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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Identifying Unknown Android Malware with Feature Extractions and Classification Techniques
Ludovic Apvrille, Axelle Apvrille
2015 IEEE Trustcom/BigDataSE/ISPA (2015), pp. 182-189
Closed Access | Times Cited: 18

Showing 18 citing articles:

Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers
Wei Wang, Yuanyuan Li, Xing Wang, et al.
Future Generation Computer Systems (2017) Vol. 78, pp. 987-994
Closed Access | Times Cited: 209
A Taxonomy and Qualitative Comparison of Program Analysis Techniques for Security Assessment of Android Software
Alireza Sadeghi, Hamid Bagheri, Joshua Garcia, et al.
IEEE Transactions on Software Engineering (2016) Vol. 43, Iss. 6, pp. 492-530
Open Access | Times Cited: 137
A Deep Learning Approach to Android Malware Feature Learning and Detection
Xin Su, Dafang Zhang, Wenjia Li, et al.
2015 IEEE Trustcom/BigDataSE/ISPA (2016)
Closed Access | Times Cited: 109
Constructing Features for Detecting Android Malicious Applications: Issues, Taxonomy and Directions
Wei Wang, Meichen Zhao, Zhenzhen Gao, et al.
IEEE Access (2019) Vol. 7, pp. 67602-67631
Open Access | Times Cited: 98
An HMM and structural entropy based detector for Android malware: An empirical study
Gerardo Canfora, Francesco Mercaldo, Corrado Aaron Visaggio
Computers & Security (2016) Vol. 61, pp. 1-18
Closed Access | Times Cited: 72
A Survey of Deep Learning Techniques for Cybersecurity in Mobile Networks
Eva Rodríguez, Beatriz Otero, Norma Gutiérrez, et al.
IEEE Communications Surveys & Tutorials (2021) Vol. 23, Iss. 3, pp. 1920-1955
Open Access | Times Cited: 44
Deep Belief Networks-based framework for malware detection in Android systems
Dina Saif, Sherin M. El-Gokhy, Elsayed A. Sallam
Alexandria Engineering Journal (2018) Vol. 57, Iss. 4, pp. 4049-4057
Open Access | Times Cited: 46
SafeDroid: A Distributed Malware Detection Service for Android
Rohit Goyal, Angelo Spognardi, Nicola Dragoni, et al.
(2016), pp. 59-66
Open Access | Times Cited: 23
DroidDeep: using Deep Belief Network to characterize and detect android malware
Xin Su, Weiqi Shi, Xilong Qu, et al.
Soft Computing (2020) Vol. 24, Iss. 8, pp. 6017-6030
Closed Access | Times Cited: 23
Parallel‐CNN network for malware detection
Nazanin Bakhshinejad, Ali Hamzeh
IET Information Security (2019) Vol. 14, Iss. 2, pp. 210-219
Open Access | Times Cited: 19
Adaptive Android APKs Reverse Engineering for Features Processing in Machine Learning Malware Detection
Benjamin Aruwa Gyunka, Aro Taye Oladele, Ojeniyi Adegoke
International Journal on Data Science (2023) Vol. 4, Iss. 1, pp. 10-25
Open Access | Times Cited: 5
Android Malware Detection through Machine Learning Techniques: A Review
Oluwakemi Christiana Abikoye, Benjamin Aruwa Gyunka, Akande Noah Oluwatobi
International Journal of Online and Biomedical Engineering (iJOE) (2020) Vol. 16, Iss. 02, pp. 14-30
Open Access | Times Cited: 13
An app based on static analysis for android ransomware
Meet Kanwal, Sanjeev Thakur, Rishabh Lashkari
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2017), pp. 1-6
Closed Access | Times Cited: 10
AndroParse - An Android Feature Extraction Framework and Dataset
Robert H. Schmicker, Frank Breitinger, Ibrahim Baggili
Springer eBooks (2018), pp. 66-88
Closed Access | Times Cited: 10
Android Malware Detection: Building Useful Representations
Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, et al.
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2016), pp. 201-206
Open Access | Times Cited: 8
RealDroid: Large-Scale Evasive Malware Detection on "Real Devices"
Liu Lang, Yacong Gu, Qi Li, et al.
(2017), pp. 1-8
Closed Access | Times Cited: 5
An Assistive System for Android Malware Analysis to Increase Malware Analysis Efficiency
Suyash Jadhav, Tae Oh, Jaehoon Jeong, et al.
(2017), pp. 370-374
Closed Access | Times Cited: 2
Identification of Distributed Malware
Darshil Jain, Shreya Khemani, Durga Prasad
(2018), pp. 242-246
Closed Access | Times Cited: 2
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