# Information Fusion in Autonomous Vehicle Using Artificial Neural Group Key Synchronization
## 3 Proposed Methodology
### Assessment of Security
#### 3.3.5 ECDSA and Hash Computation on GPU  
Nvidia has a number of various driving platforms that are ready to be installed in automobiles. The GPU on Nvidia SoC systems can be leveraged to speed safety computations, according to a study [44]. [PERSON] et al. [44] provides an ECDSA benchmark on both GPU and CPU units for the Nvidia Tegra X1 system. In offline mode, the Tegra CPU can do one signature procedure in around 10 milliseconds, while the Tegra GPU can speed up the process by three times. When it comes to validating information, the Tegra CPU can do one checking process in less than 1 millisecond, which is quicker than the GPU. The experiments in [45] demonstrated that now the Hash techniques SHA-512 and SHA3 sequence can be accelerated on the Tegra architecture and that the performance meets the delay criteria.  
As a result, Tegra's CPU deployment speed may only be sufficient for security apps. The Tegra SoC platform can speed up safety-related computation considerably quicker than the findings in [16] and will fulfill the delay requirements of security apps because of GPU acceleration. Furthermore, by allocating computing jobs for a large number of inputs utilizing such SoC architectures, this technique may achieve better speeds.  
Future confidentiality, reverse confidentiality, and key autonomy are safety objectives for dynamic organizations described by [PERSON] et al. [24]. Future confidentiality ensures that an attacker who has a collection of cluster keys will be unable to deduce any consecutive group key. To put it another way, when a principle quits the group, the key he left behind has no bearing on the architecture of succeeding group keys. During joining, a new key is generated, which ensures reverse confidentiality. In a ring procedure, the participants begin with an arbitrary input and synchronize to produce a newer key value. When a new principle joins a group using a tree structure-based protocol, reverse confidentiality is ensured by generating a newer key. The fresh group key will be produced when the principal joins the current node, as illustrated in Figure 7. We may argue that key independence is also ensured if any attacker who has a collection of cluster keys are unable  
Figure 11: M minimized SoC structure.  
to form any other cluster key since the session is fully reliant on the arbitrariness of the input. The number of test steps is also shown to be directly related to the weight range \(M\), slowing the coordination procedure and increasing the risk of intrusion. However, it helps to accelerate the coordination procedure when combined with an increase in \(M\) and the amount of concealed neurons. An attack's success rate eventually drops as a result of this. As a result, the current protocol is protected against attack, and it is also important to specify which people may be trusted to protect data. A confidential key decided upon by both participants may be utilized to produce a static length hash associated with an information for this type of integrity verification. Hash functions is used to generate a data integrity certificate that safeguards the message's authenticity and is transmitted with the message to safeguard it from illegal access. The communications are not hidden from an unknown party, but their integrity is guaranteed.