Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection
The rise in mobile malware risks brought on by the explosion of Android smartphones required more efficient detection techniques. Inspired by a cascade of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, optimized using the Earthworm Optimization Algorithm (EOA), this study pre...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-12-01
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| Series: | Cyber Security and Applications |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772918424000493 |
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| author | Brij B. Gupta Akshat Gaurav Varsha Arya Shavi Bansal Razaz Waheeb Attar Ahmed Alhomoud Konstantinos Psannis |
| author_facet | Brij B. Gupta Akshat Gaurav Varsha Arya Shavi Bansal Razaz Waheeb Attar Ahmed Alhomoud Konstantinos Psannis |
| author_sort | Brij B. Gupta |
| collection | DOAJ |
| description | The rise in mobile malware risks brought on by the explosion of Android smartphones required more efficient detection techniques. Inspired by a cascade of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, optimized using the Earthworm Optimization Algorithm (EOA), this study presents an android malware detection model. The paper used random forest model for feature selection. With a 99% accuracy and the lowest loss values, the proposed model performs better than conventional models including GRU, LSTM, RNN, Logistic Regression, and SVM.. The findings highlight the possibility of proposed method in improving Android malware detection, thereby providing a strong answer in the changing scene of cybersecurity. |
| format | Article |
| id | doaj-art-7b3fade6da004c6fa04b57910c44643f |
| institution | Kabale University |
| issn | 2772-9184 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Cyber Security and Applications |
| spelling | doaj-art-7b3fade6da004c6fa04b57910c44643f2025-01-08T04:53:52ZengKeAi Communications Co., Ltd.Cyber Security and Applications2772-91842025-12-013100083Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detectionBrij B. Gupta0Akshat Gaurav1Varsha Arya2Shavi Bansal3Razaz Waheeb Attar4Ahmed Alhomoud5Konstantinos Psannis6Department of Computer Science and Information Engineering, Asia University, Taichung 413, Taiwan, China; School of Cybersecurity, Korea University, Seoul, South Korea; Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India; University of Economics and Human Science, Warsaw, PolandDepartment of Computer Science and Information Engineering, Asia University, Taichung 413, Taiwan, China; Ronin Institute, Montclair, NJ, USA; Corresponding author.Hong Kong Metropolitan University (HKMU), Hong Kong, China; Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, IndiaInsights2Techinfo, India; UCRD, Chandigarh University, Chandigarh, IndiaManagement Department, College of Business Administration, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaDepartment of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Rafha 91911, Saudi ArabiaUniversity of Macedonia, GreeceThe rise in mobile malware risks brought on by the explosion of Android smartphones required more efficient detection techniques. Inspired by a cascade of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, optimized using the Earthworm Optimization Algorithm (EOA), this study presents an android malware detection model. The paper used random forest model for feature selection. With a 99% accuracy and the lowest loss values, the proposed model performs better than conventional models including GRU, LSTM, RNN, Logistic Regression, and SVM.. The findings highlight the possibility of proposed method in improving Android malware detection, thereby providing a strong answer in the changing scene of cybersecurity.http://www.sciencedirect.com/science/article/pii/S2772918424000493Malware detectionLSTMGRUEarthworm optimization algorithmAndroid |
| spellingShingle | Brij B. Gupta Akshat Gaurav Varsha Arya Shavi Bansal Razaz Waheeb Attar Ahmed Alhomoud Konstantinos Psannis Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection Cyber Security and Applications Malware detection LSTM GRU Earthworm optimization algorithm Android |
| title | Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection |
| title_full | Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection |
| title_fullStr | Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection |
| title_full_unstemmed | Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection |
| title_short | Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection |
| title_sort | earthworm optimization algorithm based cascade lstm gru model for android malware detection |
| topic | Malware detection LSTM GRU Earthworm optimization algorithm Android |
| url | http://www.sciencedirect.com/science/article/pii/S2772918424000493 |
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