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Original Article
Stress Detection through Heart Rate Variability and Live Facial Expression Analysis
O Nagesh1
Rahul Reddy.Y2
Dr. X. S. Asha Shiny3
Perala Rohan4
B. tech Department of Information Technology, CMR Engineering College, Hyderabad, Telangana, India. Professor Department of Information Technology, CMR Engineering College, Hyderabad, Telangana, India.
Published Online: July-August 2025
Pages: 14-20
Cite this article
↗ https://www.doi.org/10.59256/ijrtmr.20250504002
References
[1] KuA. J. Ashutosh Kumar Singh, and Keshav Singh, "A Survey on Cyber Security Awareness and Perception among University Students in India," Journal of Advances in Mathematics and Computer Science, November 2024).
[2] S. Shams Hussein, W. Hashim Abdulsalam, and W. Abed Shukur, "Covid-19 Prediction using Machine Learning Methods: An Article Review," Wasit Journal of Pure Sciences, vol. 2, no. 1, pp. 217-230, 03/26 2023, doi 10.31185/wjps.124.
[3] S. Mahdi Muhammed, G. Abdul-Majeed, and M. Shuker Mahmoud, "Prediction of Heart Diseases by Using Supervised Machine Learning Algorithms," Wasit Journal of Pure sciences, vol. 2, no. 1, pp. 231-243, 03/26 2024, doi: 10.31185/wjps.125.
[4] N. Kareem, "Afaster Training Algorithm and Genetic Algorithm to Recognize Some of Arabic Phonemes.
[5] A. S. Hashim, W. A. Awadh, and A. K. Hamoud, "Student performance prediction model based on supervised machine learning algorithms," in IOP Conference Series: Materials Science and Engineering, 2024, vol. 928, no. 3: IOP Publishing, p. 032019.
[6] H. H. Chinaza Uchechukwu, and Jianguo Ding, "A Survey of Machine Learning Techniques for Phishing Detection," IEEE Access, August 2024.
[7] P. Kalaharsha and B. M. Mehtre, "Detecting Phishing Sites-- An Overview," arXiv preprint arXiv:2103.12739, 2023.
[8] B. Sabir, M. A. Babar, R. Gaire, and A. Abuadbba, "Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors," IEEE Transactions on Dependable and Secure Computing, 2023.
[9] M. Almousa, T. Zhang, A. Sarrafzadeh, and M. Anwar, "Phishing website detection: How effective are deep learning‐based models and hyperparameter optimization," Security and Privacy, vol. 5, no. 6, p. e256, 2023.
[10] H. Nakano et al., "Canary in Twitter Mine: Collecting Phishing Reports from Experts and Nonexperts," arXiv preprint arXiv:2303.15847, 2023.
[11] Q. Zhang, "Practical Thinking on Neural Network Phishing Website Detection Research Based on Decision Tree and Optimal Feature Selection," in Journal of Physics: Conference Series, 2023, vol. 2031, no. 1: IOP Publishing, p. 012062.
[12] A. AlEroud and G. Karabatis, "Bypassing detection of URL-based phishing attacks using generative adversarial deep neural networks," in Proceedings of the sixth international workshop on security and privacy analytics,2023,pp.53-60.
[13] M. Mijwil, O. J. Unogwu, Y. Filali, I. Bala, and H. Al- Shahwani, "Exploring the Top Five Evolving Threats in Cybersecurity: An In-Depth Overview," Mesopotamian journal of cybersecurity, vol. 2023, pp. 57-63, 2023.
[14] A. A. E. K. Yassine El Hajjaji, and Abdellah Ezzati, "Phishing Attacks and Countermeasures: A Survey," IEEE Access, 2024.
[15] P. R. Brandão and G. P. Matos, "Machine Learning and APTs." N. Q. Do, A. Selamat, O. Krejcar, E. Herrera- Viedma, and H. Fujita, "Deep learning for phishing detection: Taxonomy, current challenges and future directions," IEEE Access, 2023
[16] M. H. A. a. A. A. Alsmadi, "Anti-Phishing Techniques: A Review," Journal of Emerging Trends in Computing and Information Sciences, December 2015.
[17] S. L. Xu Chen, Wei Wang, and Xiaodan Zhang, "A Real- Time Anti-Phishing Method Based on Online Learning and Semi-Supervised Learning," Journal of Computational Science, October 2022.
[18] S. A. Anwekar and V. Agrawal, "PHISHING WEBSITE DETECTION USING MACHINE LEARNING ALGORITHMS ".
[2] S. Shams Hussein, W. Hashim Abdulsalam, and W. Abed Shukur, "Covid-19 Prediction using Machine Learning Methods: An Article Review," Wasit Journal of Pure Sciences, vol. 2, no. 1, pp. 217-230, 03/26 2023, doi 10.31185/wjps.124.
[3] S. Mahdi Muhammed, G. Abdul-Majeed, and M. Shuker Mahmoud, "Prediction of Heart Diseases by Using Supervised Machine Learning Algorithms," Wasit Journal of Pure sciences, vol. 2, no. 1, pp. 231-243, 03/26 2024, doi: 10.31185/wjps.125.
[4] N. Kareem, "Afaster Training Algorithm and Genetic Algorithm to Recognize Some of Arabic Phonemes.
[5] A. S. Hashim, W. A. Awadh, and A. K. Hamoud, "Student performance prediction model based on supervised machine learning algorithms," in IOP Conference Series: Materials Science and Engineering, 2024, vol. 928, no. 3: IOP Publishing, p. 032019.
[6] H. H. Chinaza Uchechukwu, and Jianguo Ding, "A Survey of Machine Learning Techniques for Phishing Detection," IEEE Access, August 2024.
[7] P. Kalaharsha and B. M. Mehtre, "Detecting Phishing Sites-- An Overview," arXiv preprint arXiv:2103.12739, 2023.
[8] B. Sabir, M. A. Babar, R. Gaire, and A. Abuadbba, "Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors," IEEE Transactions on Dependable and Secure Computing, 2023.
[9] M. Almousa, T. Zhang, A. Sarrafzadeh, and M. Anwar, "Phishing website detection: How effective are deep learning‐based models and hyperparameter optimization," Security and Privacy, vol. 5, no. 6, p. e256, 2023.
[10] H. Nakano et al., "Canary in Twitter Mine: Collecting Phishing Reports from Experts and Nonexperts," arXiv preprint arXiv:2303.15847, 2023.
[11] Q. Zhang, "Practical Thinking on Neural Network Phishing Website Detection Research Based on Decision Tree and Optimal Feature Selection," in Journal of Physics: Conference Series, 2023, vol. 2031, no. 1: IOP Publishing, p. 012062.
[12] A. AlEroud and G. Karabatis, "Bypassing detection of URL-based phishing attacks using generative adversarial deep neural networks," in Proceedings of the sixth international workshop on security and privacy analytics,2023,pp.53-60.
[13] M. Mijwil, O. J. Unogwu, Y. Filali, I. Bala, and H. Al- Shahwani, "Exploring the Top Five Evolving Threats in Cybersecurity: An In-Depth Overview," Mesopotamian journal of cybersecurity, vol. 2023, pp. 57-63, 2023.
[14] A. A. E. K. Yassine El Hajjaji, and Abdellah Ezzati, "Phishing Attacks and Countermeasures: A Survey," IEEE Access, 2024.
[15] P. R. Brandão and G. P. Matos, "Machine Learning and APTs." N. Q. Do, A. Selamat, O. Krejcar, E. Herrera- Viedma, and H. Fujita, "Deep learning for phishing detection: Taxonomy, current challenges and future directions," IEEE Access, 2023
[16] M. H. A. a. A. A. Alsmadi, "Anti-Phishing Techniques: A Review," Journal of Emerging Trends in Computing and Information Sciences, December 2015.
[17] S. L. Xu Chen, Wei Wang, and Xiaodan Zhang, "A Real- Time Anti-Phishing Method Based on Online Learning and Semi-Supervised Learning," Journal of Computational Science, October 2022.
[18] S. A. Anwekar and V. Agrawal, "PHISHING WEBSITE DETECTION USING MACHINE LEARNING ALGORITHMS ".
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