Digital twin technology is revolutionizing the digital economy by merging the physical and virtual worlds, making it an essential for digitizing industries. A digital twin (DT), a virtual replica of a physical object, system, or process, is anticipated to create an intelligent, predictive, and highly efficient economy. There is an increasing demand for novel developments in DT across a variety of industries, including manufacturing, construction, oil and gas, aerospace, energy, and healthcare. Certain stakeholders are already realizing that DTs not only enhance efficiency and reduce costs but also enable the creation of new service offerings. However, the adoption of DT brings along a number of challenges, including concerns about data privacy and security. DT has become a popular topic with increasing interest in academic journal articles and solution offers from the industrial sector. This study presents a literature overview of DT in the context of privacy and security issues to gain a better understanding of the key barriers that may impact the future adoption of DT technologies. The paper presents an analysis of articles published in Scopus, Web of Science, and IEEE Xplore databases between 2019 and 2024 that examine the privacy and security problems of DT.