INTRUSION DETECTION SYSTEMS FOR WIRELESS MESH AND ADHOC NETWORKS

Wireless communication has become indespensable in the digital age, allowing devices to connect and share data seamlessly without the need for physical connections. Among wireless networks, Wireless Mesh Networks (WMNs) and Mobile Ad-hoc Networks (MANETs) have gained popularity due to their decentralized nature and flexibility.

In WMNs, nodews work together to extend coverage over a broad area, forming a dynamic multi-hop network. In MANETs, mobile nodes communicate directly with each other , also using multi-hop pathways, without relying on fixed infrastructure.

OVERVEIW

WMNs and MANETs are unique compared to traditional wireless networks like Wi-Fi, primarily due to their decentralized structure and peer to peer communication model. In WMNs each node can both receive and transmit data creating multiple pathways for information to travel. This structure not only enhances fault tolerance but also enables network resilience, as the failure of a single node doesn’t necessarily disrupt the entire network.

In contrast MANETs are commonly deployed in situations where there are no fixed infrastructure, such as in military operations, emergency response scenarios or sensor networks. Each node in a MANET is typically mobile, with network topology changing frequently based on node movement. This dynamic topology enables rapid deployment and flexibility but also introduces security challenges, as the lack of central control and open communication medium makes the system vulnerable to attacks.

SECURITY CHALLENGES IN WMNs AND MANETs

The decentralized nature of WMNs and MANETs introduces distinct security challenges compared to conventional networks. Some of the primary threats to these networks include:

1. Eavesdropping: Since data is transmitted over the air, malicious nodes can intercept data packets to gain access to sensitive information.

2. Denial of service: In DoS attacks, malicious nodes flood the network with redundant requests or data packets, thereby exhausting network resources and disrupting legitimate communication. This attack can lead to network congestion, reducing network efficiency.

3. Man-in-the-Middle (MitM) attacks: In this attack, a malicious nod intercepts communication between two legitimate nodes. By positioning itself in between them, the attacker can manipulate or monitor the information exchanged, posing serious risks to data confidentiality and integrity.

4. Routing attacks: Due to their reliance on dynamic routing protocols, MANETs and WMNs are particularly vulnerable to routing attacks, where attackers attempt to manipulate or corrupt routing tables to control data flow.

5. Sybil attack: In a sybil attack, a single malicious node presents multiple identities, allowing it to appear as several nodes within the network. This can compromise network resource allocation, routing and consensus mechanisms threatening network stability.

6. Node compromise and Impersonation: A legitimate node that is physically captured by an attacker can lead to serious security breaches. Attackers can use the compromised node to impersonate it, gaining unauthorized access to the network. 

Addressing these challenges requires robust security mechanisms, with intrusion detection systems (IDS’s) being essential to mitigate risks or threats in real-time.

CHALLENGES AND FUTURE DIRECTIONS.

Despite the advancements in IDSs for WMNS and MANETs, several challenges still remaining:

 Resource constraints: Many nodes in WMNs and MANETs have limited processing power, memory and battery life. This makes it challenging to implement computationally intensive algorithms.

 Scalability: As the number of nodes in WMNs and MANETs increases, maintaining an effective IDS becomes more challenging. Large-scale networks require IDS that can scale efficiently without increasing latency in the network

 Adaptability to dynamic environments: WMNs and MANETs are characterized by constantly changing network topologies. IDS must adapt to these changes in real-time, without losing effectiveness or generating excessive false alarms.

 Privacy concerns: Monitoring network traffic for intrusion detection raises concerns over data privacy. IDS must strike a balance between effective monitoring and respecting user privacy.

 False positives and Negatives: An IDS must minimize false positives (legitimate traffic flagged as malicious) and flase negatives (malicious traffic undetected). Excessive positives leads to unnecessary disruptions, while false negatives leave the network vulnerable.