## 3 Key Technologies in Trust Management for WSNs
### DoS Attacks in WSNs  
First, we answer RQ1: What types of DoS attacks in WSNs can be addressed using trust models? The review of prior research identified several types of DoS attacks in WSNs (Table 2). These attacks mostly impact the data or control packet sending rate (PSR), data or control packet receiving rate (PRR), data or control packet forwarding rate (PFR), and energy consumption rate (ECR). For example, a distributed DoS (DDos) attack involves several compromised nodes launching a DoS attack simultaneously [24]. Low-rate DoS (LDoS) attacks against SDWSNs [43] occupy network resources by forcing nodes to process intermittently sent, low-rate traffic. The aim is to overload the network by sending messages that do not match the rules in the nodes' flow tables [4; 10]. When a node receives such a message, it sends a new-flow control message to the network controller to request a new routing rule. The high volume of new-flow packets negatively affects the performance of the network.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Types of DoS Attacks** & **Impact Mechanisms** & **Key Impact Features** \\ \hline
1. Selective Forwarding & MLNs affect the availability of the network & \(\bullet\) & Decreased PFR at the MLN. \\ Attack [4] & services by dropping to a targeted destination & \(\bullet\) & Decreased ECR at the MLN. \\ \hline
2. Blackhole Attack [10] & The MLN claims to have the best route, causing all & \(\bullet\) & Increased PFR at the MLN. \\  & packets to be forwarded to it. It drops all & \(\bullet\) & Zero PFR at the MLN. \\  & forwarded packets. & & \\ \hline
3. Grey Hole Attack [47] & A variant of the blackhole attack. The MLN drops & \\  & packets intermittently or selectively. The & \(\bullet\) & Increased PFR at the MLN. \\  & degradation of network performance is less & \(\bullet\) & Decreased PFR at the MLN. \\  & detectable. & & \\ \hline
4. Flooding Attack [18] & The MLN sends a large number of connection & \\  & requests or packets and forces the attacked nodes & \(\bullet\) & Increased PSR at the MLN. \\  & to exhaust their resources by processing an & \(\bullet\) & Increased ECR the MLN. \\  & excessive number of invalid requests. & \\ \hline
5. Sinkhole Attack [47] & The MLN falsifies routing information and causes & \\  & network congestion by attracting a large amount & \(\bullet\) & Increased PFR at the MLN. \\  & of network traffic. & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Types of DoS attacks in WSNs that can be addressed by using trust models, impact mechanisms, and key impact features.  
In a Sybil attack, an MLN creates numerous fake identities, which disrupts the network communication channels [5]. Vampire attacks drain the energy of the sensor nodes, depleting their limited power supply [16]. Flooding attacks overwhelm nodes with excessive requests or data, exploiting network bandwidth and resources [18]. Hybrid attacks combine various attack strategies, increasing their complexity and effectiveness [13]. On-off attacks manipulate trust evaluation mechanisms by switching between legitimate and malicious behaviors [35]. Bad-mouthing and good-mouthing attacks use the trust model itself to disrupt WSN operations. The target nodes of a bad-mouthing attack become isolated and cannot participate in the network activities. In the good-mouthing attack, the attacker attempts to camouflage other malicious nodes by deliberately manipulating their reputation [5; 10; 15; 35]. Finally, we added to the table grey hole attacks and sinkhole attacks in  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Types of DoS Attacks** & **Impact Mechanisms** & **Key Impact Features** \\ \hline
6. Sybil Attack [5] & The attacker disrupts the topology of the network by adding multiple fake nodes, which reduces the efficiency of the routing and data transmission. &  
WSNs, as discussed by [PERSON] et al. [47], because their key impact features are similar to the ones of blackhole attacks.