Research on Multi-Agent Simulation of Epidemic News Spread Characteristics

The spread of news about an epidemic can easily lead to a social panic. In order to devise measures to control such a panic, it is necessary to consider characteristics of the spread of epidemic news, based on mechanisms at the individual level. In this paper, first, some features of multi-agent simulation are reviewed. Then a multi-agent simulation model of epidemic news spread (ENS) is designed and realized. Based on simulation experiments and sensitivity analyses, the influence of social relationships, the degree of trust in news of the epidemic, the epidemic spread intensity and the network structure of the epidemic news spread are studied. The research results include: (1) As the number of social relationships increases, the rate of spread of epidemic news rapidly rises, and the ratio of people who have heard the news directly decreases. The result is that the \'radiation effect\' of the epidemic news spread will be enhanced when the number of social relationships increases. (2) With the increase of the degree of trust in the news, the rate of spread of the news will also rapidly increase, but variation in the ratio of the people who have heard the news directly is not significant. This means that the \'radiation effect\' of the spread of the news does not change much more in relation to the degree of trust in the epidemic news. (3) The ratio of the people who have heard the news directly increases when the infection range increases (i.e. the spread intensity of epidemic increases), and vice versa. But the variation of the speed of the epidemic news spread is not significant. (4) When the network structure is assumed to be a small world network, the spread speed will be slower than that in a random network with the same average vertex degree and the forgetting speed will be faster than that in a random network with the same average vertex degree.Multi-Agent Simulation, News Spread, Small World Network , Epidemic

THE EFFECT OF TRUST ON INFORMATION DIFFUSION IN ONLINE SOCIAL NETWORKS

online social networks have a explosive growth in recent years and they provide a perfect platform for information diffusion. Many models have been given to explore the information diffusion procedure and its dynamics. But the trust relationship and memory effect are ignored. Based on the complex network theory, The information diffusion model is proposed and the network users, considered as agents, are classified into susceptible, infected and recovered individuals. The users’ behaviour rule and diffusion process are designed. The proposed agent-based model is tested by simulation experiments in four different complex networks: regular network, small world network, random network and scale-free network. Moreover, the effect of four immunization strategies are explored. The research results show that the influence of users’ trust relationship on different networks is varied, and the vertex weight priority immunization strategy is the best one in all four networks

Trust based attachment

In social systems subject to indirect reciprocity, a positive reputation is key for increasing one's likelihood of future positive interactions. The flow of gossip can amplify the impact of a person's actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation problem. To quantify this notion, we calculate the expected number of individuals, the "audience", who find out about a particular interaction. For a potential donor, a larger audience constitutes higher reputational stakes, and thus a higher incentive, to perform "good" actions in line with current social norms. For a receiver, a larger audience therefore increases the trust that the partner will be cooperative. This idea can be used for an algorithm that generates social networks, which we call trust based attachment (TBA). TBA produces graphs that share crucial quantitative properties with real-world networks, such as high clustering, small-world behavior, and power law degree distributions. We also show that TBA can be approximated by simple friend-of-friend routines based on triadic closure, which are known to be highly effective at generating realistic social network structures. Therefore, our work provides a new justification for triadic closure in social contexts based on notions of trust, gossip, and social information spread. These factors are thus identified as potential significant influences on how humans form social ties

Competition Between Homophily and Information Entropy Maximization in Social Networks

In social networks, it is conventionally thought that two individuals with more overlapped friends tend to establish a new friendship, which could be stated as homophily breeding new connections. While the recent hypothesis of maximum information entropy is presented as the possible origin of effective navigation in small-world networks. We find there exists a competition between information entropy maximization and homophily in local structure through both theoretical and experimental analysis. This competition means that a newly built relationship between two individuals with more common friends would lead to less information entropy gain for them. We conjecture that in the evolution of the social network, both of the two assumptions coexist. The rule of maximum information entropy produces weak ties in the network, while the law of homophily makes the network highly clustered locally and the individuals would obtain strong and trust ties. Our findings shed light on the social network modeling from a new perspective

CyberCraft: Protecting Electronic Systems with Lightweight Agents

The United States military is seeking new and innovative methods for securing and maintaining its computing and network resources locally and world-wide. This document presents a work-in-progress research thrust toward building a system capable of meeting many of the US military’s network security and sustainment requirements. The system is based on a Distributed Multi-Agent System (DMAS), that is secure, small, and scalable to the large networks found in the military. It relies on a staged agent architecture capable of dynamic configuration to support changing mission environments. These agents are combined into Hierarchical Peer-to-Peer (HP2P) networks to provide scalable solutions. They employ Public Key Infrastructure (PKI) communications (with digital signatures), and support trust chain management concepts. This document, a work-in-progress, presents the motivation and current challenges in choosing a network communications architecture capable of supporting one million or more agents in a DMAS

Predicting DDoS Attacks Preventively Using Darknet Time-Series Dataset

The cyber crimes in today’s world have been a major concern for network administrators. The number of DDoS attacks in the last few decades is increasing at the fastest pace. Hackers are attacking the network, small or large with this common attacks named as DDoS. The consequences of this attack are worse as it disrupts the service provider’s trust among its customers. This article employs machine learning methods to estimate short-term consequences on the number and dimension of hosts that an assault may target. KDD Cup 99, CIC IDS 2017 and CIC Darknet 2020 datasets are used for building a prediction model. The feature selection for prediction is based on KDD Cup 99 and CIC IDS 2017 dataset; CIC Darknet 2020 dataset is used for prediction of impact of DDoS attack by employing LSTM (Long Short Term Memory) algorithm. This model can help network administrators to identify and preventively predict the attacks within five minutes of the commencement of the potential attack

How Does Network Structure Impact Follow-on Financing through Syndication? Evidence from the Renewable Energy Industry

Venture capital (VC) is a critical source of finance for renewable energy ventures. Importantly, VC investments are made in rounds. In higher rounds: (1) the availability of capital drops—we find that less than 50% of renewable energy ventures receive “follow-on” financing—and (2) the rate at which VC firms co-invest increases—we find that 75% of “follow-on” investments are “syndicated”, co-investments. We argue that the way in which VC firms co-invest—in terms of how and to whom they are connected—is critical to understanding which projects are financed. Using data on 760 firm-deal observations, we examine how the VC firm’s direct ties (ego network) create trust (which we measure using the clustering coefficient) and improve access (structural holes) to important investment information. We consider too how the “small-world” nature of the global VC industry network (small-world quotient) improves “information reachability”. Finally, we consider the way in which these features interact with each other—specifically, when they can be substitutes and when they are complements—in explaining which projects do and do not receive follow-on financing through syndication. We conclude by reflecting on the implications of our findings for VC syndication and sustainable entrepreneurship in the renewable energy industry

The RAVE Network Attack

Cyber-attacks are an ever-present threat to our modern, technologically dependent world. This looming shadow of a disaster waiting to happen has led companies to invest heavily into their software resiliency and network defenses. However, many companies, especially small ones, have forgotten the danger of an insider threat, or at least how an insider threat could be emulated. Anything on the inside of a network automatically has a higher level of trust because most companies’ defenses have only gone as far as to protect their perimeter and educate their employees. What if an outside attacker was able to gain physical access for just a brief time to the inside of a small business? Say, in a waiting room or consultation? RAVE stands for Remote Attack Vector Engine, and is a device designed to test this flaw. RAVE is a small Raspberry Pi 0, disguised as any common workplace device, that an attacker can plant in a business’s network to attack from the inside. By connecting RAVE to an internal ethernet port, a secure reverse OpenVPN connection is automatically created to a Middleman Server over common HTTPS traffic through port 443 and kept persistent. An operator is then able to connect into RAVE through the Middleman Server. The operator can then use tools installed on the device to launch network scans, perform brute force password attacks on network devices and services, take over more devices on the network, and steal data from the company. By using this device, penetration testers can help companies develop better security practices to keep their network safe from infiltration and exploitation

Secure, Efficient and Privacy-aware Framework for Unstructured Peer-to-Peer Networks

Recently, the advances in Ubiquitous Computing networks and the increased computational power of network devices have led designers to create more flexible distributed network models using decentralised network management systems. Security, resilience and privacy issues within such distributed systems become more complicated while important tasks such as routing, service access and state management become increasingly challenging. Low-level protocols over ubiquitous decentralised systems, which provide autonomy to network nodes, have replaced the traditional client-server arrangements in centralised systems. Small World networks represent a model that addresses many existing challenges within Ubiquitous Computing networks. Therefore, it is imperative to study the properties of Small World networks to help understanding, modelling and improving the performance, usability and resiliency of Ubiquitous Computing networks. Using the network infrastructure and trusted relationships in the Small World networks, this work proposes a framework to enhance security, resilience and trust within scalable Peer-to-Peer (P2P) networks. The proposed framework consists of three major components namely network-aware topology construction, anonymous global communication using community trust, and efficient search and broadcasting based on granularity and pro-active membership management. We utilise the clustering co-efficient and conditional preferential attachment to propose a novel topology construction scheme that organises nodes into groups of trusted users to improve scalability. Network nodes communicate locally without advertising node identity at a global scale, which ensures user anonymity. The global communication is organised and facilitated by Service Centres to maintain security, privacy and integrity of member nodes. Service Centres are allocated using a novel leader election mechanism within unstructured scalable P2P networks. This allows providing fair and equitable access for existing and new nodes without having to make complex changes to the network topology. Moreover, the scale-free and clustering co-efficient characteristics of Small World networks help organising the network layout to maintain its balance in terms of the nodes distribution. Simulation results show that the proposed framework ensures better scalability and membership management in unstructured P2P networks, and improves the performance of the search and broadcasting in terms of the average shortest path and control overhead while maintaining user anonymity and system resiliency