Automatic annotation of confidential data in Java code

Conference paper

Bastys, I., Bolignano, P., Raimondi, F. and Schoepe, D. 2021. Automatic annotation of confidential data in Java code. Aïmeur, E., Laurent, M., Yaich, R., Dupont, B. and Garcia-Alfaro, J. (ed.) FPS 2021: The 14th International Symposium on Foundations & Practice of Security. Paris, France 08 - 12 Dec 2021 Springer. pp. 146-161 https://doi.org/10.1007/978-3-031-08147-7_10
TypeConference paper
TitleAutomatic annotation of confidential data in Java code
AuthorsBastys, I., Bolignano, P., Raimondi, F. and Schoepe, D.
Abstract

The problem of confidential information leak can be addressed by using automatic tools that take a set of annotated inputs
(the source) and track their flow to public sinks. Unfortunately, manually annotating the code with labels specifying the secret sources is one of the main obstacles in the adoption of such trackers.
In this work, we present an approach for the automatic generation of labels for confidential data in Java programs. Our solution is based on a graph-based representation of Java methods: starting from a minimal set of known API calls, it propagates the labels both intra- and inter-procedurally until a fix-point is reached. In our evaluation, we encode our synthesis and propagation algorithm in Datalog and assess the accuracy of our technique on seven previously annotated internal code bases, where we can reconstruct 75% of the pre-existing manual annotations. In addition to this single data point, we also perform an assessment using samples from the SecuriBench-micro benchmark, and we provide additional sample programs that demonstrate the capabilities and the limitations of our approach.

Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeSustainability
ConferenceFPS 2021: The 14th International Symposium on Foundations & Practice of Security
Page range146-161
Proceedings TitleFoundations and Practice of Security: 14th International Symposium, FPS 2021, Paris, France, December 7–10, 2021, Revised Selected Papers
SeriesLecture Notes in Computer Science
EditorsAïmeur, E., Laurent, M., Yaich, R., Dupont, B. and Garcia-Alfaro, J.
ISSN0302-9743
Electronic1611-3349
ISBN
Paperback9783031081460
Electronic9783031081477
PublisherSpringer
Publication dates
Online15 Jun 2022
Print16 Jun 2022
Publication process dates
Accepted08 Nov 2021
Deposited25 Jan 2022
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-08147-7_10. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-ma...

Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-08147-7_10
Web address (URL) of conference proceedingshttps://doi.org/10.1007/978-3-031-08147-7
LanguageEnglish
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