Wisam Makki Salim

@aliraqia.edu.iq

Al-Iraqia University

Wisam Makki Salim


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https://researchid.co/wisam1987
Wissam Makki Salim is an academic researcher in Artificial Intelligence (AI) and Prompt Engineering. His primary research focus is on exploring and implementing advanced AI methodologies to strengthen network security frameworks. He is dedicated to developing innovative solutions that utilize prompt engineering techniques to build adaptive and intelligent defenses against sophisticated cyber threats, effectively bridging the gap between AI’s potential and its practical application in network security. Alongside his research, Wissam has played pivotal roles in various committees, including the ministerial e-learning team during the COVID-19 pandemic, the Digital Transformation Committee at the Ministry of Higher Education overseeing university digitalization, the assessment exams committee for the medical group, and as a national evaluator for technical engineering colleges. In these roles, he supervised and visited numerous public and private universities to enhance their digital infra

EDUCATION

Al-Mustafa Private University: Baghdad, Iraq, IQ
2014-09-01 to 2018-07-01 | Bachelor's (College of Engineering Technologies)
Education

Azad University: Tehran, IR
2020-09-22 to 2023-10-04 | Master (Computer Engineering)
Education

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computer Networks and Communications
2

Scopus Publications

7

Scholar Citations

1

Scholar h-index

Scopus Publications

  • A New Descriptor Based on Machine Learning for Intrusion Detection in Wireless Sensor Networks WNSs
    Oday Oday, Oday Ali Hassen, Wisam Makki Salim, Selvakumar Manickam, Nur Azman Abu
    Journal of Intelligent Systems and Internet of Things, 2025
    Wireless sensor networks have become a vital component of the infrastructure for many modern applications. With the increasing use of wireless sensor networks, the challenges facing these networks in the field of security are escalating and growing, and with the rapid advancement of wireless communication technology, these networks are exposed to increasing, complex and continuous threats. Our research is characterized by innovation in the field of security technology to enhance protection, repel attacks and detect intrusions, among these innovations are intrusion detection systems based on machine learning as a creative and new solution. In this research, we highlight the effectiveness of different machine learning algorithms, such as supervised and unsupervised learning, in detecting anomalies and intrusions within wireless sensor networks, as our goal focuses on enhancing the security of wireless sensor networks (WSNs) by adopting intrusion detection systems (IDS) based on machine learning techniques. In this context, with a focus on using the WSN-DS dataset. The results of this research showed that machine-learning models could improve the security efficiency of wireless sensor networks by achieving accuracy ranging from 91% to 99.7% and testing time ranging from 0.006 to 0.1249, which enhances the ability to effectively retrieve and detect threats in real time.
  • Prompt Engineering: Unleashing the Power of Large Language Models to Defend Against Social Engineering Attacks
    Prof. Bashar M Nema, Ahmed I Nezer, Wisam Makki Salim
    Iraqi Journal for Computer Science and Mathematics, 2024
    Prompt Engineering is an emerging area of study that pertains to the act of conceptualizing, perfecting, and executing prompts that guide an AI model to an intended purpose. The AI model is an LLM, which they are the “hit” of our time and probably the controversial type of AI. They are capable of executing several tasks using natural language processing algorithms. Due to their ease of use and fast development, they are becoming highly dependent. We found that to interact correctly with these models and gain the best performance, several techniques should be taken into consideration. Moreover, there are additional methods or tips to write a good prompt.

RECENT SCHOLAR PUBLICATIONS

  • Governing Generative AI in Higher Education: From Crisis Management to Strategic Integration (2026-2030)
    W Makki Salim
    Available at SSRN 6007354 , 2026
    2026
  • A New Descriptor Based on Machine Learning for Intrusion Detection in Wireless Sensor Networks WNSs
    NAA Esraa Saleh Alomari1, Oday Ali Hassen1, 2, *, Wisam Makki Salim3 ...
    Journal of Intelligent Systems and Internet of Things 16 (01), 13 , 2025
    2025
    Citations: 6
  • Prompt Engineering: Unleashing the Power of Large Language Models to Defend Against Social Engineering Attacks
    AI Nezer, B AlEsawi, WM Salim
    Iraqi Journal For Computer Science and Mathematics 5 (3), 404-416 , 2024
    2024
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • A New Descriptor Based on Machine Learning for Intrusion Detection in Wireless Sensor Networks WNSs
    NAA Esraa Saleh Alomari1, Oday Ali Hassen1, 2, *, Wisam Makki Salim3 ...
    Journal of Intelligent Systems and Internet of Things 16 (01), 13 , 2025
    2025
    Citations: 6
  • Prompt Engineering: Unleashing the Power of Large Language Models to Defend Against Social Engineering Attacks
    AI Nezer, B AlEsawi, WM Salim
    Iraqi Journal For Computer Science and Mathematics 5 (3), 404-416 , 2024
    2024
    Citations: 1
  • Governing Generative AI in Higher Education: From Crisis Management to Strategic Integration (2026-2030)
    W Makki Salim
    Available at SSRN 6007354 , 2026
    2026

Publications

Prompt Engineering: Unleashing the Power of Large Language Models to Defend Against Social Engineering Attacks
Iraqi Journal for Computer Science and Mathematics
2024 | Journal article
DOI: 10.52866/
EID: 2-
Part of ISSN: 27887421
Contributors: Nezer, A.I.; Nema, B.M.; Salim, W.M.

A New Descriptor Based on Machine Learning for Intrusion Detection in Wireless Sensor Networks WNSs
Journal of Intelligent Systems and Internet of Things
2025 | Journal article
DOI: 10.54216/
Contributors: Esraa Saleh Alomari; Oday Ali Hassen; Wisam Makki Salim; Selvakumar Manickam; Nur Azman Abu