International Journal

• Park, H., Cho, G., & Kim, T. G. (2026). Wireless signal fingerprinting framework based on emphasized spectral features for IoT device authentication. Mathematics, 14(13), 2321. (SCIE)

• Kim, T. G., Park, H., You, I., & Kwak, B. I. (2026). XGBoost-based anomaly detection framework for SOME/IP in in-vehicle networks. Systems, 14(2), 196. (SCIE)

• Choi, D. S., Kim, T., Kang, B., & Im, E. G. (2025). Image-based malicious network traffic detection framework: Data-centric approach. Applied Sciences, 15(12). (SCIE)

• Park, H., Astillo, P. V., Kim, T., & You, I. (2025). 5G native network function for false base station detection using machine learning technique. Information Systems Frontiers, 1–16. (SCIE)

• Ko, S. M., Yang, J., Kim, T., & You, I. (2025). N-gram opcode frequency-based malware detection using CNN algorithm. Soft Computing, 1–9. (SCIE)

• An, B., Yang, J., Kim, S., & Kim, T. (2024). Malware detection using dual Siamese network model. CMES—Computer Modeling in Engineering & Sciences, 141(1). (SCIE)

• Park, H., Kim, T., Duguma, D. G., Kim, J., You, I., & Susilo, W. (2023). An enhanced group key-based security protocol to protect 5G SON against FBS. Computer Systems Science & Engineering, 45(2). (SCIE)

• Kim, T., Kim, J., & You, I. (2023). An anomaly detection method based on multiple LSTM-autoencoder models for in-vehicle network. Electronics, 12(17), 3543. (SCIE)

• Park, H., Kim, S., Ko, S. M., & Kim, T. (2023). CNN-based RF fingerprinting method for securing passive keyless entry and start system. Computers, Materials & Continua, 76(2). (SCIE)

• Kim, T. (2023). Deception-based method for ransomware detection. Journal of Internet Services and Information Security, 13(3), 191–201. (SCOPUS)

• Park, H., Astillo, P. V. B., Ko, Y., Park, Y., Kim, T., & You, I. (2023). SMDFbs: Specification-based misbehavior detection for false base stations. Sensors, 23(23), 9504. (SCIE)

• Park, H., & Kim, T. (2022). User authentication method via speaker recognition and speech synthesis detection. Security and Communication Networks, 2022, 1–10.

• Kim, Y. N., Ko, S. M., & Kim, T. (2022). Hidden Markov model-based anomaly detection method for in-vehicle network. Journal of Internet Services and Information Security, 12(2), 115–125. (SCOPUS)

• Kim, T., Lee, Y. R., Kang, B., & Im, E. G. (2019). Binary executable file similarity calculation using function matching. The Journal of Supercomputing, 75, 607–622. (SCIE)

• Kim, T., Kang, B., & Im, E. G. (2018). Runtime detection framework for Android malware. Mobile Information Systems, 2018. (SCIE)

• Kim, T., Kang, B., Rho, M., Sezer, S., & Im, E. G. (2019). A multimodal deep learning method for Android malware detection using various features. IEEE Transactions on Information Forensics and Security, 14(3), 773–788. (SCIE)

• Cho, I. K., Kim, T., Shim, Y. J., Ryu, M., & Im, E. G. (2016). Malware analysis and classification using sequence alignments. Intelligent Automation & Soft Computing, 22(3), 371–377. (SCIE)

• Kang, B., Kim, T., Kim, J., & Im, E. G. (2016). A dynamic taint analysis method of control-dependent data. Information, 19(11A), 5245.

• Cho, I. K., Kim, T., Shim, Y. J., Park, H., Choi, B., & Im, E. G. (2014). Malware similarity analysis using API sequence alignments. Journal of Internet Services and Information Security, 4(4), 103–114.

• Kang, B., Kim, H. S., Kim, T., Kwon, H., & Im, E. G. (2012). Fast malware classification using counting Bloom filter. Information, 15(7), 2879.

Domestic Journal

• Kim, T. G., Ji, H., & Im, E. (2018). Malware classification using machine learning and binary visualization. KIISE Transactions on Computing Practices, 24(4), 198–203.
​
• Park, J. B., Han, K. S., Kim, T. G., & Im, E. G. (2015). A study on selecting key opcodes for malware classification and its usefulness. Journal of KIISE, 42(5), 558–565.
​
• Kim, T. G., & Im, E. G. (2014). Analysis method reuse code to detect variants of malware. Journal of the Korea Institute of Information Security & Cryptology, 24(1), 32–38.
​
• Kim, T. G., Kim, I.-K., & Im, E. G. (2012). Malware detection method via major block comparison. Journal of Security Engineering, 9(5), 401–416.
​
• Kang, B., Kim, H. S., Kim, T. G., Kwon, H., & Im, E. G. (2011). Fast malware family detection method using control flow graphs. In Proceedings of the 2011 ACM Symposium on Research in Applied Computation (pp. 287–292).

International Conference

• Jung, B., Kim, T. G., & Im, E. G. (2018). Malware classification using byte sequence information. In Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems (pp. 143–148).
​
• Li, Q., Wang, L., Kim, T. G., & Im, E. G. (2016). Mobile-based continuous user authentication system for cloud security. In 2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) (pp. 176–179). IEEE.
​
• Park, J., Kim, T. G., & Im, E. G. (2016). Touch gesture data based authentication method for smartphone users. In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (pp. 136–141).
​
• Lee, T. K., Kim, T. G., & Im, E. G. (2016). User authentication method using shaking actions in mobile devices. In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (pp. 142–147).
​
• Kim, J., Kim, T. G., & Im, E. G. (2015). Structural information based malicious app similarity calculation and clustering. In Proceedings of the 2015 Conference on Research in Adaptive and Convergent Systems (pp. 314–318).
​
• Shim, Y. J., Kim, T. G., & Im, E. G. (2015). A study on similarity calculation method for API invocation sequences. In International Conference on Rough Sets and Knowledge Technology (pp. 492–501). Springer.
​
• Kim, T. G., Park, J. B., Cho, I. G., Kang, B., Im, E. G., & Kang, S. (2014). Similarity calculation method for user-define functions to detect malware variants. In Proceedings of the 2014 Conference on Research in Adaptive and Convergent Systems (pp. 236–241).
​
• Kim, J., Kim, T. G., & Im, E. G. (2014). Survey of dynamic taint analysis. In 2014 4th IEEE International Conference on Network Infrastructure and Digital Content (pp. 269–272). IEEE.
​
• Kang, B., Kim, T. G., Kang, B., Im, E. G., & Ryu, M. (2014). TASEL: Dynamic taint analysis with selective control dependency. In Proceedings of the 2014 Conference on Research in Adaptive and Convergent Systems (pp. 272–277).
​
• Kim, S., Kim, T. G., & Im, E. G. (2013). Real-time malware detection framework in intrusion detection systems. In Proceedings of the 2013 Conference on Research in Adaptive and Convergent Systems (pp. 351–352).
​

Domestic Conference

• Seong, M.-J., & Kim, T. G. (2014). Network traffic analysis of Android malware. In Proceedings of the Korea Contents Association Conference (pp. 475–476).

• Kim, T. G., & Im, E. G. (2012). User-defined function inference method for malware detection. In Proceedings of the KICS (pp. 776–777).

• Kim, T. G., & Im, E. G. (2012). Malware detection method via string comparison. In Proceedings of the KICS (pp. 493–494).

• Kang, B., Kim, T. G., & Im, E. G. (2012). Instruction set malware classification using counting Bloom filter. In Proceedings of the KICS (pp. 350–351).

• Kim, T. G., & Im, E. G. (2011). An analysis on behavioral API for accurate malware detection. In Proceedings of the KICS (pp. 663–664).