barrak, A Adham, S Faisal
    Al-Noor Journal of Engineering Management and Computer Science, 32-42 , 2025
    2025
  • INTELLIGENT INTERNATIONAL IDENTIFICATION CARD
    A Adham, A Al-Barrak
    Al-Noor Journal of Engineering Management and Computer Science, 64-72 , 2025
    2025
  • Exploring the adoption of big data analytics in the oil and gas industry: a case study
    AS Al-Harrasi, HY Adarbah, AH Al-Badi, AK Shaikh, H Al-Shihi
    Journal of Business, Communication & Technology 3 (2), 1-16 , 2024
    2024
    Citations: 2
  • Preface: International Conferences of Buildings, Construction, and Environmental Engineering (BCEE)
    MY Fattah, M Al-Mukhtar, A Al-Dahawai, A Al-Barrak
    AIP Conference Proceedings 3219 (1), 010001 , 2024
    2024
  • CT scan and deep learning for COVID-19 detection
    SA Al-Janaby, A Al-Barrak
    AIP Conference Proceedings 3219 (1), 030002 , 2024
    2024
  • Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
    NTM Saja Majeed Mohammed, Alyaa Al-Barrak
    Ingénierie des Systèmes d’Information 29 (3), 1195-1208 , 2024
    2024
    Citations: 40
  • Preface: The fourth Al-Noor International Conference for Science and Technology (4NICST2022)
    A Adham, A Al-Barrak, H Al-Jelawy, SF Jawad
    AIP Conference Proceedings 3079 (1), 010001 , 2024
    2024
  • Modeling and analysis of thermal contrast based on LST algorithm for Baghdad city
    A Al-Barrak, HJ Alatta, SF Behadili, BH Sayyid, A Adham, MA Mahmood
    AIP Conference Proceedings 3079 (1), 040010 , 2024
    2024
    Citations: 2
  • Utilizing deep learning techniques to identify people by palm print
    MH Yasir, A Al-Barrak
    Journal of Engineering 30 (04), 87-98 , 2024
    2024
    Citations: 2
  • Preface: The First Virtual Conference of Al-Amarah University College on Oil and Gas-2022
    AA Ghabra, HO Shami, MH Khaddour, S Al-Rbeawi, FS Kadhim, ...
    CONFERENCE PROCEEDINGS OF THE FIRST VIRTUAL CONFERENCE OF AL-AMARAH … , 2023
    2023
  • Use of learning methods for gender and age classification based on front shot face images
    HR Hayawi, A Al-Barrak
    International Journal of Nonlinear Analysis and Applications 14 (3), 327-342 , 2023
    2023
  • Diagnostic COVID-19 based on chest imaging of COVID-19: A survey
    SA Ayyed, A Al-Barrak
    International Journal of Nonlinear Analysis and Applications 14 (1), 1295-1309 , 2023
    2023
  • Text image secret sharing with hiding based on color feature
    NJ Ibrahim, YH Ali, A Al-barrak, TA Rashid
    Periodicals of Engineering and Natural Sciences 10 (2), 358-375 , 2022
    2022
    Citations: 1
  • Workshop 2 Blockchain in Education
    A Al-Barrak
    2020 6th International Engineering Conference “Sustainable Technology and … , 2020
    2020
  • Internet of Things (IoT)
    A Al-Barrak
    2019 2nd International Conference on Engineering Technology and its … , 2019
    2019
    Citations: 1
  • Performance of BCH and RS Codes in MIMO System Using MPFEC Diversity Technique
    AB Al-Khalil, A Al-Barrak
    2018 International Conference on Advanced Science and Engineering (ICOASE … , 2018
    2018
    Citations: 3
  • Impact of alamouti space–time block coding on the performance of vehicle–to–vehicle communication
    A Al-Barrak, AB Al-Khalil
    2018 International Conference on Advanced Science and Engineering (ICOASE … , 2018
    2018
    Citations: 6

MOST CITED SCHOLAR PUBLICATIONS

  • Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
    NTM Saja Majeed Mohammed, Alyaa Al-Barrak
    Ingénierie des Systèmes d’Information 29 (3), 1195-1208 , 2024
    2024
    Citations: 40
  • Enhancing BER performance limit of BCH and RS codes using multipath diversity
    A Al-Barrak, A Al-Sherbaz, T Kanakis, R Crockett
    Computers 6 (2), 21 , 2017
    2017
    Citations: 26
  • Utilisation of multipath phenomenon to improve the performance of BCH and RS codes
    A Al-Barrak, A Al-Sherbaz, T Kanakis, R Crockett
    2016 8th Computer Science and Electronic Engineering (CEEC), 6-11 , 2016
    2016
    Citations: 11
  • Impact of alamouti space–time block coding on the performance of vehicle–to–vehicle communication
    A Al-Barrak, AB Al-Khalil
    2018 International Conference on Advanced Science and Engineering (ICOASE … , 2018
    2018
    Citations: 6
  • Performance of BCH and RS Codes in MIMO System Using MPFEC Diversity Technique
    AB Al-Khalil, A Al-Barrak
    2018 International Conference on Advanced Science and Engineering (ICOASE … , 2018
    2018
    Citations: 3
  • Exploring the adoption of big data analytics in the oil and gas industry: a case study
    AS Al-Harrasi, HY Adarbah, AH Al-Badi, AK Shaikh, H Al-Shihi
    Journal of Business, Communication & Technology 3 (2), 1-16 , 2024
    2024
    Citations: 2
  • Modeling and analysis of thermal contrast based on LST algorithm for Baghdad city
    A Al-Barrak, HJ Alatta, SF Behadili, BH Sayyid, A Adham, MA Mahmood
    AIP Conference Proceedings 3079 (1), 040010 , 2024
    2024
    Citations: 2
  • Utilizing deep learning techniques to identify people by palm print
    MH Yasir, A Al-Barrak
    Journal of Engineering 30 (04), 87-98 , 2024
    2024
    Citations: 2
  • Prediction of COVID-19 Disease and Infection Rate Based on Dense Net
    S Ali, A Al-Barrak
    Iraqi Journal of Science, 1664-1678 , 2025
    2025
    Citations: 1
  • Text image secret sharing with hiding based on color feature
    NJ Ibrahim, YH Ali, A Al-barrak, TA Rashid
    Periodicals of Engineering and Natural Sciences 10 (2), 358-375 , 2022
    2022
    Citations: 1
  • Internet of Things (IoT)
    A Al-Barrak
    2019 2nd International Conference on Engineering Technology and its … , 2019
    2019
    Citations: 1
  • A novel diversity technique to improve the channel coding performance in wireless communications
    A Al-Barrak, A Al-Sherbaz, R Crockett, T Kanakis
    University of Northampton , 2018
    2018
    Citations: 1
  • Safety assessment model for DoS attacks detection in wireless communication and network OS environments
    A Al-Barrak, SA Hameed Alazawi, AA Abdulhameed
    Intelligent Decision Technologies 19 (5), 3360-3368 , 2025
    2025
  • Utilizing Palm Print to Identify People Based on the Resnet50 Approach
    MH Yasir, A Al-Barrak
    Iraqi Journal of Science, 2071-2085 , 2025
    2025
  • Validating the Channel Capacity in V2V Communication based on SCME Channel Model with Turbo-BLAST Coding
    A Al-Barrak, A Adham, S Faisal
    Al-Noor Journal of Engineering Management and Computer Science, 32-42 , 2025
    2025
  • INTELLIGENT INTERNATIONAL IDENTIFICATION CARD
    A Adham, A Al-Barrak
    Al-Noor Journal of Engineering Management and Computer Science, 64-72 , 2025
    2025
  • Preface: International Conferences of Buildings, Construction, and Environmental Engineering (BCEE)
    MY Fattah, M Al-Mukhtar, A Al-Dahawai, A Al-Barrak
    AIP Conference Proceedings 3219 (1), 010001 , 2024
    2024
  • CT scan and deep learning for COVID-19 detection
    SA Al-Janaby, A Al-Barrak
    AIP Conference Proceedings 3219 (1), 030002 , 2024
    2024
  • Preface: The fourth Al-Noor International Conference for Science and Technology (4NICST2022)
    A Adham, A Al-Barrak, H Al-Jelawy, SF Jawad
    AIP Conference Proceedings 3079 (1), 010001 , 2024
    2024
  • Preface: The First Virtual Conference of Al-Amarah University College on Oil and Gas-2022
    AA Ghabra, HO Shami, MH Khaddour, S Al-Rbeawi, FS Kadhim, ...
    CONFERENCE PROCEEDINGS OF THE FIRST VIRTUAL CONFERENCE OF AL-AMARAH … , 2023
    2023