PHOTO 4x4 WITH A WHITE BACKGROUND | SIMÉ NYASSI Virgile I am a Cameroonian, I defended the master thesis in computer science at the University of Ngaoundere and my topic "A Game Theoretical Model for Anticipating Email Spear-Phishing Strategies" was published in the EAI Endorsed Transactions on Scalable Information Systems. Currently, I am currently doing a PhD thesis and my project aims to mitigate vishing attacks through a suitable analysis of emotions contained in phone conversations using AI models. |
I am characterized by | Industrious, thrustworthy, and someone we could rely on to carry out my duties on time and to exacting standards. Moreover, I am very ambitious and a high achiever. Furthermore, I like movies, musics and sport. |
Professional experience |
December 2019: IT Manager Assistant at IUGET. |
Current responsibilities | |
Research Interests | My research field is cybersecurity, more precisely in artificial intelligence and phone scams. |
Projects | Emoti-Shing |
Level of studies | Ph.D |
Current Studies | Ph.D ongoing |
Description of current research | Receiving a call from a scammer who intends to manipulate someone into dishing out sensitive information or losing money from one’s mobile money account is the order of the day in our society. Thanks to Smartphones, people can perform several operations anytime, anywhere at a go, access remote accounts, withdraw cash, deposit and transfer money, make payments to utility services, and shop via the mobile device. Cybercriminals use vishing social engineering techniques to manipulate humans via calls and exploit the human nature of trust to steal users’ data and lure them into financial loses. Unlike existing works that rely on spoofable information such as call numbers, this work proposes Emoti-Shing, a novel approach that relies on the Visher’s biological features : emotions, from the voice. We use Hidden Markov Model of artificial intelligence to model the vulnerability states of a potential victim to a scam call observed via sequences of emotions that can be extracted from a scam conversation. The proposed model suggests a mean through which vishing scam can be tracked by analysing the manner in which a phone call audio conversation is done, which is independent of the caller, the content of the call and the education a potential victim may have as far as vishing is concerned. Enabling machines to intelligently identify scam calls based on "how the conversation is made" can go a long way to reduce vishing attacks. Our main contribution is to incite research in the area of vishing scam detection through voice mining by means of emotions. We aim to show that this approach has a potential of increasing vishing scam detection since it relies on the intrinsic and biological characteristics of humans that cannot be easily masked or spoofed as the case with other solutions. |
Description of past research | A solution to help victims against phishing is anticipating and leveraging impacts related to phisher actions. In this regard, this work reshapes game theoretical logic between Intrusion Detection System (IDS) agents and insiders to email spear-phishing interactions. The email spear-phishing attack is designed as a non-cooperative and repeated game between opponents. Additionally, this work relies on Quantal Response Equilibrium (QRE) to build a game theoretical approach to predict the phisher’s future intent based on past actions of both players. This approach is coupled with a recommendation strategy of appropriate allocation of resources to invest to strengthen user protection. Simulations on spear-phishing scenarios demonstrate the ability of the final system to intuitively guess the most likely phisher decisions. This work provides intelligence to spearphishing detectors and humans such that they can anticipate next phisher actions. |
Publications |
"A Game Theoretical Model for Anticipating Email Spear-Phishing Strategies" In EAI Endorsed Transactions Scalable Information Systems, 2020. "True Request–Fake Response: A New Trend of Spear Phishing Attack" In Journal of Network Security, 2019. |
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