A Data Mining Classification Approach for Behavioral Malware Detection by Monire Norouzi, Alireza Souri, Majid Samad Zamini

“…In this paper we present a data mining classification approach to detect malware behavior. We proposed different classification methods in order to detect malware based on the feature and behavior of each malware. …”
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Method of anti-confusion texture feature descriptor for malware images by Yashu LIU, Zhihai WANG, Hanbing YAN, Yueran HOU, Yukun LAI

Subjects: “…malware visualization…”
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Active-probing based distributed malware master detection system by Cheng-xiang SI, Bo SUN, Wen-han YANG, Hui-lin ZHANG, Xiao-nan XUE

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Malware classification method based on static multiple-feature fusion by Bo-wen SUN, Yan-yi HUANG, Qiao-kun WEN, Bin TIAN, Peng WU, Qi LI

Subjects: “…malware…”
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HD-SEIRS Malware Propagation Model in Heterogeneous Complex Networks by Elham Asadi, Soodeh Hosseini

Subjects: “…malware propagation modeling…”
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Multi-granularity Android malware fast detection based on opcode by Xuetao ZHANG, Meng SUN, Jinshuang WANG

“…The detection method based on opcode is widely used in Android malware detection,but it still contains some problems such as complex feature extraction method and low efficiency.In order to solve these problems,a multi-granularity fast detection method based on opcode for Android malware was proposed.Multi-granularity refers to the feature based on the bag of words model,and with the function as basic unit to extract features.By step-by-level aggregation feature,the APK multi-level information is obtained.The log length characterizes the scale of the function.And feature can be compressed and mapped to improve the efficiency and construct the corresponding classification model based on the semantic similarity of the Dalvik instruction set.Tests show that the proposed method has obvious advantages in performance and efficiency.…”
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A Malware Detection Scheme Based on Mining Format Information by Jinrong Bai, Junfeng Wang, Guozhong Zou

“…Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. …”
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An adaptive neuro-fuzzy inference system for multinomial malware classification by Amos Orenyi Bajeh, Mary Olayinka Olaoye, Fatima Enehezei Usman-Hamza, Ikeola Suhurat Olatinwo, Peter ogirima Sadiku, Abdulkadir Bolakale Sakariyah

Subjects: “…Malware…”
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Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods by Pavel Novak, Vaclav Oujezsky

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Research on Operators Mobile Malware Protection Architecture and Key Technologies by Tao Chen, Peng Gao, Xuetao Du, Shan Xue, Manzhi ang

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MALVADA: A framework for generating datasets of malware execution traces by Razvan Raducu, Alain Villagrasa-Labrador, Ricardo J. Rodríguez, Pedro Álvarez

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Mining behavior pattern of mobile malware with convolutional neural network by Xin ZHANG, Weizhong QIANG, Yueming WU, Deqing ZOU, Hai JIN

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Malware detection technology analysis and applied research of android platform by Wei-ping WEN, Rui MEI, Ge NING, Liang-liang WANG

“…For the Android platform security problem, a mobile client and server collaborative malware detection pro-posal was proposed, where mobile client application was mainly based on permission detection technology and imple-mented lightweight testing. …”
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Research on Anti-Trojan Malware Mechanism Based on Characteristic Behavior by Weifu Zou, Yiying Zhang, Suxiang Zhang, Chengyue Yang

Subjects: “…Trojan malware…”
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HoneyBow:an automated malware collection tool based on the high-interaction honeypot principle by ZHUGE Jian-wei1, HAN Xin-hui1, ZHOU Yong-lin2, SONG Cheng-yu1, GUO Jin-peng1, ZOU Wei1

Subjects: “…malware…”
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Malware recognition approach based on self‐similarity and an improved clustering algorithm by Jinfu Chen, Chi Zhang, Saihua Cai, Zufa Zhang, Lu Liu, Longxia Huang

“…Abstract The recognition of malware in network traffic is an important research problem. …”
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Malware Detection in Self-Driving Vehicles Using Machine Learning Algorithms by Seunghyun Park, Jin-Young Choi

“…In this study, we propose a machine learning-based data analysis method to accurately detect abnormal behaviors due to malware in large-scale network traffic in real time. …”
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Mobile malware traffic detection approach based on value-derivative GRU by Hanxun ZHOU, Chen CHEN, Runze FENG, Junkun XIONG, Hong PAN, Wei GUO

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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

Subjects: “…malware detection…”
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Graph representation federated learning for malware detection in Internet of health things by Mohamed Amjath, Shagufta Henna, Upaka Rathnayake

“…However, the increasing prevalence of malware threats presents significant security and privacy challenges. …”
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