METrust: A Mutual Evaluation-based Trust Model for P2P Networks

It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.

Mathematical Model Validation of Search Protocols in MP2P Networks

Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive flooding technique,floods the network with query messages,while the random walk technique operates by contacting the subsets of every node’s neighbors at each step,thereby restricting the search space.One of the key challenges in an ad-hoc network is the resource or content discovery problem which is about locating the queried resource.Many earlier works have mainly focused on the simulation-based analysis of flooding,and its variants under a wired network.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of P2P systems running over MANET.In this paper,we describe how P2P resource discovery protocols perform badly over MANETs.To address the limitations,we propose a new protocol named ABRW(Address Broadcast Random Walk),which is a lightweight search approach,designed considering the underlay topology aimed to better suit the unstructured architecture.We provide the mathematical model,measuring the performance of our proposed search scheme with different widely popular benchmarked search techniques.Further,we also derive three relevant search performance metrics,i.e.,mean no.of steps needed to find a resource,the probability of finding a resource,and the mean no.of message overhead.We validated the analytical expressions through simulations.The simulation results closely matched with our analyticalmodel,justifying our findings.Our proposed search algorithm under such highly dynamic self-evolving networks performed better,as it reduced the search latency,decreased the overall message overhead,and still equally had a good success rate.

Cluster based hierarchical resource searching model in P2P network

For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer （P2P） network, a improved model to decrease the network expense is proposed, which establishes a duster in P2P network, auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.

Epidemiological modeling of passive worm propagation on the P2P file-sharing network

The peer-to-peer（P2P） file-sharing network as a vehicle of disseminating files has become very popular. The appearance of dozens of kinds of passive worms on this network has, however, made it unsecured. This problem has been paid attention and a few of models for passive worm propagation has been presented. Unfortunately, the dynamic properties of this network are ignored in these models. Given the fact, the characteristics of both this network and the passive worm are identified, and on this basis a new mathematical model of passive worm propagation on the P2P network is presented in applying epidemiology in this paper. Note that the dynamic properties of this network are considered in the presented model. The model has been validated by large scale simulation experiments, which demonstrates that the presented model may be used for analyzing the behaviors of passive worms and predicting the trend of their propagation.

Modeling active worm propagation on the P2P network

This paper analyzes the characteristics of the Peer-to-Peer （P2P） active worm and its attacking mechanism, and then proposes a mathematical model of propagation of the P2P active worm applying Epidemiology. Based on the analysis on the protocols of realistic P2P systems, a software which can be used to simulate the P2P network environment and the propagation of P2P active worm is imple- mented in this paper. A large number of simulation experiments are performed using the developed simulation software. The results from these simulation experiments validate the proposed model, which means that the model can be used to analyze the spreading behaviors of the P2P active worm and predict its trend.

Analytical Comparison of Resource Search Algorithms in Non-DHT Mobile Peer-to-Peer Networks

One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question?Broadcasting is a basic technique in the Mobile Ad-hoc Networks(MANETs),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive ooding technique oods the network with query messages,while the random walk scheme operates by contacting subsets of each node’s neighbors at every step,thereby restricting the search space.Many earlier works have mainly focused on the simulation-based analysis of ooding technique,and its variants,in a wired network scenario.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of mobile P2P networks.In this article,we mathematically model different widely used existing search techniques,and compare with the proposed improved random walk method,a simple lightweight approach suitable for the non-DHT architecture.We provide analytical expressions to measure the performance of the different ooding-based search techniques,and our proposed technique.We analytically derive 3 relevant key performance measures,i.e.,the avg.number of steps needed to nd a resource,the probability of locating a resource,and the avg.number of messages generated during the entire search process.

The credit risk of the borrower＇s credit in P2P network

P2P network lending refers to the individual through the oJfline trading platform provided by the Business Company provides small loans to other individuals. According to the sea tree Lingyi data stalistics, as of November 2014. China has 1371 P2P network lending company, than by the end of2013 638 over more than doubled. Since 2014,The cumulative volume of the whole network lending industry is up to 431.2 billion yuan. With the increasing social awareness in the industry, the future of the number and amount of P2P network lending companies in China will continue to grow rapidly. However, at present our P2P network credit risk management issues is serious, lacking of professional risk management personnel,who audit on the borrower＇s credit mostly limited to the upload information of borrowers. Credit rating is largely dependent on the subjective judgment of the risk control personnel and audit staff, which can not meet the requirements of the transaction participants in the loan security measures.This paper to pat the loan company were empirical research, through the logistic model to find the breach the key influence factors, to construct the borrower＇s credit risk evaluation methods, and to provide the P2P network lending risk control with specific policy recommendations.

A Comprehensive and Adaptive Trust Model for Large-Scale P2P Networks

Based on human psychological cognitive behavior, a Comprehensive and Adaptive Trust （CAT） model for largescale P2P networks is proposed. Firstly, an adaptive trusted decision-making method based on HEW （Historical Evidences Window） is proposed, which can not only reduce the risk and improve system efficiency, but also solve the trust forecasting problem when the direct evidences are insufficient. Then, direct trust computing method based on IOWA （Induced Ordered Weighted Averaging） operator and feedback trust converging mechanism based on DTT （Direct Trust Tree） are set up, which makes the model have a better scalability than previous studies. At the same time, two new parameters, confidence factor and feedback factor, are introduced to assign the weights to direct trust and feedback trust adaptively, which overcomes the shortage of traditional method, in which the weights are assigned by subjective ways. Simulation results show that, compared to the existing approaches, the proposed model has remarkable enhancements in the accuracy of trust decision-making and has a better dynamic adaptation capability in handling various dynamic behaviors of peers.

Modeling and analysis of anti-worm in P2P networks

Anti-worm is an effective way to fight against malicious worm and has been followed closely by malicious worm researchers recently. However, active and passive confronting technologies in peer-to-peer （P2P） networks have not been studied in depth. This paper introduces both of them to fight against malicious worm in P2P networks. To study their effectiveness in P2P networks, this paper takes the topology degree in P2P networks into consideration and puts forward a four-state propagation model for active anti-worm and a five-state propagation model for passive anti-worm respectively. Both of the models are simplified in the case that size of a P2P network is large enough. The simulation results have not only validated the effectiveness of our propagation models but also evaluated the excellent performance of both active anti-worm and passive anti-worm.

Proactive worm propagation modeling and analysis in unstructured peer-to-peer networks

It is universally acknowledged by network security experts that proactive peer-to-peer (P2P) worms may soon en-gender serious threats to the Internet infrastructures. These latent threats stimulate activities of modeling and analysis of the proactive P2P worm propagation. Based on the classical two-factor model,in this paper,we propose a novel proactive worm propagation model in unstructured P2P networks (called the four-factor model) by considering four factors:(1) network topology,(2) countermeasures taken by Internet service providers (ISPs) and users,(3) configuration diversity of nodes in the P2P network,and (4) attack and defense strategies. Simulations and experiments show that proactive P2P worms can be slowed down by two ways:improvement of the configuration diversity of the P2P network and using powerful rules to reinforce the most connected nodes from being compromised. The four-factor model provides a better description and prediction of the proactive P2P worm propagation.

A Review of P2P Financial Research

Since 2007,people's spending habits began to change:from cash to the bank card,from mobile phone to non-cash transactions,from traditional finance to network finance.And the rapid rise of emerging industries results in many of the P2P Financial Corporation established,it makes the P2P platform trading volume continue to rise at an alarming rate.In this context,the industry self-discipline environment is like the mining of good and evil.The atmosphere was foul,bad phenomenon,investors difficult activist phenomenon,the phenomenon of credit default as one falls,another rises to a series of problems,such as serious absence of P2P financial supervision to promote the healthy and sustainable development,is a major problem for all participants,which must to be solved.Firstly,P2P development of management mode in the current situation in our country is discussed,and then it analyzes the P2P network of financial management platform,finally it proposes the existing problems in the relative countermeasures and suggestions of effective P2P financing mode,hoping to promote its advantages,overcoming the disadvantages of P2P.

基于SNMP的网络正常运转模型

SNMP(简单网络管理协议 )是IETF提出的网络管理的标准 ,P2 DR模型是可适应网络安全理论的主要模型。本文在上述理论的基础上 。

Raft Consensus Algorithm Based on Credit Model in Consortium Blockchain

As one of the underlying technologies of the blockchain,the consensus algorithm plays a vital role in ensuring security and efficiency.As a consensus algorithm for the private blockchain,Raft has better performance than the rest of the consensus algorithms,and it does not cause problems such as the concentrated hashing power,resource waste and fork.However,Raft can only be used in a non-byzantine environment with a small network size.In order to enable Raft to be used in a large-scale network with a certain number of byzantine nodes,this paper combines Raft and credit model to propose a Raft blockchain consensus algorithm based on credit model CRaft.In the node credit evaluation phase,RBF-based support vector machine is used as the anomaly detection method,and the node credit evaluation model is constructed.Then the Trust Nodes List(TNL)mechanism is introduced to make the consensus phase in a creditable network environment.Finally,the common node is synchronized to the consensus node to update the blockchain of the entire network.Experiments show that CRaft has better throughput and lower latency than the commonly used consortium blockchain consensus algorithm PBFT(Practical Byzantine Fault Tolerance).