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large amounts of intrusion detection data across multiple nodes It is infeasible to exchange a lot of raw data in the peer-to-peer approach among all nodes because of the N N communication problem Without such information, nodes can perform intrusion detection based only on local data and possibly limited data provided by other nodes This may be insuf cient for detection of certain types of attacks 5422 Hierarchical IDS Architecture The alternative to the peer-to-peer architecture is the use of a hierarchy [85, 86] In this approach, every node plays a role in the intrusion detection process but some nodes have greater responsibilities Nodes organize into small neighborhoods to perform intrusion detection All nodes in the neighborhood are responsible for performing local intrusion detection for detecting attacks that can be detected locally At the same time, nodes in the neighborhood elect a leader and all nodes in the neighborhood collect data relevant to the intrusion detection process The collected data is sent to their leader The leader is then responsible for correlating the data and detecting attacks that cannot be detected by a node in the neighborhood using local data This is similar to the way attacks are detected in the peer-to-peer approach except that in that case the data is shared with every node in the network (not just the leader of the neighborhood) Each node in the peer-to-peer approach is then responsible for analyzing the data for attacks (not just the leader in the neighborhood) Leaders of each neighborhood may also cooperate with leaders of other neighborhoods for correlating data across neighborhoods This will help in detecting attacks spanning multiple neighborhoods In he hierarchical architecture, alerts about malicious behavior within the neighborhood are sent to the leader The leader is then responsible for sharing the alerts with other nodes in the neighborhood and with leaders from other neighborhoods In a similar manner, responses to attacks can be either decided locally or driven by the leader once it determines that there is an attack by correlating events received from the neighborhood Leaders can also coordinate responses across neighborhoods This concept can be extended so that a complete hierarchy that covers the whole network may be formed Neighborhoods can be formed using clustering algorithms and leaders can be elected using the same algorithms that elect clusterheads Such algorithms have been used in the past in routing protocols for MANET We will discuss several potential clustering algorithms in Section 5431 An example hierarchy is shown in Figure 56 Nodes in a neighborhood elect a leader ( rst-level clusterheads) First-level clusterheads may elect second-level clusterheads responsible for correlating data across neighborhoods and so on until there is a well-established hierarchy represented as a tree with a root node and leaf nodes, as shown in Figure 56 The hierarchy formation needs to be designed in view of the unique requirements of the MANET environment For example, the hierarchy needs to adapt well to movements of nodes A static hierarchy where leaders are elected at the beginning of the operation of the network without any changes being allowed is not acceptable in a MANET environment Nodes that move together as a group probably need to be part of the neighborhood in the hierarchy concept discussed earlier Also, not every node may be elected a leader and take increased IDS responsibilities Nodes with limited battery life probably should not be assigned leaders and take on those additional responsibilities It is also preferable that nodes that are hardened from a security viewpoint and better protected than other nodes become leaders and take on more of the coordination responsibilities This makes it more likely that the IDS functions will execute correctly We will discuss in.

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