# Sensor Network Environments: A Review of the Attacks and Trust Management Models for Securing Them
## 4 Attack Types
### Reputation Attacks  
These attacks specifically affect trust models. They are quite similar in terms of the goals they wish to achieve. Different reputation-type attacks are often used interchangeably or in conjunction with one another to attack vulnerabilities in a given trust model.  
**Breakout fraud/on-off.** Sometimes referred to as a zigzag [30] or garnished attack [22; 29], this type of attack involves a node behaving as expected by the network for a period of time. Then, when its trust values are high enough, it will launch an attack. When the model detects suspicious behavior from the node and the trust value begins to fall, the node can stop behaving maliciously and return to normal behavior, which in turn will restore the trust value before the network ejection is initiated. This process can be repeated multiple times, as long as the node does not let its trust value drop below the threshold value. Attacks such as this demonstrate the need for a dynamic and fast trust-updating response to catch attacks early, before they disappear again for a period of time.  
**Bad-mouthing.** Bad-mouthing involves a malicious node falsely reporting the indirect trust values of another node. This will negatively affect its trust value. Collusion or sybil attacks can be used to boost the effectiveness of this attack. Some models use methods where only positive trust values can be reported back to counteract bad-mouthing attacks [20].  
**Ballot-stuffing.** As it is in the physical world, ballot-stuffing involves one user stuffing the ballot with the same vote to change the results of a vote. This scenario is the same in the digital world, where a node can stuff the ballot in a majority voting system or an indirect trust system. This can affect its own or other nodes' trust values. This attack can be achieved through means of sybil, or collusion, and this technique can also be used for self-promoting and bad-mouthing attacks in models that are vulnerable to it.  
**Collusion**. This attack can be considered as a reputation-based attack or a routing attack (or it can also be used for forms of DDoS attacks). In this attack type, multiple attackers work in collusion to modify packets, drop routing packets [41], perform bad-mouthing or self-promoting attacks or compromise majority voting schemes. It is a very broad class of attack that essentially describes any attack where there are multiple attack nodes working together to achieve a common goal.  
**Sybil.** In this scenario, a node presents multiple identities to other nodes in the network [42]. These identities can be forged or stolen from other nodes. This allows the node to have a greater say in the network and can be used to boost bad-mouthing orself-promoting attacks. It can also be used to corrupt data, majority voting schemes and other processes in the network.  
**Self-promoting**. This is an attack where the node simply reports better trust values for itself or another node that it is working with. This attack aims to boost the trust value of the attacker, giving it more access to launch further attacks. This attack can be launched using sybil or collusion attacks, as mentioned above.