# A Survey of Security Vulnerability Analysis, Discovery, Detection, and Mitigation on IoT Devices
## 4 Discussion
### Challenges  
The above evaluation reveals the challenges of current research of vulnerability analysis on IoT devices. As shown in Table 4, the impact on various technical fields is different. For IoT device vulnerability analysis technology, the challenges are as follows:  
(1) Complexity and Heterogeneity of Device  
This issue has always been the biggest challenge of IoT device vulnerability analysis technology. The IoT device is more heterogeneous than PC and mobile. It uses many CPU architectures such as ARM, MIPS, x86, and different types of operating system platforms such as Linux, Windows, and Android. It usually customizes firmware and memory usage. This makes it difficult to directly apply the industry's automated detection and discovery of vulnerabilities to the IoT field. The complexity of IoT devices aggravates the difficulty of static and dynamic analysis techniques. We find that arm-based Linux devices such as routers are selected as research targets mostly at this stage. The research on similarity detection expands cross-architecture scenarios [88; 89; 90; 91; 92; 93; 94; 95; 96]; others do not challenge this issue. (2) Limitations of device resources  
IoT devices generally run a reduced operating system or even run a single program on a microcontroller due to the lightweight requirements of products. The above reasons create the characteristics of limited devices resources. For the program of IoT device security testing, it is not very easy to deploy related analysis modules to the target to implement monitoring analysis on the periphery of the running program. Security researchers can not use traditional security analysis methods and tools. They need to restructure the analysis platform. In addition, dynamic analysis performance is reduced because the computing power of the device hardware is limited. In recent years, researchers have built simulation systems to address this challenge in the field of basic framework [43; 44; 45; 46; 47] and vulnerability discovery [59; 60; 64]. However, it has not been solved well, and this is still a long-term challenge. (3) Closed-Source Measures  
For general software, we can mine or detect source code or binary programs. For IoT device manufacturers, these can not be applied due to their closed source strategy. Source code analysis is no longer applicable to IoT vulnerability analysis, such as similarity detection on source code in Section 3.3.2. They even encrypt the firmware and strengthen the authentication of the serial debugging interface and think it is safer. For example, for the latest firmware of Dlink DIR-882(867, 878), 360 clear robots are all encrypted. Thus, vulnerability analysis based on source code, firmware, and the debugging interface is becoming increasingly difficult. Through previous evaluations, we find that vulnerability discovery and detection technology have avoided relying on these requirements, such as debugging interface [59; 60], and firmware [57] in the past two years. However, there are new problems such as incomplete information. \begin{table}
\begin{tabular}{c l c c c c} \hline \hline
**Category** & **Name** & **T1** & **T2** & **T3** & **T4** \\ \hline \multirow{3}{*}{Challenges} & Complexity and heterogeneity of device & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\  & Limitations of device resources & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\  & Closed-source measures & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\  & Application of AI technology & & \(\surd\) & \(\surd\) & \(\surd\) \\ \multirow{3}{*}{Opportunities} & Dependency of third-party and open source code & \(\surd\) & \(\surd\) & \(\surd\) \\  & Development of peripheral systems & & \(\surd\) & \(\surd\) & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: This table summarizes impact scope of challenges and opportunities. The scope of influence includes four kinds such as basic framework of vulnerability analysis (T1), technology of vulnerability discovery (T2), technology of vulnerability detection (T3), technology of vulnerability Mitigation (T4).