Técnicas y Herramientas de Análisis Forense en Redes para la Detección y Mitigación de Ataques
DOI:
https://doi.org/10.64973/gzp33g02Palabras clave:
Análisis forense, redes, ciberseguridad, evidencia digital, herramientasResumen
El análisis forense de redes se ha vuelto una pieza importante para investigar incidentes de ciberseguridad y recopilar evidencia digital en entornos que cada vez son más complejos. En este trabajo se revisaron 22 estudios científicos recientes con el fin de conocer las principales herramientas, métodos y desafíos presentes en esta área, considerando escenarios como IoT, la computación en la nube, las redes SDN y las tecnologías 6G. Los resultados muestran que herramientas conocidas como Wireshark y Autopsy todavía se siguen utilizando bastante, aunque poco a poco están siendo acompañadas por otras que usan aprendizaje automático para ayudar en el análisis. Sin embargo, todavía hay varios problemas por resolver, como el hecho de que no todas las herramientas funcionan bien entre sí, la dificultad para conservar correctamente la evidencia digital y la falta de reglas legales claras que sean comunes para todos los casos. En general, los resultados indican que es necesario seguir mejorando el uso de estas tecnologías en situaciones reales, teniendo en cuenta no solo lo técnico, sino también el trabajo humano y el marco legal que las rodea.
Referencias
Abd Elmonsef Sarhan, S., Youness, H. A., & Bahaa-Eldin, A. M. (2023). A framework for digital forensics of encrypted real-time network traffic, instant messaging, and VoIP application case study. Ain Shams Engineering Journal, 14(9), 102069. https://doi.org/10.1016/j.asej.2022.102069
Abuowaida, S., Owida, H. A., Mohammad, S. I. S., Alshdaifat, N., Elsoud, E. A., Alazaidah, R., Vasudevan, A., & Alshurideh, M. T. (2025). Evidence Detection in Cloud Forensics: Classifying Cyber-Attacks in IaaS Environments using machine learning. Data and Metadata, 4, 699–699. https://doi.org/10.56294/dm2025699
Akinbi, A. O. (2023). Digital forensics challenges and readiness for 6G Internet of Things (IoT) networks. WIREs Forensic Science, 5(6), e1496. https://doi.org/10.1002/wfs2.1496
Alqabbani, A., Saleem, K., & Almazyad, A. S. (2023). Digital Communication Forensics in 6G and beyond Networks. Applied Sciences, 13(19), 10861. https://doi.org/10.3390/app131910861
Alzakari, S. A., Aljebreen, M., Ahmad, N., Alhashmi, A. A., Alahmari, S., Alrusaini, O., Al-Sharafi, A. M., & Almukadi, W. S. (2025). An intelligent ransomware based cyberthreat detection model using multi head attention-based recurrent neural networks with optimization algorithm in IoT environment. Scientific Reports, 15(1), 8259. https://doi.org/10.1038/s41598-025-92711-4
Çi̇L, A., & DEMİRCİ, M. (2024). A comparative analysis of software-defined network controllers in terms of network forensics processes and capabilities. Sigma Journal of Engineering and Natural Sciences – Sigma Mühendislik ve Fen Bilimleri Dergisi, 42(2), 425–437. https://doi.org/10.14744/sigma.2022.00107
Dunsin, D., Ghanem, M. C., Ouazzane, K., & Vassilev, V. (2024). A comprehensive analysis of the role of artificial intelligence and machine learning in modern digital forensics and incident response. Forensic Science International: Digital Investigation, 48, 301675. https://doi.org/10.1016/j.fsidi.2023.301675
Egger, M., Urbanke, R. L., & Bitar, R. (2025). Federated One-Shot Learning With Data Privacy and Objective-Hiding. IEEE Transactions on Information Forensics and Security, 20, 5166–5180. https://doi.org/10.1109/TIFS.2025.3570132
Fakiha, B. (2024). Investigating the Secrets, New Challenges, and Best Forensic Methods for Securing Critical Infrastructure Networks. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 15(1), 104–114. https://doi.org/10.58346/JOWUA.2024.I1.008
Ghabban, F. M., Alfadli, I. M., Ameerbakhsh, O., AbuAli, A. N., Al-Dhaqm, A., & Al-Khasawneh, M. A. (2021). Comparative Analysis of Network Forensic Tools and Network Forensics Processes. 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), 78–83. https://doi.org/10.1109/ICSCEE50312.2021.9498226
González Arias, R., Bermejo Higuera, J., Rainer Granados, J. J., Bermejo Higuera, J. R., & Sicilia Montalvo, J. A. (2024). Systematic Review: Anti-Forensic Computer Techniques. Applied Sciences, 14(12), 5302. https://doi.org/10.3390/app14125302
Jarrett, A., & Choo, K.-K. R. (2021). The impact of automation and artificial intelligence on digital forensics. WIREs Forensic Science, 3(6), e1418. https://doi.org/10.1002/wfs2.1418
Jiménez, M. B., Fernández, D., Eduardo Rivadeneira, J., & Flores-Moyano, R. (2024). A Filtering Model for Evidence Gathering in an SDN-Oriented Digital Forensic and Incident Response Context. IEEE Access, 12, 75792–75808. https://doi.org/10.1109/ACCESS.2024.3405588
Menahil, A., Iqbal, W., Iftikhar, M., Shahid, W. B., Mansoor, K., & Rubab, S. (2021). Forensic Analysis of Social Networking Applications on an Android Smartphone. Wireless Communications and Mobile Computing, 2021(1), 5567592. https://doi.org/10.1155/2021/5567592
Nayak, S. C., Tiwari, V., & Samanthula, B. K. (2023). Review of Ransomware Attacks and a Data Recovery Framework using Autopsy Digital Forensics Platform. 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), 0605–0611. https://doi.org/10.1109/CCWC57344.2023.10099169
Qureshi, S., Tunio, S., Akhtar, F., Wajahat, A., Nazir, A., & Ullah, F. (2021). Network Forensics: A Comprehensive Review of Tools and Techniques. International Journal of Advanced Computer Science and Applications (IJACSA), 12(5). https://doi.org/10.14569/IJACSA.2021.01205103
Ragab, M., Ashary, E. B., Alghamdi, B. M., Aboalela, R., Alsaadi, N., Maghrabi, L. A., & Allehaibi, K. H. (2025). Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities. Scientific Reports, 15(1), 4470. https://doi.org/10.1038/s41598-025-88843-2
Soni, N. (2024). IoT forensics: Challenges, methodologies, and future directions in securing the Internet of Things ecosystem. Computer and Telecommunication Engineering, 2(4), 3070. https://doi.org/10.54517/cte3070
Waseem, Q., Alshamrani, S. S., Nisar, K., Wan Din, W. I. S., & Alghamdi, A. S. (2021). Future Technology: Software-Defined Network (SDN) Forensic. Symmetry, 13(5), 767. https://doi.org/10.3390/sym13050767
Yaacoub, J.-P. A., Noura, H. N., Salman, O., & Chehab, A. (2022). Advanced digital forensics and anti-digital forensics for IoT systems: Techniques, limitations and recommendations. Internet of Things, 19, 100544. https://doi.org/10.1016/j.iot.2022.100544
Zareen, M. S., Aslam, B., Tahir, S., Rasheed, I., & Khan, F. (2024). Unveiling the Dynamic Landscape of Digital Forensics: The Endless Pursuit. Computers, 13(12), 333. https://doi.org/10.3390/computers13120333
Zhang, H. (2024). Simulation of network forensics model based on wireless sensor networks and inference technology. Measurement: Sensors, 34, 101261. https://doi.org/10.1016/j.measen.2024.101261
Descargas
Publicado
Número
Sección
Licencia
Derechos de autor 2026 EDULEARN Revista Multidisciplinar
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
