# A Review on Mixed Reality: Current Trends, Challenges and Prospects
## 3 Concept of Mixed Reality
### Security and Privacy  
Although the development of an MR application provides great benefits, the practical use of it requires user acceptance. One issue with respect to user acceptance is preserving security and privacy. Privacy and security strategies need to consider different aspects, including the ability to gather user information, using MR information provided by third parties, the ability to share these systems, and providing security in the environment of these applications. Ref. [6] presented a comprehensive classification of all current security strategies for MR spaces into five classes: input protection, data access protection, output protection, interaction protection, and device protection (Table 3). Input protection refers to the protection of sensitive user information or information of users entering the MR platform that needs to be hidden. Data protection refers to the protection of information collected by MR sources, such as sensors, or wearable or mobile devices, which may be used by the 3D agent. Some concepts such as accuracy and accessibility are important in this regard. Output protection refers to the protection of information against external access and modification by other MR applications during rendering or display. User interaction protection refers to a mechanism that is needed to allow users to share their MR experience. Device protection refers to the mechanism that is used to maintain security in the MR tools and the input and output interfaces [6]. [PERSON]. [81] presented a secure prototype called SecSpace for collaborative environments using ontology reasoning, a distributed communication interface. [PERSON]. [82] used a security mechanism comprising three classes, i.e., spatial access, media access, and object access, to control access to the virtual elements and media used during teaching through user authorization.  
In large-scale MR applications such as MR social media platforms, the security mechanism is more complex. The security strategy needs to consider different levels of privacy, such as privacy for social network data and privacy for MR system objects. A good example in this regard is the Geollery platform proposed by [83]. This platform combines spatial resources, such as 3D geometry and social media (using Twitter) on an MR platform. In such an environment, the user can navigate in a 3D urban environment, chat with friends through a virtual avatar, and even paint a comment on a street wall in a collaborative environment. In this platform, the security mechanism is preserved on two levels: privacy for social media data and privacy for the virtual avatar. In social media, users have different modes such as preserving privacy for the public, a friend, and a virtual avatar, and also they can hide their display name in the system. [PERSON]. [84] proposed a model for preserving the security of 3D MR data (such as point clouds). This model formulated the security of 3D data and the necessary metrics using the adversarial inference model. Of course, the strategies used in this section provide great benefit, but they need improvements. To develop security strategies, one must consider concepts such as unlinkability to specify the proper management of the user, entity, party, and links with data, flow, and process, in addition to considering the concept of plausible deniability to manage the denial of individuals (i.e., toward each other or the entity during the process) [6]. The geometry-based inference model for 3D MR could be improved by incorporating photogrammetric information such as an RGB color profile [84].