A Survey on Security in Mobile Peer-to-Peer Architectures—Overlay-Based vs. Underlay-Based Approaches <s> Attacks on the P2P Routing Algorithm <s> Recent peer-to-peer research has focused on providing efficient hash lookup systems that can be used to build more complex systems. These systems have good properties when their algorithms are executed correctly but have not generally considered how to handle misbehaving nodes. This paper looks at what sorts of security problems are inherent in large peer-to-peer systems based on distributed hash lookup systems. We examine the types of problems that such systems might face, drawing examples from existing systems, and propose some design principles for detecting and preventing these problems. <s> BIB001 </s> A Survey on Security in Mobile Peer-to-Peer Architectures—Overlay-Based vs. Underlay-Based Approaches <s> Attacks on the P2P Routing Algorithm <s> Structured peer-to-peer overlay networks provide a substrate for the construction of large-scale, decentralized applications, including distributed storage, group communication, and content distribution. These overlays are highly resilient; they can route messages correctly even when a large fraction of the nodes crash or the network partitions. But current overlays are not secure; even a small fraction of malicious nodes can prevent correct message delivery throughout the overlay. This problem is particularly serious in open peer-to-peer systems, where many diverse, autonomous parties without preexisting trust relationships wish to pool their resources. This paper studies attacks aimed at preventing correct message delivery in structured peer-to-peer overlays and presents defenses to these attacks. We describe and evaluate techniques that allow nodes to join the overlay, to maintain routing state, and to forward messages securely in the presence of malicious nodes. <s> BIB002
The DHT lookup algorithm has to rely on the benign, cooperative behavior of the nodes that form the P2P network. Due to this, nodes that manipulate the lookup process have a serious influence on the network. During a Storage and Retrieval Attack BIB001 , a malicious nodes denies the access to objects maintained by itself. As it is hard to distinguish between unavailable and denied objects during a lookup, most P2P systems are not inherently able to detect this attack. The efficiency of this attack depends directly on the fraction of malicious nodes, since objects are equally distributed to nodes. Sit and Morris BIB001 introduced the Incorrect Lookup Routing attack. Malicious nodes drop or redirect incoming route requests instead of forwarding them to the correct destination. This is a simple and straight forward attack that affects the routing of lookup requests in DHTs. During the lookup process, a request is sent from the source to a node that is closer to the destination regarding the node-ID. Whenever a node receives a request, it checks whether it is the destination or whether it has to forward the request to the next overlay hop closer to the destination. For this recursive routing, Castro et al. introduced an analytical model that describes the effects of malicious nodes that drop packets (as shown in Equation 1). The packet delivery ratio (σ) is based on the average number of hops (h) per request and the fraction of malicious nodes (f ). While dropping lookup requests affects the routing process strongly, redirecting requests is a more subtle attack and may affect even DHTs protected by countermeasures. Tables   P2P routing tables have to be updated regularly to provide reliable routes when lookup requests have to be forwarded. Most DHTs update and optimize their routing tables by using entries provided by the routing tables of other nodes in the DHT. Malicious nodes may forge routing tables and provide routing table entries with links to inappropriate or non-existing nodes BIB001 . Further, corrupted routing updates can increase the fraction of routing table entries that refer to malicious nodes BIB002 . As most DHTs use metrics like proximity or age to optimize their routing table entries, malicious nodes may exploit these metrics to maximize the impact of the attack. Manipulation of the routing updates in order to increase the number of malicious nodes in a routing table of a benign node also results in a cascading effect. As each malicious node that is added to a routing table will provide routing updates, the fraction of malicious nodes increases as shown in Equation 2 BIB002 . The fraction of malicious routing entries f table increases whenever a routing update is initiated as each benign node provides entries with a fraction of f network malicious nodes, but each malicious node provides malicious entries only.