A Propagation Model for Social Engineering Botnets in Social Networks

2011 ◽  
Author(s):  
Shuhao Li ◽  
Xiaochun Yun ◽  
Zhiyu Hao ◽  
Xiang Cui ◽  
Yipeng Wang
Keyword(s):  
Social Networks ◽  
Social Engineering ◽  
Propagation Model

scholarly journals A Bio-Inspired Defensive Rumor Confinement Strategy in Online Social Networks

2021 ◽  
Vol 33 (1) ◽  
pp. 47-70
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L. D.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Propagation Model ◽  
Information Propagation ◽  
Control Approach ◽  
Rumor Propagation ◽  
Immunization Strategies ◽  
New Information ◽  
The Individual ◽  
Rumor Control

Online social networks (OSNs) are used to connect people and propagate information around the globe. Along with information propagation, rumors also penetrate across the OSNs in a massive order. Controlling the rumor propagation is utmost important to reduce the damage it causes to society. Educating the individual participants of OSNs is one of the effective ways to control the rumor faster. To educate people in OSNs, this paper proposes a defensive rumor control approach that spreads anti-rumors by the inspiration from the immunization strategies of social insects. In this approach, a new information propagation model is defined to study the defensive nature of true information against rumors. Then, an anti-rumor propagation method with a set of influential spreaders is employed to defend against the rumor. The proposed approach is compared with the existing rumor containment approaches and the results indicate that the proposed approach works well in controlling the rumors.

Freedom of Expression and the Right to Privacy and Ethics in Dialectic of Human Rights in This Complex and Turbulent Society

2021 ◽  
Vol 9 (2) ◽  
pp. 1-28
Author(s):  
José Poças Rascão ◽  
Nuno Gonçalo Poças
Keyword(s):  
Social Networks ◽  
Human Rights ◽  
Online Social Networks ◽  
Freedom Of Expression ◽  
Technological Development ◽  
Social Engineering ◽  
Digital Data ◽  
Right To Privacy ◽  
The Right To Privacy ◽  
The Right

The article is about human rights freedom of expression, the right to privacy, and ethics. Technological development (internet and social networks) emphasizes the issue of dialectics and poses many challenges. It makes the theoretical review, the history of human rights through and reference documents, an analysis of the concepts of freedom, privacy, and ethics. The internet and social networks pose many problems: digital data, people's tracks, the surveillance of citizens, the social engineering of power, online social networks, e-commerce, spaces of trust, and conflict.

Modelling multi-topic information propagation in online social networks based on resource competition

2016 ◽  
Vol 43 (3) ◽  
pp. 342-355 ◽  
Author(s):  
Liyuan Sun ◽  
Yadong Zhou ◽  
Xiaohong Guan
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Online Social Networks ◽  
Resource Competition ◽  
Propagation Model ◽  
Small Scale ◽  
Model Parameters ◽  
Information Propagation ◽  
Practical Applications ◽  
The Impact

Understanding information propagation in online social networks is important in many practical applications and is of great interest to many researchers. The challenge with the existing propagation models lies in the requirement of complete network structure, topic-dependent model parameters and topic isolated spread assumption, etc. In this paper, we study the characteristics of multi-topic information propagation based on the data collected from Sina Weibo, one of the most popular microblogging services in China. We find that the daily total amount of user resources is finite and users’ attention transfers from one topic to another. This shows evidence on the competitions between multiple dynamical topics. According to these empirical observations, we develop a competition-based multi-topic information propagation model without social network structure. This model is built based on general mechanisms of resource competitions, i.e. attracting and distracting users’ attention, and considers the interactions of multiple topics. Simulation results show that the model can effectively produce topics with temporal popularity similar to the real data. The impact of model parameters is also analysed. It is found that topic arrival rate reflects the strength of competitions, and topic fitness is significant in modelling the small scale topic propagation.

scholarly journals Elements of Social Engineering Methodology Used During the COVID-19 Pandemic

2021 ◽  
pp. 5-18
Author(s):  
Oleksandr Trukhachov
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Theoretical Study ◽  
Social Engineering ◽  
The Political ◽  
Traditional Media ◽  
Opinion Change ◽  
Political Landscape ◽  
History Of ◽  
Scientific Phenomenon

The article focuses on elements of social engineering (SI) that could be used by the states in their own interests during the COVID-19 pandemic. These elements were used to form negative public opinion, change the political landscape, and reduce citizens’ trust in their own governments. These elements are influence and persuasion. Traditional media and social networks play a major role in the use of these SI elements. SI has a long history of theoretical study as a scientific phenomenon. Practical elements of SI have a large arsenal, from government tools to influencing individuals. The article aims to demonstrate using SI elements, influence, and persuasion by the interested states and governments to obtain certain preferences for both foreign and domestic policies.

scholarly journals The Social Cloud for Public eResearch

2021 ◽  
Author(s):  
◽  
Koshy John
Keyword(s):  
Social Networks ◽  
Cloud Computing ◽  
Computational Models ◽  
Social Engineering ◽  
Functional System ◽  
Distributed Computation ◽  
Computational Time ◽  
The Novel ◽  
The Social ◽  
Social Cloud

<p>Scientific researchers faced with extremely large computations or the requirement of storing vast quantities of data have come to rely on distributed computational models like grid and cloud computing. However, distributed computation is typically complex and expensive. The Social Cloud for Public eResearch aims to provide researchers with a platform to exploit social networks to reach out to users who would otherwise be unlikely to donate computational time for scientific and other research oriented projects. This thesis explores the motivations of users to contribute computational time and examines the various ways these motivations can be catered to through established social networks. We specifically look at integrating Facebook and BOINC, and discuss the architecture of the functional system and the novel social engineering algorithms that power it.</p>

scholarly journals Key Node Discovery Algorithm Based on Multiple Relationships and Multiple Features in Social Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xianyong Li ◽  
Ying Tang ◽  
Yajun Du ◽  
Yanjie Li
Keyword(s):  
Social Networks ◽  
Propagation Model ◽  
Multiple Relationships ◽  
Information Propagation ◽  
Multiple Features ◽  
Relational Networks ◽  
Discovery Algorithms ◽  
Relational Network ◽  
Single Relation ◽  
Key Nodes

The key nodes play important roles in the processes of information propagation and opinion evolution in social networks. Previous work rarely considered multiple relationships and features into key node discovery algorithms at the same time. Based on the relational networks including the forwarding network, replying network, and mentioning network in a social network, this paper first proposes an algorithm of the overlapping user relational network to extract different relational networks with same nodes. Integrated with these relational networks, a multirelationship network is established. Subsequently, a key node discovery (KND) algorithm is presented on the basis of the shortest path, degree centrality, and random walk features in the multirelationship network. The advantages of the proposed KND algorithm are proved by the SIR propagation model and the normalized discounted cumulative gain on the multirelationship networks and single-relation networks. The experiment’s results show that the proposed KND method for finding the key nodes is superior to other baseline methods on different networks.

scholarly journals The Social Cloud for Public eResearch

2021 ◽  
Author(s):  
◽  
Koshy John
Keyword(s):  
Social Networks ◽  
Cloud Computing ◽  
Computational Models ◽  
Social Engineering ◽  
Functional System ◽  
Distributed Computation ◽  
Computational Time ◽  
The Novel ◽  
The Social ◽  
Social Cloud

<p>Scientific researchers faced with extremely large computations or the requirement of storing vast quantities of data have come to rely on distributed computational models like grid and cloud computing. However, distributed computation is typically complex and expensive. The Social Cloud for Public eResearch aims to provide researchers with a platform to exploit social networks to reach out to users who would otherwise be unlikely to donate computational time for scientific and other research oriented projects. This thesis explores the motivations of users to contribute computational time and examines the various ways these motivations can be catered to through established social networks. We specifically look at integrating Facebook and BOINC, and discuss the architecture of the functional system and the novel social engineering algorithms that power it.</p>

scholarly journals DR-SCIR Public Opinion Propagation Model with Direct Immunity and Social Reinforcement Effect

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 584 ◽  
Author(s):  
Weidong Li ◽  
Tianyi Guo ◽  
Yunming Wang ◽  
Bo Chen
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Propagation Model ◽  
Social Reinforcement ◽  
Reinforcement Effect ◽  
Factor B ◽  
Effect Factor ◽  
The Public ◽  
Simulation Results ◽  
First Time

The DR-SCIR network public opinion propagation model was employed to study the characters of S-state users stopping transmitting information for the first time and secondary transmission of immune users. The model takes into account symmetry and complexity such as direct immunization and social reinforcement effect, proposes the probability of direct immunity Psr and the probability of transform from the immune state to the hesitant state Prc, and divides public opinion information into positive public opinion and negative public opinion based on whether the public opinion information is confirmed. Simulation results show that, when direct immunity Psr = 0.5, the density of I-state nodes in the model decreased by 54.12% at the peak index; when the positive social reinforcement effect factor b = 10, the density of I-state nodes in the model increased by 16.67% at the peak index; and when the negative social reinforcement effect factor b = -10, the density of I-state nodes in the model decreased by 55.36% at the peak index. It shows that increasing the positive social reinforcement effect factor b can promote the spread of positive public opinion, reducing the negative social reinforcement effect factor b can control the spread of negative public opinion, and direct immunization can effectively suppress the spread of public opinion. This model can help us better analyze the rules of public opinion on social networks, so as to maintain a healthy and harmonious network and social environment.

scholarly journals SETQR Propagation Model for Social Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 127533-127543 ◽  
Author(s):  
Yuexia Zhang ◽  
Ziyang Chen
Keyword(s):  
Social Networks ◽  
Propagation Model
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