Authors:
Gamze Tillem
;
Zekeriya Erkin
and
Reginald L. Lagendijk
Affiliation:
Delft University of Technology, Netherlands
Keyword(s):
Software Privacy, Homomorphic Encryption, Applied Cryptography, Software Process Mining.
Related
Ontology
Subjects/Areas/Topics:
Applied Cryptography
;
Cryptographic Techniques and Key Management
;
Data and Application Security and Privacy
;
Data Engineering
;
Databases and Data Security
;
Information and Systems Security
;
Privacy
;
Privacy Enhancing Technologies
;
Secure Software Development Methodologies
;
Security in Information Systems
Abstract:
The growing complexity of software with respect to technological advances encourages model-based analysis
of software systems for validation and verification. Process mining is one recently investigated technique
for such analysis which enables the discovery of process models from event logs collected during software
execution. However, the usage of logs in process mining can be harmful to the privacy of data owners. While
for a software user the existence of sensitive information in logs can be a concern, for a software company,
the intellectual property of their product and confidential company information within logs can pose a threat
to company’s privacy. In this paper, we propose a privacy-preserving protocol for the discovery of process
models for software analysis that assures the privacy of users and companies. For this purpose, our proposal
uses encrypted logs and processes them using cryptographic protocols in a two-party setting. Furthermore, our
proposal applies data pack
ing on the cryptographic protocols to optimize computations by reducing the number
of repetitive operations. The experiments show that using data packing the performance of our protocol is
promising for privacy-preserving software analysis. To the best of our knowledge, our protocol is the first of
its kind for the software analysis which relies on processing of encrypted logs using process mining techniques.
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