# Privacy-Aware Access Protocols for MEC Applications in 5G +
## 1 Introduction  
The standardization of mobile edge computing (MEC) was initiated by the European Telecommunication Standards Institute (ETSI) in 2014. The purpose was to bring cloud computing to the mobile networks closer to the mobile users [1, 2]. In 2017, ETSI changed the term Mobile Edge Computing to multi-access edge computing while keeping the acronym MEC [3]. The MCP Generation Partnership Project (3 GPP) describes edge computing as an enabler that allows the hosting of services, provided by mobile network operators or by third parties, near the mobile user [4]. The local hosting of services has the benefits of lower end-to-end latency and reduced load in the core transportation network [5]. Cloud computing is a requisite for IoT devices to manage their data, and MEC provides cloud computing resources at the edge of the network. With the increment of IoT devices, the amount of produced data is increasing along with the need for storage and computing powers [6]. Therefore, computational offloading is emerging so that these IoT devices can take advantage of performing tasks locally in MEC rather than relying on cloud servers [7]. In addition to reducing the processing time and power, it helps protect user data privacy since transferring the local data to the cloud is a threat to the privacy of the data. For example, with a deep learning framework, data can be processed in MEC, and only the output is sent to the cloud server instead of the original dataset [8]. Thus, MEC can provide efficient, reliable, and secure support to IoT networks, which would also enable improvements of AI, blockchain, and big data techniques [9]. In addition, vertical industries (e.g., smart city services and vehicle-to-everything (V2X) [10]), distributed content delivery and caching are some examples of services that would benefit from the MEC applications [11]. Fifth-generation (5G) mobile networks have been designed to provide high bandwidth, low latency, and low operational costs [12]. One other aim of the development of 5G is to provide flexible deployment of the data plane [2]. The flexibility and the advances of 5G would help to support MEC and the deployment of innovative applications and intelligent services which IoT devices provide [9]. MEC is considered as an application function (AF) in the 5G system, and it is connected to the 5G network through the user plane function (UPF) [13]. While MEC is regarded as a key technology of 5G, MEC is already used in existing 4G networks [2]. A schematic illustration of MEC deployment in 5G networks is shown in Figure 1. A client of an application in a mobile device can be served not only by the main server of the application over the internet, but also by a local MEC application server in the network of the operator. To enable the latter, a new entity that is built upon data center technologies and called MEC host is deployed near the edge of the mobile network. More specifically, it can be deployed to several locations that are within or beside the radio access network (RAN) [3]. Either the mobile network operator (MNO) or third-party cloud services providers can deploy the MEC host to the mobile network [4]. Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and Oracle Cloud are examples of third-party cloud service providers [14, 15]. MEC usage involves a large amount of data passing between the user at the edge of the mobile network and the MEC application in the MEC host. Parts of these data may be personal and sensitive, which raises privacy concerns. The network entities involved in MEC usage could belong to the same company or different companies. Independently of who owns the network entities, analyzing the MEC-related data could be helpful. We will come back to these privacy issues in Section 3.2.1. Prior works on MEC security and privacy focus on protecting user privacy against outsiders.