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Browsing ICTs including Big Data and Artificial Intelligence by Author "Ouya, Samuel"

Now showing items 1-8 of 8

Android Malware Classification: Updating Features Through Incremental Learning Approach(UFILA)

Sawadogo, Zakaria; Mendy, Gervais; Dembelle, Jean Marie; Ouya, Samuel (IEEE Xplore, 2022-03-11)

Exponential growth of the use of connected objects, in particular of smartphones, is the consequence of the digitization of services. All types of applications, from the least critical to the most critical are available ...
Android malware detection: An in-depth investigation of the impact of the use of imbalance datasets on the efficiency of machine learning models

Sawadogo, Zakaria; Dembele, Jean-Marie; Mendy, Gervais; Ouya, Samuel (IEEE Xplore, 2023-03-29)

Machine learning techniques have become an essential part of research into the detection and classification of malicious applications. There are several approaches or algorithms that learn from existing data and predict ...
Android Malware Detection: Feature Update Using Incremental Learning Approach: Further Investigation of UFILA

Sawadogo, Zakaria; Dembelle, Jean Marie; Mendy, Gervais; Ouya, Samuel (IEEE Xplore, 2023-03-29)

Several kinds of mobile applications are available on platforms offering various services to users. Both malware and good applications are found in software repositories, which is a major cybersecurity problem. To address ...
Android malware detection: Investigating the impact of imbalanced data-sets on the performance of machine learning models

Sawadogo, Zakaria; Mendy, Gervais; Marie Dembele, Jean; Ouya, Samuel (IEEE Xplore, 2022-03-11)

Artificial intelligence has revolutionized many areas of research, including research on malicious application detection and classification. Nowadays, there are many approaches that learn from existing data and predict the ...
DeepMalOb: Deep Detection of Obfuscated Android Malware

Sawadogo, Zakaria; Jean-Marie, Dembele; Attoumane, Tahar; Gervais, Mendy; Ouya, Samuel (Springer, 2023-02-21)

The detection of malware android became very crucial with the use of obfuscation techniques by developers of malicious applications. In the literature several approaches have been proposed to take into account certain ...
Mid@ndro: a Middleware Architecture for Malware Detection on Android

Sawadogo, Zakaria; Thioye, Babacar; Gaye, Ibrahima; Dembele, Jean-Marie; Mendy, Gervais; Ouya, Samuel (IEEE Xplore, 2023-12-29)

Android is a highly popular platform for mobile devices; however, it is also vulnerable to malware attacks due to the platform's ability to allow users to install apps from unverified sources. This increases the risk of ...
Towards a DeepMalOb Improvement in the Use of Formal Security Risk Analysis Methods

Sawadogo, Zakaria; Khan, Muhammad Taimoor; Dembelle, Jean Marie; Mendy, Gervais; Ouya, Samuel (IEEE Xplore, 2023-12-29)

Researchers are concerned about the detection of obfuscated Android malware, and multiple studies have been proposed to address certain obfuscation techniques. However, the comprehensive consideration of all obfuscation ...
Zero-Vuln: Using deep learning and zero-shot learning techniques to detect zero-day Android malware

Sawadogo, Zakaria; Dembele, Jean-Marie; Mendy, Gervais; Ouya, Samuel (IEEE Xplore, 2023-09-22)

The prevalence of cyber security threats, such as the Android Zero-day vulnerability, is becoming increasingly worrisome. With the widespread use of Android-powered mobile devices, attackers are leveraging zero-day ...

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Browsing ICTs including Big Data and Artificial Intelligence by Author "Ouya, Samuel"

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