Back to results
Massachusetts Institute of Technology
Graph Metrics for Improving Cybersecurity on Software Dependency Networks
Abstract
dc:description.abstractModern software ecosystems are deeply interconnected, allowing a vulnerability in a single component to propagate and affect many others. In this thesis, we model software ecosystems as directed graphs, and apply various graph-theoretic metrics to quantify security risk. We compare two deep learning frameworks (PyTorch and TensorFlow) with two traditional software frameworks (npm and PyPI), identifying critical properties of their dependency structures, which motivates several recommendations for improving software supply chain security.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Yao, Darren Z.
- Advisors dc:contributor.advisor
-
- Pal, Ranjan
- Siegel, Michael D.
Rights
dc:rights- Statement dc:rights
-
- In Copyright - Educational Use Permitted
- Copyright retained by author(s)
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/162980
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/162980