FPSblo:A Blockchain Network Transmission Model Utilizing Farthest Point Sampling

Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.

Monitoring Peer-to-Peer Botnets:Requirements,Challenges,and Future Works

The cyber-criminal compromises end-hosts(bots)to configure a network of bots(botnet).The cyber-criminals are also looking for an evolved architecture that makes their techniques more resilient and stealthier such as Peer-to-Peer(P2P)networks.The P2P botnets leverage the privileges of the decentralized nature of P2P networks.Consequently,the P2P botnets exploit the resilience of this architecture to be arduous against take-down procedures.Some P2P botnets are smarter to be stealthy in their Commandand-Control mechanisms(C2)and elude the standard discovery mechanisms.Therefore,the other side of this cyberwar is the monitor.The P2P botnet monitoring is an exacting mission because the monitoring must care about many aspects simultaneously.Some aspects pertain to the existing monitoring approaches,some pertain to the nature of P2P networks,and some to counter the botnets,i.e.,the anti-monitoring mechanisms.All these challenges should be considered in P2P botnet monitoring.To begin with,this paper provides an anatomy of P2P botnets.Thereafter,this paper exhaustively reviews the existing monitoring approaches of P2P botnets and thoroughly discusses each to reveal its advantages and disadvantages.In addition,this paper groups the monitoring approaches into three groups:passive,active,and hybrid monitoring approaches.Furthermore,this paper also discusses the functional and non-functional requirements of advanced monitoring.In conclusion,this paper ends by epitomizing the challenges of various aspects and gives future avenues for better monitoring of P2P botnets.

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.

Peer-to-Peer网络中文件查询的研究

随着P2P网络应用研究的热化,文件查询即给出文件名后如何确定文件的存放位置,已经成为大规模分布式网络中最常遇到的问题之一。文件查询的效率直接影响到整个P2P网络的性能。本文从P2P网络的基本现状出发,给出了目前文件查询在非结构化,结构化和松散结构化P2P网络中的解决方案并进行了深入分析和比较。文章最后指出了目前P2P网络中文件查询算法的缺点和今后的研究方向。

Deadline-aware network coding for video on demand service over P2P networks

We are interested in providing Video-on-Demand (VoD) streaming service to a large population of clients using peer-to-peer (P2P) approach. Given the asynchronous demands from multiple clients, continuously changing of the buffered contents, and the continuous video display requirement, how to collaborate with potential partners to get expected data for future content delivery are very important and challenging. In this paper, we develop a novel scheduling algorithm based on deadline- aware network coding (DNC) to fully exploit the network resource for efficient VoD service. DNC generalizes the existing net- work coding (NC) paradigm, an elegant solution for ubiquitous data distribution. Yet, with deadline awareness, DNC improves the network throughput and meanwhile avoid missing the play deadline in high probability, which is a major deficiency of the con- ventional NC. Extensive simulation results demonstrated that DNC achieves high streaming continuity even in tight network conditions.

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.

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.

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.

Deep Q-Learning Based Optimal Query Routing Approach for Unstructured P2P Network

Deep Reinforcement Learning(DRL)is a class of Machine Learning(ML)that combines Deep Learning with Reinforcement Learning and provides a framework by which a system can learn from its previous actions in an environment to select its efforts in the future efficiently.DRL has been used in many application fields,including games,robots,networks,etc.for creating autonomous systems that improve themselves with experience.It is well acknowledged that DRL is well suited to solve optimization problems in distributed systems in general and network routing especially.Therefore,a novel query routing approach called Deep Reinforcement Learning based Route Selection(DRLRS)is proposed for unstructured P2P networks based on a Deep Q-Learning algorithm.The main objective of this approach is to achieve better retrieval effectiveness with reduced searching cost by less number of connected peers,exchangedmessages,and reduced time.The simulation results shows a significantly improve searching a resource with compression to k-Random Walker and Directed BFS.Here,retrieval effectiveness,search cost in terms of connected peers,and average overhead are 1.28,106,149,respectively.

Improving Resilience against DDoS Attack in Unstructured P2P Networks

In unstructured peer-to-peer （P2P） systems such as Gnutella, a general routing search algorithm is used to blindly flood a query through network among peers. But unfortunately, malicious nodes could easily make use of the search approach launching distributed denial of service （DDoS） attack which aims at the whole network. In order to alleviate or minimize the bad effect due to behavior of malicious nodes using the flooding search mechanism, the paper proposes a Markov-based evaluation model which exerts the trust and reputation mechanism to computing the level of trustworthy of nodes having the information requested by evaluation of the nodes＇ history behavior. Moreover, it can differentiate malicious nodes as early as possible for isolating and controlling the ones＇ message transmitted. The simulation results of the algorithm proposed show that it could effectively isolate malicious nodes, and hold back the transmission of vicious messages so that it could enhance tolerance of DDoS based on flooding in Guutella-like P2P network.

A PEER-TO-PEER INCENTIVE SCHEME FOR OVERCOMING FREE RIDING

Free riding has a great influence on the expandability,robustness and availability of Peer-to-Peer(P2P) network.Controlling free riding has become a hot research issue both in academic and industrial communities.An incentive scheme is proposed to overcoming free riding in P2P network in this paper.According to the behavior and function of nodes,the P2P network is abstracted to be a Distributed and Monitoring-based Hierarchical Structure Mechanism(DMHSM) model.A utility function based on several influencing factors is defined to determine the contribution of peers to the whole system.This paper also introduces reputation and permit mechanism into the scheme to guarantee the Quality of Service(QoS) and to reward or punish peers in the network.Finally,the simulation results verify the effectiveness and feasibility of this model.

Greedysearch based service location in P2P networks

A model is built to analyze the performance of service location based on greedy search in P2P networks. Hops and relative QoS index of the node found in a service location process are used to evaluate the performance as well as the probability of locating the top 5% nodes with highest QoS level. Both model and simulation results show that, the performance of greedy search based service location improves significantly with the increase of the average degree of the network. It is found that, if changes of both overlay topology and QoS level of nodes can be ignored during a location process, greedy-search based service location has high probability of finding the nodes with relatively high QoS in small number of hops in a big overlay network. Model extension under arbitrary network degree distribution is also studied.

Windows 10’s Browser Forensic Analysis for Tracing P2P Networks’Anonymous Attacks

A web browser is the most basic tool for accessing the internet from any of the machines/equipment.Recently,data breaches have been reported frequently from users who are concerned about their personal information,as well as threats from criminal actors.Giving loss of data and information to an innocent user comes under the jurisdiction of cyber-attack.These kinds of cyber-attacks are far more dangerous when it comes to the many types of devices employed in an internet of things(IoT)environment.Continuous surveillance of IoT devices and forensic tools are required to overcome the issues pertaining to secure data and assets.Peer to peer(P2P)applications have been utilized for criminal operations on the web.Therefore,it is a challenge for a forensic investigator to perform forensic analysis of the evolving hardware and software platforms for IoT.For identity concealment and privacy protection,the Onion Router(Tor)and Chrome with the Invisible Internet Project(I2P)as the foundation browser are often used.Confirmation is required to determine whether Tor is truly anonymous and private as they claim.Some people,on the other hand,utilize the Tor browser for evil reasons.Tools and techniques are available for the collection of artifacts,identifying problem areas,further processing and analysis of data on the computer and IoT.Present research tried to explore a few tools for the tracing of I2P activities over computer on windows 10 that reflects IoT devices.According to the results of this research,it leaves an excessive amount of important digital evidence on the operating system that can be exploited to attack the information of users.This research is based on windows operating system and does not support other operating systems.

A Scalable and Robust DHT Protocol for Structured P2P Network

Distributed Hash Tables (DHTs) were originated from the design of structured peer-to-peer (P2P) systems. A DHT provides a key-based lookup service similar to a hash table. In this paper, we present the detailed design of a new DHT protocol, Tambour. The novelty of the protocol is that it uses parallel lookup to reduce retrive latency and bounds communication overhead to a dynamically adjusted routing table. Tambour estimates the probabilities of routing entries' liveness based on statistics of node lifetime history and evicts dead entries after lookup failures. When the network is unstable, more routing entries will be evicted in a given period of time, and the routing tables will be getting smaller which minimize the number of timeouts for later lookup requests. An experimental prototype of Tambour has been simulated and compared against two popular DHT protocols. Results show that Tambour outperforms the compared systems in terms of bandwith cost, lookup latency and the overall efficiency.

Caching Scheme Based on Power-Law Characteristic in Unstructured P2P Networks

In order to reduce the traffic load and improve the availability of the shared resources in unstructured P2P networks, a caching scheme combining alternative index and adaptive replication （AIAR） is presented. AIAR uses random walk mechanism to disperse the caching information of resources in the network based on its power-law characteristic, and dynamically adjusts replicas according to the visit frequency on resources and the degree information of peers. Subsequent experimental results show that the proposed AIAR scheme is beneficial to improve the search performance of success rate and respond speed. In addition, compared to some existing caching scheme, AIAR can perform much better in success rate, especially in a dynamic environment.

An ALM Model for Streaming Media Service in P2P-SIP Network

Application layer multicast (ALM) has been widely applied in Internet, as a substitute for IP multicast. However, it causes network load to increase because it adopts unicast in data transmission, which limits the application. In this article, in order to improve the ALM performance in P2P-SIP network, an ALM model was proposed which reduced network load via merging messages in concast mode. Finally network simulations prove that this model has better benefit on single node load and average network load. Therefore, it is suitable for streaming media service in P2P-SIP Network.

A Novel Digital Rights Management Scheme in P2P Networks

P2P networking is a distributed application architecture that partitions tasks or workloads between peers. How to integrate P2P networks and DRM to offer a novel content distribution mode for digital media resources is a significant research project. In this paper, a novel DRM architecture in P2P Networks is proposed, three phases include content provide phase, content purchase phase and content access phase, are modeled, and key technologies are introduced. Finally analysis indicates that the proposed scheme has the characteristics of security, controllability and scalability.

基于P2P网络的大规模视频直播系统

介绍了一种基于P2P(peer-to-peer)网络的大规模视频直播系统Gridmedia.该系统采用Gossip协议构建无结构的应用层覆盖网络,每个节点可以独立地选择自己的伙伴节点.在覆盖网络上,每个节点通过一种推拉结合的流传输策略从邻居节点获取数据.与DONet中的纯拉策略相比,推拉结合策略大幅度减小了终端用户观看视频的延迟,并有效降低了直播系统的控制开销.PlanetLab上的大量实验充分表明了该策略的有效性.Gridmedia的原型系统通过300Kbps的视频码流对2005年春节联欢晚会进行了全球互联网直播.晚会期间,全球范围内有超过500000人次通过系统观看了直播,最高在线人数达到了15239人,充分验证了系统的性能.

用Small-World设计无组织P2P系统的路由算法

由于peer-to-peer系统在文件共享方面有着巨大的应用前景,peer-to-peer搜索问题已成为目前学术界重点的研究问题之一.对于缺乏缓存机制的无组织P2P系统,已有的分布式路由算法缺乏全局导航能力,属于无序搜索.为此,提出一种key clustering算法,将路由空间分为HUB和AUT两层,从全局角度进行有序搜索.为提高key clustering算法的可扩展性,借鉴Small-world领域的研究成果,在路由表中以一定概率插入连接远距离节点的快捷连接,以缩短平均路径长度.初步仿真实验表明,引入快捷连接的key clustering算法具有良好的搜索能力和扩展性.

P2P数据管理

P2P(peer-to-peer)技术是未来重构分布式体系结构的关键技术,拥有广阔的应用前景.P2P系统的大多数问题都可归结为数据放置和检索问题,因此,P2P数据管理成为数据库领域活跃的研究课题.当前,P2P数据管理主要有信息检索、数据库查询和连续查询3个子领域,取得了许多研究成果.在介绍P2P技术的优点后,指出了P2P数据管理研究的目标.然后针对上述3个方面,论述P2P数据管理研究的现状,着重讨论了P2P数据库查询的索引构造策略、语义异构的解决方法、查询语义、查询处理策略、查询类型和查询优化技术.通过比较,指出了现状与目标的差距,提出了需要进一步研究的问题.