Browsing by Author "Sezer, Sakir"
Now showing items 1-20 of 21
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Analysis of Bayesian classification-based approaches for Android malware detection
Yerima, Suleiman; Sezer, Sakir; McWilliams, G. (Article)Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting ... -
Android Malware Detection Using Parallel Machine Learning Classifiers
Yerima, Suleiman; Sezer, Sakir; Muttik, I. (Conference)Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms ... -
Android malware detection: An eigenspace analysis approach
Yerima, Suleiman; Sezer, Sakir; Muttik, I. (Conference)The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. ... -
Cloud Computing in the Quantum Era
Kaiiali, Mustafa; Sezer, Sakir; Khalid, Ayesha (Conference)Cloud computing has become the prominent technology of this era. Its elasticity, dynamicity, availability, heterogeneity, and pay as you go pricing model has attracted several companies to migrate their businesses' services ... -
Continuous implicit authentication for mobile devices based on adaptive neuro-fuzzy inference system
Sezer, Sakir; Yao, F.; Yerima, Suleiman; Kang, B. (Conference)As mobile devices have become indispensable in modern life, mobile security is becoming much more important. Traditional password or PIN-like point-of-entry security measures score low on usability and are vulnerable to ... -
Deep android malware detection
McLaughlin, Niall; Martinez del Rincon, Jesus; Kang, BooJoong; Yerima, Suleiman; Miller, Paul; Sezer, Sakir; Safaei, Yeganeh; Trickel, Erik; Zhao, Ziming; Doupe, Adam; Gail Joon Ahn (Conference)In this paper, we propose a novel android malware detection system that uses a deep convolutional neural network (CNN). Malware classification is performed based on static analysis of the raw opcode sequence from a ... -
DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection
Yerima, Suleiman; Sezer, Sakir (Article)Android malware has continued to grow in volume and complexity posing significant threats to the security of mobile devices and the services they enable. This has prompted increasing interest in employing machine learning ... -
Dynalog: An Automated Dynamic Analysis Framework for Characterizing Android Applications
Alzaylaee, M.K.; Yerima, Suleiman; Sezer, Sakir (Conference)Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware ... -
EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning
Yerima, Suleiman; Sezer, Sakir; Alzaylaee, Mohammed K. (Conference)The Android operating system has become the most popular operating system for smartphones and tablets leading to a rapid rise in malware. Sophisticated Android malware employ detection avoidance techniques in order to hide ... -
Event-driven implicit authentication for mobile access control
Yerima, Suleiman; Sezer, Sakir; Yao, F.; Kang, B. (Conference)In order to protect user privacy on mobile devices, an event-driven implicit authentication scheme is proposed in this paper. Several methods of utilizing the scheme for recognizing legitimate user behavior are investigated. ... -
Fuzzy logic-based implicit authentication for mobile access control
Yerima, Suleiman; Yao, F.; Kang, B.; Sezer, Sakir (Conference)In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected ... -
High Accuracy Android Malware Detection Using Ensemble Learning
Yerima, Suleiman; Sezer, Sakir; Muttik, I. (Article)With over 50 billion downloads and more than 1.3 million apps in Google's official market, Android has continued to gain popularity among smartphone users worldwide. At the same time there has been a rise in malware targeting ... -
Improving Dynamic Analysis of Android Apps Using Hybrid Test Input Generation
Mohammed K. Alzaylaee; Yerima, Suleiman; Sezer, Sakir (Conference)The Android OS has become the most popular mobile operating system leading to a significant increase in the spread of Android malware. Consequently, several static and dynamic analysis systems have been developed to detect ... -
Machine learning-based dynamic analysis of Android apps with improved code coverage
Yerima, Suleiman; Alzaylaee, Mohammed K.; Sezer, Sakir; yerima (Article)This paper investigates the impact of code coverage on machine learning-based dynamic analysis of Android malware. In order to maximize the code coverage, dynamic analysis on Android typically requires the generation of ... -
MobiQ: A modular Android application for collecting social interaction, repeated survey, GPS and photographic data
Yerima, Suleiman; Loughlin, M.; Sezer, Sakir; Moriarty, J.; McCann, M.; McAneney; O'Hara, L; Tully, M.A.; Ell, P.S.; Millar, R.; McDonald, G. (Article)The MobiQ app for Android smartphones is a feature-rich application enabling a novel approach to data collection for longitudinal surveys. It combines continuous automatic background data collection with user supplied data. ... -
A Multi-Classifier Network-Based Crypto Ransomware Detection System: A Case Study of Locky Ransomware
O. Almashhadani, Ahmad; Kaiiali, Mustafa; Sezer, Sakir; O’Kane, Philip (Article)Ransomware is a type of advanced malware that has spread rapidly in recent years, causing significant financial losses for a wide range of victims, including organizations, healthcare facilities, and individuals. Modern ... -
N-gram Opcode Analysis for Android Malware Detection
Yerima, Suleiman; Sezer, Sakir; Kang, B.; McLaughlin, K. (Article)Android malware has been on the rise in recent years due to the increasing popularity of Android and the proliferation of third party application markets. Emerging Android malware families are increasingly adopting ... -
N-opcode Analysis for Android Malware Classification and Categorization
Yerima, Suleiman; Sezer, Sakir; Kang, B.; McLaughlin, K. (Conference)Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly ... -
A New Android Malware Detection Approach Using Bayesian Classification
Yerima, Suleiman; Sezer, Sakir; McWilliams, G.; Muttik, I. (Conference)Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting ... -
PageRank in Malware Categorization
Yerima, Suleiman; Sezer, Sakir; Kang, B.; McLaughlin, K. (Conference)In this paper, we propose a malware categorization method that models malware behavior in terms of instructions using PageRank. PageRank computes ranks of web pages based on structural information and can also compute ranks ...