Towards a Reliable and Automated Analysis of Compromised Systems

The vast majority of research in computer security is dedicated to the design of detection, protection, and prevention solutions. While these techniques play a critical role to increase the security and privacy of our digital infrastructure, it is enough to look at the news to understand that it is not a matter of "if" a computer system will be compromised, but only a matter of "when". It is a well known fact that there is no 100% secure system, and that there is no practical way to prevent attackers with enough resources from breaking into sensitive targets. Therefore, it is extremely important to develop automated techniques to timely and precisely analyze computer security incidents and compromised systems. Unfortunately, the area of incident response received very little research attention, and it is still largely considered an art more than a science because of its lack of a proper theoretical and scientific background. The objective of BITCRUMBS is to rethink the Incident Response (IR) field from its foundations by proposing a more scientific and comprehensive approach to the analysis of compromised systems. BITCRUMBS will achieve this goal in three steps:

  1. by introducing a new systematic approach to precisely measure the effectiveness and accuracy of IR techniques and their resilience to evasion and forgery;
  2. by designing and implementing new automated techniques to cope with advanced threats and the analysis of IoT devices;
  3. by proposing a novel forensics-by-design development methodology and a set of guidelines for the design of future systems and software.
To provide the right context for these new techniques and show the impact of the project in different fields and scenarios, BITCRUMBS plans to address its objectives using real case studies borrowed from two different domains: traditional computer software, and embedded systems.

Bitcrumbs is a project funded by a European Research Council (ERC) consolidator grant.

The project started in mid-2018 and will run until 2023.


The Tangled Genealogy of IoT Malware
Emanuele Cozzi, Pierre-Antoine Vervier, Matteo Dell'Amico, Yun Shen, Leyla Bilge, Davide Balzarotti
Annual Computer Security Applications Conference (ACSAC) 2020
PDF Bibtex
Prevalence and Impact of Low-Entropy Packing Schemes in the Malware Ecosystem
Alessandro Mantovani, Simone Aonzo, Xabier Ugarte-Pedrero, Alessio Merlo, Davide Balzarotti
Network and Distributed System Security (NDSS) Symposium , 2020
PDF Bibtex
Artifacts: Dataset, Code
When malware is packin' heat; limits of machine learning classifiers based on static analysis features
Hojjat Aghakhani, Fabio Gritti, Francesco Mecca, Martina Lindorfer, Stefano Ortolani, Davide Balzarotti, Giovanni Vigna, Christopher Kruegel
Network and Distributed System Security (NDSS) Symposium, 2020
PDF Bibtex
Artifacts: Dataset
SoK: Cyber Insurance - Technical Challenges and a System Security Roadmap
Savino Dambra, Leyla Bilge, Davide Balzarotti
IEEE Symposium on Security & Privacy, San Francisco, CA 2020
PDF Bibtex
Back to the Whiteboard: a Principled Approach for the Assessment and Design of Memory Forensic Techniques
Fabio Pagani, Davide Balzarotti
28th USENIX Security Symposium (USENIX Security 19) , Santa Clara, CA (acceptance rate: 15.7%)
PDF Slides Bibtex
Artifacts: Code
A Close Look at a Daily Dataset of Malware Samples
Xabier Ugarte-Pedrero, Mariano Graziano, Davide Balzarotti
ACM Transactions on Privacy and Security (TOPS)
PDF Bibtex
Artifacts: not available as the experiments were performed by CISCO employees by using internal data and tools
Introducing the Temporal Dimension to Memory Forensics
Pagani, Fabio, Fedorov, Oleksii, Balzarotti, Davide
ACM Transactions on Privacy and Security (TOPS)
PDF Bibtex
Artifacts: Code, Memory Images
Understanding Linux Malware
Emanuele Cozzi, Mariano Graziano, Yanick Fratantonio, Davide Balzarotti
IEEE Symposium on Security & Privacy , San Francisco, CA (acceptance rate: 11.5%)
PDF Slides Bibtex
Artifacts: Free Service, List of Samples