# From Bottom of Sea to Space: Quo Vadis IoT? So What About Security?
## 3 Security Challenges and Mechanisms
### IoT on the Ground
#### 3.2.2 Extensions with Applications in Transportation
The use of blockchain sharding can reduce stress on the main blockchain and increase throughput of data. The current work has been tested and proven feasible in real world applications. Another Blockchain-based trust management system using smart contracts is proposed by the authors of [127]. The proposed scheme also uses physically unclonable functions (PUFs), certificates, and dynamic Proof of Work (PoW) algorithms. The blockchain is used to manage trusted vehicles. Once a vehicle has established trust, PUFs assign the vehicle a unique ID. RSU establishes certificates to preserve the privacy of vehicles. Dynamic PoW allows for the system to scale to the level of traffic, which, in turn, takes up fewer resources when it is not needed. Through security and performance analysis the system is proven to be feasible in IoV and is superior when compared to similar methods of trust management. Many location-based emergency services used in the location of vehicles are very large IP-based networks. The issue with these systems is that they have high amounts of latency, problems with evenly disseminating information, and are vulnerable to attacks on the systems' trust. The authors of [128] propose an emergent semantic-based information-centric fog system. To help increase trust, the authors implement a semantic-based trustworthy routing scheme. This scheme would allow the system to detect fake nodes in the system. To do this, the authors implement fog nodes to maintain three different data structures: a forwarding information base, a pending interest table, and a content store. Using this information, the scheme is able to analyze the traffic effectively and find fake nodes from the network. Through testing, the system had a decrease in failure rate by 50% when compared to the traditional systems without fog networks or clouds. As mentioned earlier, intelligent routing is an important system in IoV that could allow for a reduction in wasted time. That being said, with an increase in the IoV, there is a large influx of data that needs to be processed in real time. To help combat this, the authors of [129] address issues in security, trust, and privacy, as well as propose a deep learning model to process the data. To do this it is proposed to use a lightweight 1D convolutional neural network (CNN) model. Through testing, it was shown to cause very little delay in real-time trust management. Large scale networks in IoV are becoming an increasingly tough challenge for having good network performance while still managing trust in the network. In the article [130], the authors discuss a hardware trusted model to build a trust chain. This would allow for a high level of protection, a tested running environment, and trusted state attestation (the ability to prove its identity). To prevent more latency created by the trust management system, it is proposed to use a remote novel batch approach. Simulation testing has proved that the trustworthiness of the network is intact while not creating an overly latent network. As discussed above, larger networks create issues as each node in the network must be verified using a trust management scheme. The authors of [131] propose a scheme that takes advantage of the blockchain to limit the bottlenecking that can occur in other schemes. Blockchain allows for a system to be traceable, untamperable, unforgeable, and transparent in a network of vehicles. Through the use of the Dirichlet distribution, reputation regression, and revocation punishment, the scheme can manage and classify the trust of vehicles in the network. This model shows a strong ability to find malicious nodes in a network when tested via simulations. * Attack Resilience In the IoV, the ability of a vehicle to defend against an attack is paramount to the safety of the passengers. One such attack, known as the Sybil Distributed Denial of Service (DDoS) Attack, has shown the vulnerabilities of edge node detection in current systems. The authors of [132] propose a Real-Time Edge Detection Scheme for Sybil DDoS.