taha mohammad almasri

@digitalfuture.sa

AI and BI Specialist, Digital Future Company (Department: Data Analytics and AI Solutions)
Digital Future Company (Ministry of Interior - Client)

taha mohammad almasri


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https://researchid.co/tahaalmasri94

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence

FUTURE PROJECTS

AI-Driven Bio-Surveillance Systems for Emerging Health Threats

Developing advanced mobile edge computing frameworks to detect multiple biological threats in real-time, integrating machine learning and IoT.


Applications Invited
Collaborators in AI/ML and PhD students in Computer Science.

Secure Data Analytics Platforms for Government Infrastructure

Designing ETL pipelines and BI dashboards with enhanced security for large-scale data projects, focusing on compliance and performance.


Applications Invited
Industry partners and MSc students in Data Engineering.

LP Models for Arabic Sentiment Analysis in Fintech

Fine-tuning large language models (LLMs) for text analysis in financial applications, with RAG integration.


Applications Invited
Collaborators in NLP and undergraduate interns.
3

Scopus Publications

63

Scholar Citations

3

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Enabling multiple health security threats detection using mobile edge computing
    Mohammad Al-Zinati, Taha Almasri, Mohammad Alsmirat, Yaser Jararweh
    Simulation Modelling Practice and Theory, 2020
  • A Mobile-Edge Computing Bio-Surveillance Framework for Multiple Biological Attacks Detection
    Mohammad Al-Zinati, Taha Almasri, Mohammad Alsmirat, Yaser Jararweh
    2019 6th International Conference on Internet of Things Systems Management and Security Iotsms 2019, 2019
    Hostile biological attacks are becoming increasingly dangerous and life-threatening. Nevertheless, most of these attacks are not detected in a timely manner. Current biosurveillance systems depend on the data gathered from different medical sources such as hospitals and specialized laboratories. Recently, bio-surveillance systems start to utilize recent advances in sensors and IoT technologies to improve their real-time detection of health security threats. Despite the great improvements shown by these systems, there is no evidence on their effectiveness in case of multiple concurrent attacks. Triggering multiple concurrent attacks further complicates the problem as gathered monitoring information tend to obfuscate each other. To address this issue, we propose a multi-agent framework for multiple biological threat detection. The proposed framework utilizes recent advances in wearable sensors to monitor human vital signs. Moreover, intelligent agents are defined in the context of mobile-edge computing platforms to group monitoring information into focused clusters. These clusters are then used to effectively detect multiple concurrent health security threats. The evaluation of the proposed frame-work shows its effectiveness in detecting concurrent biological attacks.
  • Evaluation of security regarding Z-Wave wireless protocol
    Muneer Bani Yassein, Wail Mardini, Taha Almasri
    ACM International Conference Proceeding Series, 2018
    In the early adoptions of Z-Wave protocol for smart home automation, security issues were not taken into consideration. As this protocols got higher adoption rates, more security studies were performed to increase the security level of this protocol and solve many of the security bugs founds. The first issue, the protocols has no encryption and weak security procedures adopted to protect the commands during transmissions. There were significant improvements in order to make this protocol security levels reach AES 128-bit encryption, which is the same level of protection major banks use. In this paper, our researcher is focused on vulnerabilities, weakness and how the administrators can protect their home area networks (HANs) that uses Z-wave protocol with an additional security.

RECENT SCHOLAR PUBLICATIONS

  • Enabling multiple health security threats detection using mobile edge computing
    M Al-Zinati, T Almasri, M Alsmirat, Y Jararweh
    Simulation Modelling Practice and Theory 101, 101957 , 2020
    2020
    Citations: 38
  • A mobile-edge computing bio-surveillance framework for multiple biological attacks detection
    M Al-Zinati, T Almasri, M Alsmirat, Y Jararweh
    2019 Sixth International Conference on Internet of Things: Systems … , 2019
    2019
    Citations: 3
  • Evaluation of security regarding Z-Wave wireless protocol
    MB Yassein, W Mardini, T Almasri
    Proceedings of the Fourth International Conference on Engineering & MIS 2018 … , 2018
    2018
    Citations: 22

MOST CITED SCHOLAR PUBLICATIONS

  • Enabling multiple health security threats detection using mobile edge computing
    M Al-Zinati, T Almasri, M Alsmirat, Y Jararweh
    Simulation Modelling Practice and Theory 101, 101957 , 2020
    2020
    Citations: 38
  • Evaluation of security regarding Z-Wave wireless protocol
    MB Yassein, W Mardini, T Almasri
    Proceedings of the Fourth International Conference on Engineering & MIS 2018 … , 2018
    2018
    Citations: 22
  • A mobile-edge computing bio-surveillance framework for multiple biological attacks detection
    M Al-Zinati, T Almasri, M Alsmirat, Y Jararweh
    2019 Sixth International Conference on Internet of Things: Systems … , 2019
    2019
    Citations: 3

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

Publication 1: "A Mobile-Edge Computing Bio-Surveillance Framework for Multiple Biological Threat Detection" (Aug 2019, Conference Paper).
Publication 2: "Enabling Multiple Health Security Threats Detection Using Mobile Edge Computing" (Aug 2019, Journal Article, Simulation Modelling Practice and Theory).
Publication 3: "Evaluation of Security Regarding Z-Wave Wireless Protocol" (Jun 2018, Conference Paper).

Industry, Institute, or Organisation Collaboration

Digital Future Company (collaboration with Ministry of Interior, KSA); Liwwa Fintech (Jordan); JOHUD (Jordan); Jordan University of Science and Technology

INDUSTRY EXPERIENCE

over 3 years at Digital Future Company in AI/BI for government projects; 4 months at Liwwa as Software Engineer; over 3 years at JOHUD and JUST teaching and coordinating

SOCIAL, ECONOMIC, or ACADEMIC BENEFITS

Contributions to health security through bio-surveillance research; Enhanced decision-making in government via BI tools; Training over 100 students in full-stack development at JOHUD.