I'm starting to do research in machine learning on sensitive datasets, which sometimes seems like a double-edged sword. For instance, some projects involve showing how a company/organization/government can infer sensitive information about you and abuse it. I feel that this has to be published as it may already be abused somewhere or will be soon. At the same time, if I publish too many details then some corporations etc. may find it easy to implement and start abusing.
Do some conferences/journals accept papers that have scarce details on some parts of the modeling such that it may hinder abuse? It should be noted that while the code may be sent to the reviewers for a check, the data is sometimes of a sensitive nature such that it cannot be handed over.