# Artificial Neural Network-Based Mechanism to Detect Security Threats in Wireless Sensor Networks
## 1 Introduction
The network layer within a WSN bears the responsibility of establishing and maintaining communication pathways between sensor nodes, enabling the routing of data from its source to the intended destination. Despite its essential role, the network layer is vulnerable to various security threats that imperil the integrity, confidentiality, and accessibility of data. In hop-to-hop communication in WSNs, a node always prefers the path towards the destination that includes fewer hops, which is called the optimal path. Due to the shorter distance, the optimal path provides many benefits like lower transmission overhead, lower energy consumption and less packet loss. When a node in multi-hop communication requests the path towards the destination, attacker nodes will present themselves as the nodes closest to the destination. The requesting node will select the path offered by the attacker node due to optimal path selection, and a routing attack then occurs in the WSN. Routing attacks manipulate the routing process to disrupt the accurate transmission of data, leading to network congestion, data loss, and possible denial of service. These attacks on the network layer come in several forms, such as flooding attacks, spoofing attacks, sybil attacks, black-hole attacks, gray-hole attacks, sink-hole attacks, and wormhole attacks [6]. Some of these types of attack are shown in Figure 1.  
Flooding attacks occur when an excessive number of route requests is generated within a network. These attacks can be highly damaging, depleting network resources, reducing availability, and overburdening nodes, preventing them from fulfilling their tasks [7]. The primary objective of a spoofing attack is to create a cyclic path between source and destination nodes within WSNs by introducing false routing information. Such an attack possesses the ability to manipulate routing data. This type of attack can result in severe consequences, including node partition, the redirection of nodes along incorrect paths, a reduction in network lifetime, and the dissemination of erroneous routing information [8]. A sybil attack involves an attacker forwarding multiple messages with different IDs to various nodes while making them appear as if they are coming from different sources. The attack thus causes collisions in the network, forcing nodes to find alternate routes. The attacker manipulates this situation to create confusion among nodes, making it challenging for them to select the correct path for data transmission. This type of attack can disrupt data integrity and alter the data flow by changing the routing path [9]. A rogue node in the network fabricates a black-hole attack by drawing all traffic to itself while claiming to have the shortest path to the target. Meanwhile, the packets are absorbed or dropped by the malicious node, preventing them from reaching their intended destination. The intention is to cause a \"black hole\" in the network that will hinder data from reaching its intended destination and obstruct communication. Gray-hole attacks, also known as selective forwarding attacks, are more intricate, as compromised nodes claim to have superior routes in order to attract data packets, with the aim of subsequently dropping or modifying the packets before they reach their destination. This attack subverts the routing process, potentially allowing unauthorized access to sensitive information. In wormhole attack, two or more nasty nodes band together through either high-speed wireless communication or ethernet or fiber-optic cables to form a tunnel that connects them. By swiftly moving packets from one end of the network to the other, the tunnel creates the illusion that nodes are closer to one another than they are. The attackers' goal is to establish a shortcut in the network, which could lead to nodes choosing the wrong route and possibly interfere with communication. Because of their transparent operation, wormhole nodes are invisible to other nodes in the network.