Research Identity

I am a computer science researcher with a strong interest in the field of cybersecurity. I have a background in computer science and engineering, with a focus on network security and cryptography. I am passionate about exploring new technologies and methods for enhancing the security of digital systems and networks, and I have a track record of conducting innovative research in this area.

I am a member of a research team that focuses on the development of new technologies and algorithms for detecting and preventing cyber threats. My team and I are working on a number of projects that are aimed at enhancing the security of critical infrastructure systems, such as power grids and water treatment facilities.

In addition to my research work, I am also involved in teaching and mentoring undergraduate and graduate students in the field of cybersecurity. I believe that it is important to provide the next generation of computer science researchers with the knowledge, skills, and expertise they need to succeed in the field, and I enjoy sharing my passion for cybersecurity, computer networks with my students.

Overall, my research identity in computer science is focused on exploring new technologies and methods for enhancing the security of digital systems and networks.


I have a passion for teaching and research and for thus I am pursuing an academic career. the depth of my experience in Cybersecurity, Computer Networks, Artificial inelegance.  My achievements range from setting publication research papers and teaching.

– Research thrusts

This section presents the existing and ongoing work in each research area mentioned above in more detail. In my PhD work, I worked in Distributed Denial-of-Service (DDoS) attacks are incidents in a cloud computing environment that cause major performance disturbances [1].

Intrusion-detection and prevention system (IDPS) are tools to protect against such incidents, and the correct placement of IDS/IPS systems on networks is of great importance for optimal monitoring and for achieving maximum effectiveness in protecting a system[2]. Even with such systems in place, however, the security level of general cloud computing must be enhanced. More potent attacks attempt to take control of the cloud environment itself; such attacks include malicious Virtual-Machine (VM) hyperjacking as well as traditional network-security threats such as traffic snooping (which intercepts network traffic), address spoofing and the forging of VMs or IP addresses. It is difficult to manage a host-based IDPS (H-IDPS) because information must be configured and managed for every host, so it is vital to ensure that security analysts fully understand the network and its context in order to distinguish between false positives and real problems [3]. For this, it is necessary to know the current most important classifiers in machine learning, as these offer feasible protection against false-positive alarms in DDoS attacks[4].

While for my master’s degree, which was by full research time. I worked in IP phones privacy and security, which have benefited greatly from the ever-increasing capabilities of computer hardware in general, including faster microprocessors, larger memory capacity, and greater network bandwidth. A single IP phone shipping in 2010 has far more computing capacity than most of the early PBXs[5].  Today, while many companies might still choose to buy from a single vendor for the sake of convenience, the reality is that in the era of interoperable protocol standards like Session Initiation Protocol (SIP), the companies are no longer required to buy from the same vendor.  Thus, the most popular SIP authentication schemes were studied intensively. Furthermore, an improvement from previous cryptographic scheme known as Yoon scheme, which proposed for SIP authentication has done efficiency in security, but costly on time. Thus, it led us to introduce an enhancing way for SIP authentication scheme based on Elliptic Curve Cryptography (ECC) with lookup tables and scalar multiplication.

  • Interdisciplinary work

Cybersecurity, Computer Networks, Cloud Computing, Artificial intelligence, Optimization problems, Swarm intelligence

  • Conclusion and Future Plans

This concludes a brief overview of my work over the last roughly 15 years. Regrettably, several interesting efforts had to be omitted for the sake of brevity. In the future, I am particularly excited about the several research areas: Blockchain security, Industry 4.0 security and 5G security and of course Data science.  Further, developing a new Mathematical model in Deep learning algorithm for Cybersecurity and Data Science. I believe that I am uniquely capable to handle the above challenges, based on my expertise in mixed qualitative and quantitative research methods


[1]        A. N. Jaber, M. F. Zolkipli, M. A. Majid, and S. Anwar, “Methods for Preventing Distributed Denial of Service Attacks in Cloud Computing,” Advanced Science Letters, vol. 23, no. 6, pp. 5282-5285, 2017.

[2]        A. Naser, M. F. Zolkipli, S. Anwar, and M. S. Al-Hawawreh, “Present status and challenges in cloud monitoring framework: a survey.” pp. 201-201.

[3]        M. K. Hussein, N. B. Zainal, and A. N. Jaber, “Data security analysis for DDoS defense of cloud based networks.” pp. 305-310.

[4]        A. N. Jaber, M. F. B. Zolkipli, and M. B. A. Majid, “Security Everywhere Cloud: An Intensive Review of DoS and DDoS Attacks in Cloud Computing,” Journal of Advanced & Applied Sciences (JAAS), vol. 3, no. 5, pp. 152-158, 2015.

[5]        A. N. Jaber, “Improving the Efficiency of SIP Authentication Based on the Per-calculated Look-up Table,” Universiti Sains Malaysia, 2013.