NZEKET NJOYA ALIMA
Software engineer and Computer science teacher in Hight school since 6 years old. PhD Student on AI and Cybersecurity at University of Ngaoundere. Founder and promoter of Adamawa Code Kids, a non profit organisation which aims to value and promote the uses of ICT tools among primary and secondary schools in rural areas. 2022 Techwomen alumni
I am characterized by
Interested on Gender issues; I am most supportive of other persons and particularly women and young girls ; I am good planner and organiser and I think that No one can progress alone. We always need someone somewhere. So teamwork is essential and useful, because alone we go faster but together we go further.
Professional experience
I have experiences on front-end technologies, programming languages as Python, PHP, java and javascript; I also have experiences on civic leadership and personal management.
Current responsibilities
Computer engineering teacher at University Institute of Technology of Ngaoundere and Computer science teacher in Hight school
Research Interests
AI and Cybersecurity. Also interested on Robotics, Machine learning and Data science
Projects
Level of studies
Ph.D
Current Studies
Ph.D ongoing
Description of current research
To highlight the dynamic and evolving character of a phishing attack, our PhD research, gives a new approach which uses Imitation Learning-based characterization of interactions during social engineering cybercrimes to detect social engineering attacks based on mobile payment. In this technic an agent (a learning machine) is trained to perform a task from demonstrations by learning a mapping between observations and actions. The promise of imitation here is to facilitate learning by allowing the learner (our final system) to observe a teacher (phisher) in action.
Description of past research
Our previous work focused on the theme "Characterisation and detection of phishing attacks directed towards mobile payment: the case of MTN MoMo and Orange Money". The general objective was to propose a model that would allow the detection of money transfer attacks observed in the MTN and Orange operators. The specific objectives were (1) To study the concepts related to social engineering attacks in general and mobile payment phishing in particular. (2) To characterise all the possibilities of mobile payment scams observed in the money transfer operators Orange and MTN and to see in which context to design a solution model based on reinforcement learning (RL) in order to anticipate user victimisation. (3) To make this attack formal by building a sequence of automata that indicate at each step the behaviour of the scammer towards his victim; and finally (4) To detect vulnerabilities from the model obtained using the two reinforcement learning methods: Q-learning and Markov Decisional Models.
Publications
a.nzeket[AERO]cycomai[POINT]com
Google scholar page
Social media pages
LinkedIn: https://www.linkedin.com/in/alima-nzeket-epse-bessama-bb9aab10a/
Facebook: https://web.facebook.com/alimalafortune
Twitter : https://twitter.com/AlimaNzeket?t=61JYu1Vo0v3CcpKSVHKS0g&s=08
Personal/Business Web
witaada.com