Use Fewer Instances of the Letter “i”: Toward Writing Style Anonymization

Abstract

Abstract. This paper presents Anonymouth, a novel framework for anonymizing writing style. Without accounting for style, anonymous authors risk identification. This framework is necessary to provide a tool for testing the consistency of anonymized writing style and a mechanism for adaptive attacks against stylometry techniques. Our framework defines the steps necessary to anonymize documents and implements them. A key contribution of this work is this framework, including novel methods for identifying which features of documents need to change and how they must be changed to accomplish document anonymization. In our experiment, 80% of the user study participants were able to anonymize their documents in terms of a fixed corpus and limited feature set used. However, modifying pre-written documents were found to be difficult and the anonymization did not hold up to more extensive feature sets. It is important to note that Anonymouth is only the first step toward a tool to acheive stylometric anonymity with respect to state-of-the-art authorship attribution techniques. The topic needs further exploration in order to accomplish significant anonymity.

Translate Once, Translate Twice, Translate Thrice and Attribute: Identifying Authors and Machine Translation Tools in Translated Text

“…We experimented using a variety of features to identify the features leading to highest accuracy as measured by the true-positive rate. We utilized two authorship attribution tools, (1) JGAAP 4 developed by Juola et al [10] and (2) JStylo, a novel framework for authorship attribution that was developed by McDonald et al [11]. JGAAP is limited to analysis using one feature at a time.…”

Generalised Differential Privacy for Text Document Processing

“…An early work in this area by Kacmarcik et al [22] applies obfuscation by modifying the most important stylometric features of the text to reduce the effectiveness of author attribution. This approach was used in Anonymouth [35], a semi-automated tool that provides feedback to authors on which features to modify to effectively anonymise their texts. A similar approach was also followed by Karadhov et al [23] as part of the PAN@Clef 2017 task.…”

Active Authentication on Mobile Devices via Stylometry, Application Usage, Web Browsing, and GPS Location

“…See [14] for a thorough summary of stylometric studies in each of these three problem domains along with their study parameters and the resulting accuracy. These studies traditionally use large sets of features (see Table II in [15]) in combination with support vector machines (SVMs) that have proven to be effective in high dimensional feature space [16], even in cases when the number of features exceeds the number of samples. Nevertheless, with these approaches, often more than 500 words are required in order to achieve adequately low error rates [17].…”