Suchergebnisse - Characterization and Detection of Android Malware

KronoDroid: Time-based Hybrid-featured Dataset for Effective Android Malware Detection and Characterization von Guerra-Manzanares, Alejandro, Bahsi, Hayretdin, Nõmm, Sven

“… ). Critical factors to take into account when aiming to build more effective, robust, and long-lasting Android malware detection systems …”
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A novel Sybil attack detection scheme in mobile IoT based on collaborate edge computing von Junwei Yan, Tao Jiang, Liwei Lin, Zhengyu Wu, Xiucai Ye, Mengke Tian, Yong Wang

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Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions von Nguyet Quang Do, Ali Selamat, Ondrej Krejcar, Enrique Herrera-Viedma, Hamido Fujita

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Multilayer Framework for Botnet Detection Using Machine Learning Algorithms von Wan Nur Hidayah Ibrahim, Syahid Anuar, Ali Selamat, Ondrej Krejcar, Ruben Gonzalez Crespo, Enrique Herrera-Viedma, Hamido Fujita

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Android malware concept drift using system calls: Detection, characterization and challenges von Guerra-Manzanares, Alejandro, Luckner, Marcin, Bahsi, Hayretdin

“… •Demonstrates the existence of concept drift issues in Android malware detection …”
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Towards a Network-Based Framework for Android Malware Detection and Characterization von Lashkari, Arash Habibi, A.Kadir, Andi Fitriah, Gonzalez, Hugo, Mbah, Kenneth Fon, A. Ghorbani, Ali

“… Mobile malware is so pernicious and on the rise, accordingly having a fast and reliable detection system is necessary for the users …”
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Android Malware: Detection, Characterization, and Mitigation von Zhou, Yajin

“… These malicious apps have posed serious threats to user security and privacy. The primary goal of my research is to understand and mitigate the Android malware threats …”
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Dissecting Android Malware: Characterization and Evolution von Zhou, Yajin, Jiang, Xuxian

“… The popularity and adoption of smart phones has greatly stimulated the spread of mobile malware, especially on the popular platforms such as Android …”
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DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling von Haipeng Cai, Na Meng, Ryder, Barbara, Yao, Daphne

“… Most existing Android malware detection and categorization techniques are static approaches, which suffer from evasion attacks, such as obfuscation …”
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Lightweight, Effective Detection and Characterization of Mobile Malware Families von Elish, Karim O., Elish, Mahmoud O., Almohri, Hussain M. J.

“… Despite numerous approaches and previous studies to develop solutions for detecting and preventing Android malware, the rapid continuous development of new malware variants requires a careful …”
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Uncovering the Face of Android Ransomware: Characterization and Real-Time Detection von Chen, Jing, Wang, Chiheng, Zhao, Ziming, Chen, Kai, Du, Ruiying, Ahn, Gail-Joon

“… In recent years, we witnessed a drastic increase of ransomware, especially on popular mobile platforms including Android …”
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DeepFlow: Deep learning-based malware detection by mining Android application for abnormal usage of sensitive data von Dali Zhu, Hao Jin, Ying Yang, Di Wu, Weiyi Chen

“… Traditional malware detection approaches based on signatures or abnormal behaviors are invalid when dealing with novel malware …”
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MCGDroid: An android malware classification method based on multi-feature class-call graph characterization von He, Mingkun, Ge, Jike, Chen, Zuqin, Ling, Jin, Kong, Weiquan

“… Malicious software (malware) attacks constitute a major category of security risks affecting the Android operating system …”
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Android Malware Detection: an Eigenspace Analysis Approach von Yerima, Suleiman Y, Sezer, Sakir, Muttik, Igor

“… Hence, in this paper we propose and evaluate a machine learning based approach based on eigenspace analysis for Android malware detection using features derived from static analysis characterization …”
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SAC: Collaborative learning of structure and content features for Android malware detection framework von Yang, Jin, Liang, Huijia, Ren, Hang, Jia, Dongqing, Wang, Xin

“… With the rapid development of Internet of Things (IoT) technology, Android devices have increasingly become primary targets for malware attacks …”
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An Empirical Study on Android Malware Characterization by Social Network Analysis von Zhao, Haojun, Wu, Yueming, Zou, Deqing, Jin, Hai

“… Android malware detection has always been a hot research field. Prior work has validated that graph-based Android malware detection methods are effective …”
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Android malware detection: An eigenspace analysis approach von Yerima, Suleiman Y., Sezer, Sakir, Muttik, Igor

“… Hence, in this paper we propose and evaluate a machine learning based approach based on eigenspace analysis for Android malware detection using features derived from static analysis characterization …”
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BLADE: Robust malware detection against obfuscation in android von Sihag, Vikas, Vardhan, Manu, Singh, Pradeep

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An Android Malware Detection Approach Using Weight-Adjusted Deep Learning von Li, Wenjia, Wang, Zi, Cai, Juecong, Cheng, Sihua

“… ) which severely threaten the security of Android smartphones, we propose an Android malware characterization and identification approach that uses deep learning algorithm to address the urgent need for malware detection …”
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Android Malware Characterization Using Metadata and Machine Learning Techniques von Guzmán, Antonio, Muñoz, Alfonso, Hernández, José Alberto, Martín, Ignacio

“… ) other features publicly available at Android markets are more relevant in detecting malware, such as the application developer and certificate issuer; and (3 …”
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