In the current digital era, we continuously create records of our activities, that are accumulated in a variety of data-storages. One common way to protect our privacy is to remove identifiers (e.g., ID, name) from the records. This approach is known to be naive, as in many cases re-identification is enabled based on quasi-identifiers (e.g., age, gender). In this research we examine an interesting and unexpected new quasi-identifier – music selections of an individual which represents their musical preferences. In the current era we consume music mainly on-demand by streaming (e.g., Spotify, YouTube, Apple Music) rather than as broadcast. The prosperity of the various music platforms is immense, and so is the sharing of beloved music, for example on online social networks. Thus, the creation of records that represent music selections is prevalent. In this paper we introduce a methodology to re-identify users based on their music selections, and prove the efficiency of the methodology empirically in four experiments ($n=22,38,35,30$). We discuss the social and emotional benefits of the current way we listen to music, against the threat of privacy disclosure.

在当前的数字时代，我们不断创建我们的活动记录，这些记录存储在各种数据存储中。保护我们隐私的一种常用方法是从记录中删除标识符（例如ID，名称）。众所周知，这种方法是幼稚的，因为在许多情况下，基于准标识符（例如年龄，性别）可以重新识别。在这项研究中，我们研究了一个有趣且出乎意料的新准标识符-音乐选择代表他们的音乐爱好的个人。在当前时代，我们主要通过流媒体（例如Spotify，YouTube，Apple Music）按需消费音乐，而不是通过广播消费。各种音乐平台的繁荣是巨大的，喜欢的音乐的共享也是如此，例如在在线社交网络上。因此，代表音乐选择的记录的创建是普遍的。在本文中，我们介绍了一种根据用户的音乐选择来重新识别用户的方法，并在四个实验中通过经验证明了该方法的有效性（$ñ=22，38，35，30$）。我们讨论了当前听音乐的方式在社交和情感上的好处，以防止隐私泄露的威胁。