# An Overview of Fog Computing and Edge Computing Security and Privacy Issues
## 5 Security and Privacy Issues of Edge Computing  
Like fog computing, edge computing technology is also facing severe security challenges due to which the confidential data of users is at stake. In [38], the authors proposed salable distributed machine learning approach to detect attacks towards edge computing environment. In [39], the author surveys the existing security threats and privacy challenges along with the cryptographic techniques and countermeasures in edge computing network. We can summarize the main challenges of edge computing as fallow. First, normally nodes of edge are connected to a very a large number of IoT devices which have a limited resource in addition to different internal components this leads to having different types of routing protocols to disseminate messages this difference in the components may lead to some security issues. Which may lead to having several challenges in terms of access control in IoT environment. Another challenge that rise some concerns regard security in edge computing is key management of communications. While edge computing can provide end to end communication of IoT devices relying on different routing protocols; confidentiality and integrity of the data is still concerning. Therefore, a special key management and distribution mechanism may have to be designed to handle this concerns. In research work [40], the author gives a detailed analysis of security challenges in edge computing from five aspects: key management, access control, privacy protection, attack mitigation and anomaly detection. Furthermore, this paper presents the work achieved in edge computing security into five categories along with the current research situation in \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**Sr. No.** & **Privacy Aspects** & **Privacy Issues** \\ \hline
1. & User Privacy & Limited Network Visibility \\ \hline
2. & Identity Privacy & Inefficient Attack Detection techniques \\ \hline
3. & Data Privacy & Unavailability of user selective data collection \\ \hline
4. & Usage Privacy & Issues of Virtualization \\ \hline
5. & Location Privacy & Issues of Multitenancy \\ \hline
6. & Network Privacy & Suspected fog nodes \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Privacy and issues in fog. these categories. In Table 3, we have shown a summary of the data security and privacy challenges categorized with respect to the edge computing architecture [39]. There are different factors that lead to security and privacy issues in edge computing networks that put the user's personal data at risk, as discussed below:  
1. In edge computing, edge nodes exist nearer to users which result in reception of large amount of sensitive data. If any of these data are stolen, it can result in an alarming consequences. 2. Edge computing possess limited network resources, as compared to cloud computing, due to which they do not support complex encryption algorithms. 3. Edge computing network consists of dynamic environment which is constantly changing. As a result of this, attackers can easily become part of the group. Moreover, it is very difficult to create security rules for such dynamic network. The attacks on edge computing are as follows:  
* Eavesdropping: Similar to the fog computing, the eavesdropping attack in edge computing consists of an eavesdropper who can hide itself and maliciously monitor the activity on the channel to steal or overhear the confidential data. * Denial of Service (DoS) Attacks: Denial of service attack, just like in fog computing, allows the intruder or hacker to take control over the system or network and make its access unavailable for the legitimate user by sending a large amount of requests that jam the network. * Distributed Denial of Service (DDoS) Attack: It is an attack in which the goal of the attacker is to interrupt the normal services provided by different servers on the basis of distributed resources like cluster of compromised edge devices.