  We propose PRISM to enable users of machine translation systems to preserve
the privacy of data on their own initiative. There is a growing demand to apply
machine translation systems to data that require privacy protection. While
several machine translation engines claim to prioritize privacy, the extent and
specifics of such protection are largely ambiguous. First, there is often a
lack of clarity on how and to what degree the data is protected. Even if
service providers believe they have sufficient safeguards in place,
sophisticated adversaries might still extract sensitive information. Second,
vulnerabilities may exist outside of these protective measures, such as within
communication channels, potentially leading to data leakage. As a result, users
are hesitant to utilize machine translation engines for data demanding high
levels of privacy protection, thereby missing out on their benefits. PRISM
resolves this problem. Instead of relying on the translation service to keep
data safe, PRISM provides the means to protect data on the user's side. This
approach ensures that even machine translation engines with inadequate privacy
measures can be used securely. For platforms already equipped with privacy
safeguards, PRISM acts as an additional protection layer, reinforcing their
security furthermore. PRISM adds these privacy features without significantly
compromising translation accuracy. Our experiments demonstrate the
effectiveness of PRISM using real-world translators, T5 and ChatGPT
(GPT-3.5-turbo), and the datasets with two languages. PRISM effectively
balances privacy protection with translation accuracy.
