**3.5. Rating component: Cautious rating for trust enabled routing (CRATER)**

In this section, a new rating approach for reputation systems in WSN called CRATER[85] is presented. CRATER evaluates nodes reputation by a risk representation. This risk value is computed based on FHI, SHI and idle behavior (NBP). The mathematical modeling of CRATER assumes a set of conditions that we define as cautious assumptions in which a node is very cautious in dealing with other's information.

In reputation systems, after a node gathers some information regarding the behavior of other nodes of interest, it needs to evaluate or rate these nodes. This is done by the rating function or the rating component of the system. Rating function is based on the node's own observation, other nodes' observations that are exchanged among themselves and the history of the observed node.

The rating component of a reputation system is a very critical part since it is responsible for providing the reputation of nodes. Thus, it can be considered as the heart of any reputation system.

To illustrate the rating operation, assume that node A wants to evaluate a reputation value for a node B that may or may not be directly monitored by A. Then, the reputation value of B evaluated by A is a number that reflects how good or bad node B behaves from the perspective of node A, considering:


Once a reputation value for B is formed by A, A will decide about a certain level of trust relationship with B

An important issue in rating is the reputation update. Since rating is related to node behavior, the reputation of a node should be a dynamic metric that changes with time. This change would be due to new FHI observations, new SHI, or other defined aspects like, for example, to "forgive" some idle malicious nodes.

A new rating technique called *Cautious RAting for Trust Enabled Routing* (CRATER) is presented in [85]. Basically, this technique identifies three rating factors: FHI, SHI and Neutral Behavior period (NBP) during which a node is not doing any activity. The new contribution in CRATER is its mathematical approach that is used to rate nodes based on what we call cautious assumptions, which are very true in many applications in WSN.

## *3.5.1. Cautious assumptions*

264 Wireless Sensor Networks – Technology and Protocols

monitoring activity.

history of the observed node.

perspective of node A, considering:

hand information, SHI.

system.

FHI.

Thus, in our EMPIRE solution, we are trying to induce a condition-independent and probabilistic "virtual scheduling" among nodes to overcome that problem. It is very important here to emphasize the node cooperation assumption. Node cooperation implies that a node will be willing to inform other nodes about its findings from its NMA. This is known as indirect reputation knowledge sharing or second hand information propagation. With this assumption, nodes will still be able to capture the events it loses during its OFF state. EMPIRE is based on a distributed and probabilistic monitoring approach. The main goal of EMPIRE is to provide good monitoring operation that satisfies the security requirements, while using the least possible nodal monitoring activity. This way, a node will also be able to conserve its resources. Our simulation results show that EMPIRE can satisfy various levels of monitoring requirements with different possible choices of nodal monitoring activity levels. Moreover, EMPIRE is safe in the sense that it can differentiate between malicious and non malicious nodes regardless of the choice of the nodal

A detailed discussion and analysis of the EMPIRE procedure, simulation setup,

In this section, a new rating approach for reputation systems in WSN called CRATER[85] is presented. CRATER evaluates nodes reputation by a risk representation. This risk value is computed based on FHI, SHI and idle behavior (NBP). The mathematical modeling of CRATER assumes a set of conditions that we define as cautious assumptions in which a

In reputation systems, after a node gathers some information regarding the behavior of other nodes of interest, it needs to evaluate or rate these nodes. This is done by the rating function or the rating component of the system. Rating function is based on the node's own observation, other nodes' observations that are exchanged among themselves and the

The rating component of a reputation system is a very critical part since it is responsible for providing the reputation of nodes. Thus, it can be considered as the heart of any reputation

To illustrate the rating operation, assume that node A wants to evaluate a reputation value for a node B that may or may not be directly monitored by A. Then, the reputation value of B evaluated by A is a number that reflects how good or bad node B behaves from the

Monitoring results obtained by direct observations from A as first hand information,

Monitoring results gathered from other nodes observing B and shared with A as second

**3.5. Rating component: Cautious rating for trust enabled routing (CRATER)** 

performance measures, and simulation results can be found in [84].

node is very cautious in dealing with other's information.

Monitoring results of all types of routing activities.

The rating methodology proposed in CRATER assumes what we call "the cautious assumptions". These assumptions are:

