# Sensor Network Environments: A Review of the Attacks and Trust Management Models for Securing Them
## 3 Trust Model Concepts
### Environments  
While trust models can be deployed in a number of areas, this paper focuses on models used in sensor networks or similar network types, where the nodes of the network are communicating data back to a central system. There are many types of network topologies and attributes. Featured below is a list of some of the main ones, with a brief definition of each. Networks are not limited to just one of these attributes and are often a combination of a few. For example, you could have a heterogeneous, static, clustered network. * Homogeneous: a network where all nodes are identical--same function, device, rank, etc. * Heterogeneous: a network where nodes are not all identical. * Hierarchical/clustered: networks where some nodes have a higher rank than others. Often, the network is controlled by a base station, which is in command of lower-level nodes or in a clustered network cluster head. These cluster heads are each in command of their own cluster of edge nodes. It is usually the case that the higher ranked the node is, the more computing power and resources it has. * Static: a network where nodes are neither leaving nor entering--e.g., a smart factory sensor network usually has the same sensors all the time. Note: sometimes static canbe referred to in terms of the nodes' physical positioning. In this paper, static refers to the above definition unless explicitly stated otherwise. * Dynamic: a network where nodes are entering and leaving the network, e.g., a mobile network or VANETs. Note: sometimes dynamic can be referred to in terms of the nodes' physical positioning. In this paper, dynamic refers to the above definition unless explicitly stated otherwise. Each network type will have different properties and challenges and will require slightly contrasting methods of determining the trust of its nodes. What follows is a description of some of the common types of networks that trust models are currently being used in. IoT/CPS: Internet of things and cyber-physical systems are similar in terms of their network structures. They are a rapidly advancing area, which can be applied to many different use cases, such as smart homes or cities, smart medical equipment/monitors and industry 4.0. Internet of things networks are, in general, a heterogeneous network comprised of many different sensors and controllable devices, all communicating with each other across a network. Trust models are applied to IoT-type networks in [9; 10; 11; 12; 13; 14; 15; 16; 17]. The challenges IoT networks tend to face are very common among most of the network environments. These challenges include potentially low computational power and low power resources (if battery-operated) for the network nodes, as well as the deployment of network nodes in a wide array of areas, which can leave some nodes vulnerable to physical compromise. Nodes within the network can be corrupted due to cyber or physical means, introducing internal attack threats to the network which cannot be effectively diminished by conventional security. Mobile crowd sensing: [18; 19] A subset of IoT applications, mobile crowd sensing is where large groups are used to collect data on some type of metric, such as traffic or noise. Many mobile phone apps use crowd sensing to collect data, such as google maps, which collects data on your location and speed to provide information to other users on traffic flow and journey times. Crowd-sensing applications use trust models to determine whether the data they get are trustworthy and useful or not, as in [19]. Wireless sensor networks: WSNs [3; 12; 13; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29] are perhaps one of the most common use cases for trust models. This is due to the fact that sensor nodes, more often than not, have very limited computing capabilities. Trust models can be developed in very lightweight manners to account for this. Their wide range of deployment and low computing capabilities make them vulnerable to being compromised in a similar manner to the previously mentioned IoT devices.