Social Network Security Research Articles

Method of calculating of the information in social networks protection depending on the number of communities

A mathematical model (linear system of differential equations) was developed and a research of the model of personal data protection against the number of communities and the intensity of data transfer in social networks was conducted. The linear system of information protection in social networks in the mathematical sense of this term is considered. When described by linear models, the object should be linear, at least approximately. This approach makes it quite simple to consider mathematical models. If such a thing is not noticed, it is necessary to examine the security system for linearity. Such dependecies has been studied: the dependence of the amount of information flow in the social network on the components of information protection, the amount of personal data, and the speed of the data flow; the security of the system on the size of the system (as well as on the amount of personal data); information security threats on the number of communities, and also calculated: – coefficient representing the impact of information protection measures; – coefficient representing the impact of data leakage rate; – the coefficient representing the influence of the amount of data on its leakage; – the coefficient representing the influence of the system size on system security; – coefficient representing the impact of system security on data leakage; – the number of connections in the social networks; – number of vertices in the social networks; – the parameter can be used to configure the network partitioning algorithm. The solution has been obtained - the harmonic oscillator equation, which breaks down into three cases: pre-resonance zone, resonance zone and post-resonance zone. So, the impact of the parameters of the number of communities on the parameters of the social network security system was investigated. Such a study is useful and important from the point of view of information protection in the network, since the parameters of the number of communities has significant influence, up to 100%, per protection indicator. As the result of research, it was established that social network security systems are non-linear.

An Economic Analysis of Climate Change in Dry Lands of Maduri District, Tamil Nadu, India

The study was conducted in dry lands of Madurai district with a sample size of 150 to study the vulnerability, resilience and adaptation strategies to climate change and also to assess the sustainability of dry land farming and livelihood security of dry land farmers. The results revealed that Thirumangalam block was highly vulnerable to climate change with the index value of 0.689. In ecological sustainability, sorghum was more sustainable. Economic viability analyses showed that cotton was more sustainable The dependency on local inputs was higher for both cotton and sorghum with comparative higher usage of local inputs, such as labour, seed and Farm Yard Manure. Migration percentage was relatively high in dry land agro ecosystem due to low employment generation in this system. Thus, the resilience analysis showed that the migration has to be checked, savings has to be enhanced. Farm Yard Manure was the most important green technology adopted by the farmers with a proportion of 50.00 per cent. The livelihood security analyses that farmers in dry land system were much secure in habitat and social network security. Farmers’ perceived decline in yield was the most important impact of climate change and labour shortage was the most important constraint in adoption of climate resilient technologies. Policy implication suggested include suitable technological interventions should be given to sorghum farmers to make the crop more economically viable. Government should initiate agricultural development and welfare programmes for dryland farmers in the region.

User Perceptions of Privacy and Security in Online Social Networks

User Perceptions of Privacy and Security in Online Social Networks

Determining the degree of information security in social networks depending on the profile of connections between subscribers

Even before the emergence of social networks, it was found out what influence the people around him have on a person. At the same time, it was determined that very often the most useful for a person is not the close environment of the subject (strong ties), but people with whom the subject communicates "on the surface" (weak ties). Based on these conclusions, the question arises about the role of unfamiliar people in the life of an individual. People who are not part of a narrow cluster of close friends and acquaintances reveal useful information to the individual - information that the individual does not possess, due to the fact that with weak ties the subject of communication has fewer general contacts. At the same time, another problem arises - the problem of information security, which can be accessed by completely unknown people who are not part of the subject's close environment. To develop a methodology for assessing the security of information in social networks, a solution to the protection system in social networks was found, taking into account the effect of a specific parameter - the strength of connections between subscribers, to conduct a visual analysis of the system's behavior. In contrast to the classical approach, a linear mathematical model was created, the stationary position of the system was found, and the equation of a harmonic oscillator with decaying amplitude was obtained. The natural oscillation frequency, period and damping coefficient of the protection system are determined. It was concluded that, based on the conditions of the ratio of dissipation and the natural frequency of fluctuations of the quantity, the decay of the latter to a certain value is carried out periodically, with a decaying amplitude, or according to an exponentially decaying law. As a result of studies of the linear model of protection based on differential equations, it was established that the social network protection systems are non-linear. The need for further research of the non-linear model of the information protection system in social networks for the purpose of calculating the security of information, taking into account the type of connections between subscribers, has been determined.

Private Data Protection in Social Networks Based on Blockchain

With the rapid development of big data and social networks, user data in social networks are facing huge risks of privacy leakage. It is urgent to establish a complete and effective method for protecting private data in social networks. Based on the problem of information leakage in social networks, classifies user privacy data, and constructs different privacy data protection schemes through blockchain time stamp recording data storage, hash function anonymous operation of data, asymmetric encryption and digital signature of sending information. The blockchain-based privacy data protection method in social networks can effectively solve the privacy leakage problem in social networks, and provide a reference for the research in the field of information security and social network security. This paper designs a new blockchain-based privacy data protection scheme for different privacy disclosure categories, which provides a new solution to the current privacy disclosure problem in social networks. However, the existing methods will consume a lot of computational power in the process of information interaction. The subsequent research will optimize the computational power of blockchain and try to build a better blockchain social network privacy data protection system.

A social network security user recommendation algorithm based on community user emotions

A social network security user recommendation algorithm based on community user emotions

A comprehensive survey on online social networks security and privacy issues: Threats, machine learning‐based solutions, and open challenges

AbstractOver the past few years, online social networks (OSNs) have become an inseparable part of people's daily lives. Instead of being passive readers, people are now enjoying their role as content contributors. OSN has permitted its users to share their information including the multimedia content. OSN users can express themselves in virtual communities by providing their opinions and interacting with others. As a consequence, the privacy and security threats in OSNs have emerged as a major concern to the research and business world. In the recent past, a number of survey works have been conducted to discuss different security and privacy threats in OSNs. However, till date, no survey work has been conducted that aims to classify and analyze various machine learning (ML)‐based solutions adapted for the security defense of OSNs. In this survey article, we present a detailed taxonomy with a classification of various works done on various security attacks in OSNs. We then review and summarize the existing state of art survey works on OSN security, and indicate the merits and limitations of these survey works. Next, we review all recent works that aim to provide ML‐based solutions toward defense of security attacks on OSNs. Finally, we discuss the future road‐map on OSN security and provide a comprehensive analysis on the open research issues with feasible measurements and possible solutions.

Security Analysis of Social Network Topic Mining Using Big Data and Optimized Deep Convolutional Neural Network.

This research aims to conduct topic mining and data analysis of social network security using social network big data. At present, the main problem is that users' behavior on social networks may reveal their private data. The main contribution lies in the establishment of a network security topic detection model combining Convolutional Neural Network (CNN) and social network big data technology. Deep Convolution Neural Network (DCNN) is utilized to complete the analysis and search of social network security issues. The Long Short-Term Memory (LSTM) algorithm is used for the extraction of Weibo topic information in the memory wisdom. Experimental results show that the recognition accuracy of the constructed model can reach 96.17% after 120 iterations, which is at least 5.4% higher than other models. Additionally, the accuracy, recall, and F1 value of the intrusion detection model are 88.57%, 75.22%, and 72.05%, respectively. Compared with other algorithms, the model's accuracy, recall, and F1 value are at least 3.1% higher than other models. In addition, the training time and testing time of the improved DCNN network security detection model are stabilized at 65.86 s and 27.90 s, respectively. The prediction time of the improved DCNN network security detection model is significantly shortened compared with that of the models proposed by other scholars. The experimental conclusion is that the improved DCNN has the characteristics of lower delay under deep learning. The model shows good performance for network data security transmission.

Review on Social Media and Digital Security

The emerging social media with inherent capabilities seems to be gaining edge over comprehensiveness, diversity and wisdom, nevertheless its security and trustworthiness issues have also become increasingly serious, which need to be addressed urgently. The available studies mainly aim at both social media content and user security, including model, protocol, mechanism and algorithm. Unfortunately, there is a lack of investigating on effective and efficient evaluations and measurements for security and trustworthiness of various social media tools, platforms and applications, thus has effect on their further improvement and evolution. To address the challenge, this paper firstly made a survey on the state-of-the-art of social media networks security and trustworthiness particularly for the increasingly growing sophistication and variety of attacks as well as related intelligence applications. And then, we highlighted a new direction on evaluating and measuring those fundamental and underlying platforms, meanwhile proposing a hierarchical architecture for crowd evaluations based on signaling theory and crowd computing, which is essential for social media ecosystem. Finally, we conclude our work with several open issues and cutting-edge challenges.

Performance assessment of OppNet routing protocols with real world mobility traces

A new paradigm has been introduced by researchers in the field of data accessing at several mobile positions through implementation of WAN instead of cellular telephony. Based on range/coverage and network topology WAN taxonomy has been categorized as fixed network, mobile access network and ad – hoc network/wireless mesh networks respectively. Several interesting challenges has been posed by researchers in wireless networks such as routing, bandwidth, congestion, security, quality of service (QoS) and data rate enhancement. Of late, researchers around the world have started working in the domain of SHiP (Sparse, Hybrid, Intermittent and Partitioned) Network, which are plagued by several characteristics features such as: sporadic connections, intermittent routing, store – carry – forward type of message forwarding mechanism, dynamic network topology, transitive closure of message transmission, fluctuating network link, bottleneck probability, trust, and security in social networks. In this paper an outline of Oppnet (Opportunistic Network), part of SHiP Network has been presented with as in-depth coverage of routing problems and research challenges in it. Additionally, taxonomy of Oppnet routing protocols is illustrated with the features on basis of which categorization has been done. An exhaustive investigation through implementation of well-known routing schemes like: Epidemic, Spray and Wait, PROPHET and Direct delivery against mobility models such as: Random Walk, Random Waypoint, Shortest path-based movement and Cluster Movement has been accomplished in open-source software: ONE simulator with real world mobility dataset and traces of city of New Delhi, capital of India. Results achieved have been good and exceed our expectations.

Review on Social Media and Digital Security

The emerging social media with inherent capabilities seems to be gaining edge over comprehensiveness, diversity and wisdom, nevertheless its security and trustworthiness issues have also become increasingly serious, which need to be addressed urgently. The available studies mainly aim at both social media content and user security, including model, protocol, mechanism and algorithm. Unfortunately, there is a lack of investigating on effective and efficient evaluations and measurements for security and trustworthiness of various social media tools, platforms and applications, thus has effect on their further improvement and evolution. To address the challenge, this paper firstly made a survey on the state-of-the-art of social media networks security and trustworthiness particularly for the increasingly growing sophistication and variety of attacks as well as related intelligence applications. And then, we highlighted a new direction on evaluating and measuring those fundamental and underlying platforms, meanwhile proposing a hierarchical architecture for crowd evaluations based on signaling theory and crowd computing, which is essential for social media ecosystem. Finally, we conclude our work with several open issues and cutting-edge challenges.

Social network security using genetic algorithm

Social network security using genetic algorithm

A provably secure and lightweight mutual authentication protocol in fog-enabled social Internet of vehicles

The Internet of vehicles technology has developed rapidly in recent years and has become increasingly important. The social Internet of vehicles provides better resources and services for the development of the Internet of vehicles and provides better experience for users. However, there are still many security problems in social vehicle networking environments. Once the vehicle is networked, the biggest problem is data security according to the three levels of data collection, intelligent analysis, and decision control of the Internet of vehicles. Recently, Wu et al. proposed a lightweight vehicle social network security authentication protocol based on fog nodes. They claimed that their security authentication protocol could resist various attacks. However, we found that their authentication protocols are vulnerable to internal attacks, smart card theft attacks, and lack perfect forward security. In this study, we propose a new protocol to overcome these limitations. Finally, security and performance analyses show that our protocol perfectly overcomes these limitations and exhibits excellent performance and efficiency.

Study of Awareness about Peer to Peer Security in Social Networks

In the present world, utilising Social media usage has grown at a phenomenal rate. The social network platforms such as Instagram, Facebook, WhatsApp, Twitter and many more provide services and facilitate peer-to-peer communication through chat, audio/video conferencing, and data sharing in a variety of formats. Using these platforms for their communication has become easier to communicate and adapt whereas the scams behind these underlying networks is unknown. As a potential case of zero trust, peer-to-peer technologies assert that they will support end-to-end communication while demanding access control, negligibility, and adaptability against suppression and enormous data breaches caused by abused trust.. This paper gives the survey of about how the security, confidentiality in social networks are prone to be in the first level. Second, how clueless people are of this demanding use of applications and analysis of the survey and the (P2P) technologies and its framework. Finally it gives a comprehensive examination of the frameworks, applications, and architectures for P2P-based online social networks.

Real Time Profile Analysis and Fake Detection Model for Improved Profile Security in Online Social Networks

Real Time Profile Analysis and Fake Detection Model for Improved Profile Security in Online Social Networks

Social Networking Security during COVID-19: A Systematic Literature Review

During the Covid-19 Pandemic, the usage of social media networks increased exponentially. People engage in education, business, shopping, and other social activities (i.e., Twitter, Facebook, WhatsApp, Instagram, YouTube). As social networking expands rapidly, its positive and negative impacts affect human health. All this leads to social crimes and illegal activities like phishing, hacking, ransomware, password attacks, spyware, blackmailing, Middle-man-attack. This research extensively discusses the social networking threats, challenges, online surveys, and future effects. We conduct an online survey using the google forms platform to collect the responses of social networking sites (SNS) users within Pakistan to show how SNS affects health positively and negatively. According to the collected response, we analyzed that 50% of the users use SNS for education purposes, 17.5% use it for shopping purposes, 58.2% use it for entertainment, 37.1% use it for communication, and 9.8% use it for other purposes. According to the response, the excessive use of SNS affects the health that 9.8% users face the physical threat, 42.8% user faces mental health issues due to excessive or inappropriate use of SN, and 50.5% users feel moral threat using Social sites. Finally, we conclude our paper by discussing the open challenges, conclusions, and future directions.

Social Network and Data Security Issues

Computer security is a branch of technology known as Information Security, as it is applied to computers and networks. The objective of computer security involves the protection of information and property from theft and corruption, or natural disasters, while information and property can remain productive and accessible to their intended users. Computer system security terminology means the collective processes and mechanisms through which information, sensitive and valuable services are protected from dissemination, and tampering with or collapsing caused by unauthorized or unreliable activities, and unplanned events, respectively to solve the problems of information security on the social network website. We have to learn about the basic concept and structure of the social network website and its associated social network. The social network of services in the Internet zone usually refers to: social network service, social networking programs and social network website. Clearly, these three things are interlinked and indispensable; they are combined to form a platform for users to communicate information.

Devising a procedure to determine the level of informational space security in social networks considering interrelations among users

+ Linear and dynamic models of the system of information security in social networks, taking into consideration the relationships between users, were studied and the resistance of the security system was analyzed. There is a practical interest in studying dependence of the behavior of the system of social network security on the parameters of users’ interaction. Dynamic systems of information security in social networks in the mathematical sense of this term were considered. A dynamic system refers to any object or process, for which the concept of state as a totality of certain magnitudes at a given time is unambiguously defined and the law that describes a change (evolution) of the initial state over time was assigned. The network of social interactions consists of a totality of social users and a totality of the relations between them. Individuals, social groups, organizations, cities, countries can act as users. Relations imply not only communication interactions between users but also relations of the exchange of various resources and activities, including conflict relations. As a result of research, it was found that the security systems of a social network are nonlinear. Theoretical study of the dynamic behavior of an actual object requires the creation of its mathematical model. The procedure for developing a model is to compile mathematical equations based on physical laws. These laws are stated in the language of differential equations. Phase portraits of the data security system in the MATLAB/Multisim program, which indicate the stability of a security system in the working range of parameters even at the maximum value of the impacts, were determined. Thus, the influence of users’ interaction parameters on the parameters of the system of social network security was explored. Such study is useful and important in terms of information security in the network, since the parameters of users’ interaction significantly affect, up to 100 %, the security indicator.

Лингвобезопасность: антивакцинаторский медиадискурс в контексте аксиологических мировоззренческих трасформаций

We consider the impact of anti-vaccination movement and its substantial value attitudes on social networks users in the context of the COVID-19 pandemic. The study is conducted on the materials of the social networks VKontakte, Odnoklassniki, Telegram. In total, 2700 publications are analyzed by the method of communicative content analysis through the modeling of quantitative and qualitative data from March 12, 2020 (the beginning of pandemic) to December 31, 2021. When systematizing the results, a general scientific descriptive method is used. Four discursive practices of the anti-vaccination media discourse have been identified, directing users of social networks to perceive a certain aspect of vaccination and suggesting different justification of vaccination resistance strategies. In each discursive practice, the main topics of fake messages are presented, and argumentative models of anti-vaccinators in media texts are also noted. The problem of evaluation and interpretation of facts in the modern media discourse is considered. According to the results of study, the characteristic features of the formed “digital guerrilla media discourse” are formulated, the tools of linguistic security in social networks are designated. In order to protect public health, it is proposed to form programs for the training of new highly specialized professionals, such as “infodemiologist”, where information and biological aspects of public health will be equally taken into account.

РАДИКАЛЬНЫЙ ФЕМИННЫЙ И МАСКУЛИННЫЙ МЕДИАДИСКУРС В АСПЕКТЕ ЛИНГВОБЕЗОПАСНОСТИ

This article examines the impact of radical gender media discourse and its substantive value attitudes on social media users. The main criterion is determined for classifying these discourses as being radical, as the manifestation of hatred as an underlying principle. The authors outline the reasons for the radicalization of the feminine and masculine media discourse. Each media discourse contains an axiological trust matrix, with the help of which the audience is captured and new users are involved, the archetypal models being used are analyzed. In total, 1,700 publications on the social network Vkontakte have been analyzed using the method of communicative content analysis through modeling quan-titative and qualitative data from January 01, 2020 to January 01, 2022. The article identifies the sub-discourses cov-ering the main semantic zones of radical feminists and masculists' media discourse in the Russian segment of the Inter-net and assuming a different explanation of the strategies to resist the oppression of women and men. Each sub-discourse presents the main thematic dominants. The threats in the radical feminine and masculine media discourse aimed at the destruction of the family and parenthood as social institutions are considered separately. The ways are outlined designed to cause rejection and hostility to the concept of «child» in the childhate sub-discourse. According to the authors of the study, the norm of modern masculinity and femininity, formed in new media, crystallized in the im-ages of the «digital troll man» and the «new Amazon»; they also describe the tools of linguistic security in social net-works.