scholarly journals Parallel Evolutionary Peer-to-Peer Networking in Realistic Environments

2017 ◽  
Vol 2017 ◽  
pp. 1-17
Author(s):  
Kei Ohnishi
Keyword(s):  
Peer To Peer ◽  
P2p Network ◽  
Evolutionary Adaptation ◽  
Network Topologies ◽  
Simulation Results ◽  
Random Change ◽  
Peer To Peer Networking

In the present paper we first conduct simulations of the parallel evolutionary peer-to-peer (P2P) networking technique (referred to as P-EP2P) that we previously proposed using models of realistic environments to examine if P-EP2P is practical. Environments are here represented by what users have and want in the network, and P-EP2P adapts the P2P network topologies to the present environment in an evolutionary manner. The simulation results show that P-EP2P is hard to adapt the network topologies to some realistic environments. Then, based on the discussions of the results, we propose a strategy for better adaptability of P-EP2P to the realistic environments. The strategy first judges if evolutionary adaptation of the network topologies is likely to occur in the present environment, and if it judges so, it actually tries to achieve evolutionary adaptation of the network topologies. Otherwise, it brings random change to the network topologies. The simulation results indicate that P-EP2P with the proposed strategy can better adapt the network topologies to the realistic environments. The main contribution of the study is to present such a promising way to realize an evolvable network in which the evolution direction is given by users.

scholarly journals Detection of DDOS attacks in distributed peer to peer networks

2018 ◽  
Vol 7 (2.7) ◽  
pp. 1051
Author(s):  
Gera Jaideep ◽  
Bhanu Prakash Battula
Keyword(s):  
High Risk ◽  
Large Scale ◽  
Peer To Peer ◽  
P2p Network ◽  
Ddos Attacks ◽  
P2p Networks ◽  
Distributed Environment ◽  
Trace Back ◽  
Peer To Peer Networks ◽  
Direct Attack

Peer to Peer (P2P) network in the real world is a class of systems that are made up of thousands of nodes in distributed environments. The nodes are decentralized in nature. P2P networks are widely used for sharing resources and information with ease. Gnutella is one of the well known examples for such network. Since these networks spread across the globe with large scale deployment of nodes, adversaries use them as a vehicle to launch DDoS attacks. P2P networks are exploited to make attacks over hosts that provide critical services to large number of clients across the globe. As the attacker does not make a direct attack it is hard to detect such attacks and considered to be high risk threat to Internet based applications. Many techniques came into existence to defeat such attacks. Still, it is an open problem to be addressed as the flooding-based DDoS is difficult to handle as huge number of nodes are compromised to make attack and source address spoofing is employed. In this paper, we proposed a framework to identify and secure P2P communications from a DDoS attacks in distributed environment. Time-to-Live value and distance between source and victim are considered in the proposed framework. A special agent is used to handle information about nodes, their capacity, and bandwidth for efficient trace back. A Simulation study has been made using NS2 and the experimental results reveal the significance of the proposed framework in defending P2P network and target hosts from high risk DDoS attacks.  

scholarly journals AToM: Active topology monitoring for the bitcoin peer-to-peer network

2021 ◽  
Author(s):  
Federico Franzoni ◽  
Xavier Salleras ◽  
Vanesa Daza
Keyword(s):  
Reference Model ◽  
Peer To Peer ◽  
Network Protocol ◽  
P2p Network ◽  
Malicious Nodes ◽  
The Past ◽  
Side Channels ◽  
Peer Network ◽  
Topology Information ◽  
Peer To Peer Network

AbstractOver the past decade, the Bitcoin P2P network protocol has become a reference model for all modern cryptocurrencies. While nodes in this network are known, the connections among them are kept hidden, as it is commonly believed that this helps protect from deanonymization and low-level attacks. However, adversaries can bypass this limitation by inferring connections through side channels. At the same time, the lack of topology information hinders the analysis of the network, which is essential to improve efficiency and security. In this paper, we thoroughly review network-level attacks and empirically show that topology obfuscation is not an effective countermeasure. We then argue that the benefits of an open topology potentially outweigh its risks, and propose a protocol to reliably infer and monitor connections among reachable nodes of the Bitcoin network. We formally analyze our protocol and experimentally evaluate its accuracy in both trusted and untrusted settings. Results show our system has a low impact on the network, and has precision and recall are over 90% with up to 20% of malicious nodes in the network.

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