On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On the origin of power laws in Internet topologies
ACM SIGCOMM Computer Communication Review
IEEE Internet Computing
Comparing Hybrid Peer-to-Peer Systems
Proceedings of the 27th International Conference on Very Large Data Bases
Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and
Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and
Inferring internet denial-of-service activity
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
The price of validity in dynamic networks
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Improving Query Response Delivery Quality in Peer-to-Peer Systems
IEEE Transactions on Parallel and Distributed Systems
The price of validity in dynamic networks
Journal of Computer and System Sciences
Optimizing overlay topology by reducing cut vertices
Proceedings of the 2006 international workshop on Network and operating systems support for digital audio and video
Gossip-based aggregation of trust in decentralized reputation systems
Autonomous Agents and Multi-Agent Systems
On the reliability of large-scale distributed systems - A topological view
Computer Networks: The International Journal of Computer and Telecommunications Networking
A self-organization mechanism based on cross-entropy method for P2P-like applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Probabilistic replication based on access frequencies in unstructured peer-to-peer networks
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
| Hi-index | 0.00 |
Peer-to-peer systems such as Gnutella are resilient to failures at a single point in the network because of their decentralized nature. However an attack resulting in the removal of a small percentage of highly connected nodes could cripple such systems. We believe that distributed attack recovery is not simply a reactive process but requires proactive measures by the nodes in the system. We propose a distributed recovery method, where clients proactively detect attacks by monitoring the rate at which their first and second-degree neighbors leave the network and reconfigure themselves to form a topology that is more resilient to attacks when one has been detected. This topology is created and maintained through a new type of node discovery mechanism that is used during normal network operations. The recovery method is able to reconnect the network and deal with any ongoing attacks once one has started.