TraVaG: Differentially Private Trace Variant Generation Using GANs. (arXiv:2303.16704v1 [cs.LG])

Process mining is rapidly growing in the industry. Consequently, privacy
concerns regarding sensitive and private information included in event data,
used by process mining algorithms, are becoming increasingly relevant.
State-of-the-art research mainly focuses on providing privacy guarantees, e.g.,
differential privacy, for trace variants that are used by the main process
mining techniques, e.g., process discovery. However, privacy preservation
techniques for releasing trace variants still do not fulfill all the
requirements of industry-scale usage. Moreover, providing privacy guarantees
when there exists …

algorithms art data differential privacy discovery event gans high industry information main mining preservation privacy private process process mining rate requirements research scale state techniques trace