Redefining Malware Sandboxing: Enhancing Analysis Through Sysmon and ELK Integration

Autor: Rasmi-Vlad Mahmoud, Marios Anagnostopoulos, Sergio Pastrana, Jens Myrup Pedersen

Publikováno v: IEEE Access, Vol 12, Pp 68624-68636 (2024)

In cybersecurity, adversaries employ a myriad of tactics to evade detection and breach defenses. Malware remains a formidable weapon in their arsenal. To counter this threat, researchers unceasingly pursue dynamic analysis, which aims to comprehend a

Externí odkaz: https://doaj.org/article/a4db618c9e484201b6ced964884ea098

Towards realistic privacy-preserving deep learning over encrypted medical data

Autor: José Cabrero-Holgueras, Sergio Pastrana

Publikováno v: Frontiers in Cardiovascular Medicine, Vol 10 (2023)

Cardiovascular disease supposes a substantial fraction of healthcare systems. The invisible nature of these pathologies demands solutions that enable remote monitoring and tracking. Deep Learning (DL) has arisen as a solution in many fields, and in h

Externí odkaz: https://doaj.org/article/b0d8bd43c77a46e789d4bc56f692be76

Automatically identifying the function and intent of posts in underground forums

Autor: Andrew Caines, Sergio Pastrana, Alice Hutchings, Paula J. Buttery

Publikováno v: Crime Science, Vol 7, Iss 1, Pp 1-14 (2018)

Abstract The automatic classification of posts from hacking-related online forums is of potential value for the understanding of user behaviour in social networks relating to cybercrime. We designed annotation schema to label forum posts for three pr

Externí odkaz: https://doaj.org/article/365f9d4aea90451ca4b94aff5dfe8309

Towards Improving Code Stylometry Analysis in Underground Forums

Autor: Jorge Blasco, Michal Tereszkowski-Kaminski, Guillermo Suarez-Tangil, Sergio Pastrana

Publikováno v: Proceedings on Privacy Enhancing Technologies, Vol 2022, Iss 1, Pp 126-147 (2022)
King's College London
IMDEA Networks Institute Digital Repository
instname

Code Stylometry has emerged as a powerful mechanism to identify programmers. While there have been significant advances in the field, existing mechanisms underperform in challenging domains. One such domain is studying the provenance of code shared i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae315cdb0bcb91118dacb8031347036e
https://doaj.org/article/0f09d9231f5b412abab528bb2857f5c3

SoK: Privacy-Preserving Computation Techniques for Deep Learning

Autor: Sergio Pastrana, José Cabrero-Holgueras

Publikováno v: Proceedings on Privacy Enhancing Technologies, Vol 2021, Iss 4, Pp 139-162 (2021)

Deep Learning (DL) is a powerful solution for complex problems in many disciplines such as finance, medical research, or social sciences. Due to the high computational cost of DL algorithms, data scientists often rely upon Machine Learning as a Servi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::949b48957bdb6aa3f07557012e7b680b
https://doi.org/10.2478/popets-2021-0064