# From Bottom of Sea to Space: Quo Vadis IoT? So What About Security?
## 3 Security Challenges and Mechanisms
### IoT on the Ground
#### 3.2.8 Extensions with Social Applications  
Internet of People The Internet of People is a recent trend in research on the IoT that has led to a variety of different discoveries. The authors of [184] propose a method to improve the current recommendation systems that are becoming used more in areas such as social media searches. The algorithm they propose takes a user's relationship in a network and the item's relationship in a network. To adjust weights of items in the system a tuning parameter is added. Objects that are not yet seen are extracted and ranked based on resource scores. Testing shows a high accuracy on top recommended items for given datasets.  
Similar to the above, the authors of [185] create an interest detection framework based on social networks. Using similarities between different likes and dislikes of a user, a proximity function is able to create links between items. The scheme uses a greedy community detection algorithm to further find users with common likes and dislikes. Lastly, a link detection algorithm is used to create links between items that are commonly linked together using community information. When tested experimentally, the proposed method outperforms other deep learning schemes built for similar purposes.  
To the best of the authors' knowledge, security challenges and mechanisms of this extension have not been adequately studied in existing research works.  
Internet of Scholars (IoS) has appeared in a few recent research reports. Scholars are having a more difficult time finding needed publications and scholarly connections as more publications are released. A recommendation tool specifically for scholars can be very useful. The authors of [186] introduce the idea of a scholarly friend recommendation system. Using academic social networks, the authors hope to help scholars find people who do research in areas that could benefit each other. The authors first construct an attributed social network using digital libraries. Attributed random walk is used to model scholar attributes and network structure. To create recommendations, a graph recurrent neural framework is used. The effectiveness of the model is shown when tested on information collected from ResearchGate and LinkedIn.  
In our review, we have not found any research work focusing on the security of the Internet of Scholars.  
Internet of Mobile Things has also been recently studied in the literature. There are many applications that involve networks of mobile devices. Issues arise due to the computational limitations these devices have, which makes it difficult to send large amounts of data. In [187] the authors propose a scheme for fog computing based on Fountain codes, reducing latency and processing time of receiving positions of mobile devices. The fog computing scheme is able to offload tasks using its high computation power. The scheme takes advantage of maximum distance separable code allowing for the scheme to be highly flexible with low complexity. Testing shows that through the use of the Fountain code-based scheme the loads of transmission and communication are reduced.  
This extension has not been studied from a security perspective in existing research works.