Commercial intrusion detection systems are designed for corporate networks; they almost always assume a small number of choke points between internal and external networks, and often they also assume centralized control of all the devices on the internal network. Neither assumption is valid for a peer-to-peer
overlay network, where there are typically a large number of mutually distrusting human agencies operating a small number of network peers each, and the routes between them are diverse.
It might seem that in the peer-to-peer environment, each node would have no choice but to run its own IDS. However, if we are willing to assume some degree of trust vested in other node operators, perhaps the task could be delegated. That’s the germ of this paper. For an idealized peer-to-peer network, they derive a game-theoretically optimal strategy for rotating the job of running the IDS around all the
super-peers (long-lived nodes with extra responsibilities; many real P2P networks have such nodes).
I like the concept, but the idealized scenario they used may be too idealized to be applicable in real life. Key assumptions which probably don’t hold include:
- The attacker does not already control any super-peers.
- The IDS is perfect: that is, if attack traffic passes through a node running an IDS, the attack will be detected and blocked.
- The attacker’s goal is to take control of, or deny availability of, a specific set of super-peers.
- The defender can predict in advance which nodes will be attacked. (I would accept this if it were probabilistic, e.g. assuming that the attacker is more likely to target nodes that contribute more to to the overall network capacity.)
I think a more realistic model would go something like this: The attacker is assumed already to control some fraction of the super-peers. (The attacker may also mount attacks from other computers, either independently or in collaboration with malicious super-peers.) The attacker seeks to avoid detection, and so does not mount overt attacks on other super-peers; instead, it has some strategy for violating the protocol to achieve an adversarial goal (e.g. forging blockchain transactions, deanonymizing users, delivering false data to users) The malicious peers execute the protocol honestly most of the time, but sometimes break the rules. The defender’s goal is to detect peers that are violating the protocol often enough that this can’t be an accident, while not wasting too many resources on monitoring overhead.
Note: This paper is said to have been published in the