*3.5.2. Rating factors in CRATER*

In CREATER, each node rates its neighbor by assigning a risk value to the corresponding monitored node. The risk value of node j assigned by node i, ri,j is defined as a quantity that represents how much risk the node i will encounter when it uses node j as a next hop to route its packets. This value ranges from 0 to 1 where 0 represents the minimum risk and 1 represents the maximum risk. The reputation of node j as per node i is then computed as:

$$\mathbf{r}\mathbf{e}\mathbf{p}\mathbf{v}\mathbf{u} \tag{1}$$

The CRATER operation is based on rating the nodes on the risk notion. Each node evaluates the risk values of its neighbors and takes the proper action based on the values it obtains. The risk values are affected by three factors:


Each node in the system continuously and periodically updates the risk values of its neighbors based on the information collected during these update periods .

The general algorithm that a node i follows to rate its neighbor j is:

	- Calculate ri,j,FHI using the new FHI.
	- Update the old risk value, ri,j,old using the new calculated ri,j,FHI to get ri,j.
	- Calculate the ri,j,SHI using the SHI.
	- Update ri,j using the ri,j,SHI
	- Update ri,j if neutral behavior periods are realized.

When node j is observed by i for n consecutive update periods to be idle in its behavior, node i will give node j a chance to be more trusted by reducing its current risk value. A node is considered to be in idle behavior if it does not perform any routing operation. The reduction procedure follows exactly the same methodology explained in rating based on FHI when ri,j,FHI=0. The only difference here is that in the case of neutral behavior the update is done after we observe such behavior during n consecutive update periods whereas it is done immediately after an update period in the case of ri,j,FHI=0. The choice of n is a design parameter that depends on how much a network is tolerable against attacks. High values of n mean that we are not willing to forgive malicious nodes quickly.

A detailed discussion and analysis of the CRATER approach, simulation setup, performance measures, and simulation results, can be found in [85].
