Biblio
Blockchain networks which employ Proof-of-Work in their consensus mechanism may face inconsistencies in the form of forks. These forks are usually resolved through the application of block selection rules (such as the Nakamoto consensus). In this paper, we investigate the cause and length of forks for the Bitcoin network. We develop theoretical formulas which model the Bitcoin consensus and network protocols, based on an Erdös-Rényi random graph construction of the overlay network of peers. Our theoretical model addresses the effect of key parameters on the fork occurrence probability, such as block propagation delay, network bandwidth, and block size. We also leverage this model to estimate the weight of fork branches. Our model is implemented using the network simulator OMNET++ and validated by historical Bitcoin data. We show that under current conditions, Bitcoin will not benefit from increasing the number of connections per node.
Peer to Peer (P2P) is a dynamic and self-organized technology, popularly used in File sharing applications to achieve better performance and avoids single point of failure. The popularity of this network has attracted many attackers framing different attacks including Sybil attack, Routing Table Insertion attack (RTI) and Free Riding. Many mitigation methods are also proposed to defend or reduce the impact of such attacks. However, most of those approaches are protocol specific. In this work, we propose a Blockchain based security framework for P2P network to address such security issues. which can be tailored to any P2P file-sharing system.
Peer-to-peer computing (P2P) refers to the famous technology that provides peers an equal spontaneous collaboration in the network by using appropriate information and communication systems without the need for a central server coordination. Today, the interconnection of several P2P networks has become a genuine solution for increasing system reliability, fault tolerance and resource availability. However, the existence of security threats in such networks, allows us to investigate the safety of users from P2P threats by studying the effects of competition between these interconnected networks. In this paper, we present an e-epidemic model to characterize the worm propagation in an interconnected peer-to-peer network. Here, we address this issue by introducing a model of network competition where an unprotected network is willing to partially weaken its own safety in order to more severely damage a more protected network. The unprotected network can infect all peers in the competitive networks after their non react against the passive worm propagation. Our model also evaluated the effect of an immunization strategies adopted by the protected network to resist against attacking networks. The launch time of immunization strategies in the protected network, the number of peers synapse connected to the both networks, and other effective parameters have also been investigated in this paper.
MANET is an infrastructure less, dynamic, decentralised network. Any node can join the network and leave the network at any point of time. Due to its simplicity and flexibility, it is widely used in military communication, emergency communication, academic purpose and mobile conferencing. In MANET there no infrastructure hence each node acts as a host and router. They are connected to each other by Peer-to-peer network. Decentralised means there is nothing like client and server. Each and every node is acted like a client and a server. Due to the dynamic nature of mobile Ad-HOC network it is more vulnerable to attack. Since any node can join or leave the network without any permission the security issues are more challenging than other type of network. One of the major security problems in ad hoc networks called the black hole problem. It occurs when a malicious node referred as black hole joins the network. The black hole conducts its malicious behavior during the process of route discovery. For any received RREQ, the black hole claims having route and propagates a faked RREP. The source node responds to these faked RREPs and sends its data through the received routes once the data is received by the black hole; it is dropped instead of being sent to the desired destination. This paper discusses some of the techniques put forwarded by researchers to detect and prevent Black hole attack in MANET using AODV protocol and based on their flaws a new methodology also have been proposed.