Social network security: Issues, challenges, threats, and solutions

Rathore, Shailendra; Sharma, Pradip Kumar; Loia, Vincenzo; Jeong, Young Sik; Park, Jong Hyuk

doi:10.1016/j.ins.2017.08.063

Cited by 213 publications

(143 citation statements)

References 47 publications

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“…The semi-supervised model solves these problems to a large extent. It is successfully used to detect the Internet of Things (IoT) distributed attack [12] and plays a significant role in maintaining social network security [13].…”

Section: Related Workmentioning

confidence: 99%

Multiple Interactive Attention Networks for Aspect-Based Sentiment Classification

Zhang

Zhu

et al. 2020

Applied Sciences

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Aspect-Based (also known as aspect-level) Sentiment Classification (ABSC) aims at determining the sentimental tendency of a particular target in a sentence. With the successful application of the attention network in multiple fields, attention-based ABSC has aroused great interest. However, most of the previous methods are difficult to parallelize, insufficiently obtain, and fuse the interactive information. In this paper, we proposed a Multiple Interactive Attention Network (MIN). First, we used the Bidirectional Encoder Representations from Transformers (BERT) model to pre-process the data. Then, we used the partial transformer to obtain a hidden state in parallel. Finally, we took the target word and the context word as the core to obtain and fuse the interactive information. Experimental results on the different datasets showed that our model was much more effective.Appl. Sci. 2020, 10, 2052 2 of 15 words [7]. However, these models simply average the aspect or context vector to guide learning the attention weight on the context or aspect words. Therefore, these models are still in the preliminary stage in dealing with fine-grained sentiment analysis.In conclusion, there are two problems with previous approaches. The first problem is that previous approaches are difficult to obtain the hidden state interactively in parallel. Another problem is to insufficiently obtain and fuse contextual information and aspect information.This paper proposed a model named Multiple Interactive Attention Network (MIN) to address these problems. To address the first problem, we took advantage of Multi-Head Attention (MHA) to obtain useful interactive information. To address another problem, we adopted target-context pair and Context-Target-Interaction (CTI) in our model.The main contributions of this paper are presented as follows:1.We took advantage of MHA and Location-Point-Wise Feed-Forward Networks (LPFFN) to obtain the hidden state interactively in parallel. Besides, we applied pre-trained Bidirectional Encoder Representations from Transformers (BERT) [8] in our model. 2.We used the CTI and target-context pair to help us obtain and fuse useful information. We also verified the effectiveness of these two methods. 3.We experimented on different public authoritative datasets: restaurant reviews and laptop reviews of the SemEval-2014 Task 4 dataset, the ACL(Annual Meeting of the Association for Computational Linguistics) 14 Twitter dataset, SemEval-2015 Task 12 dataset, SemEval-2016 Task 5 dataset. The experimental results showed our model outperformed state-of-the-art methods.

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Section: Related Workmentioning

confidence: 99%

Multiple Interactive Attention Networks for Aspect-Based Sentiment Classification

Zhang

Zhu

et al. 2020

Applied Sciences

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“…According to the source [34], threats existing at the social networking level are shared in :  threats to media content (common exposure and manipulation of shared multimedia content, use of steganography, transmission of metadata, links to multimedia content, static links, labeling, etc.) ;  traditional threats (phishing, malware, spam, etc);  social threats (harassment on the Internet through repeated sending of messages, espionage).…”

Section: Securitymentioning

confidence: 99%

Integration of Emerging Technologies into Social Networks

Baltoi¹

2020

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Social networks provide solutions to more and more everyday needs of people. Appearing as a solution to people's need to communicate through technology, they have developed and integrated more and more features. In this paper a qualitative research based on the study of the existing articles is carried out. Thus, a series of statistical data on the impact and penetration of the Internet and social networks within society will be presented, and some of the benefits that social networks offer to people or businesses and a series of various functionalities and emerging technologies that presents a particular interest for future development, having the capacity to innovate in this field; electronic payments and emerging technologies such as artificial intelligence, Internet of Things devices or biometric technology to increase security.

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“…Currently, social networking services (SNS) are not only a mass media, but are also used by users (actors) to unite like-minded people in virtual communities, to express civic position, to coordinate real-life actions and, as a consequence, to influence political and social processes in the state. The global and Ukrainian experience of using SNS by citizens for selforganization in alarming situations and during resonant events has shown that they are an effective tool for influencing public opinion, mobilizing citizens and strengthening protest sentiment in society [1][2][3][4][5]. Such phenomena have become possible due to the high degree of actor's confidence in SNS information compared with the traditional media.…”

Section: Introductionmentioning

confidence: 99%

The conceptual model of information confrontation of virtual communities in social networking services

Молодецька¹,

Tymonin²,

Melnychuk³

2020

IJECE

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Social networking services are one of the most popular mass media and are used as an effective tool for information confrontation due to their functional characteristics. Existing models of information confrontation take into account the redistribution between conflict parties of only one kind of resource, although in the social networking services there is a need to consider additional factors that determine the effectiveness of virtual communities' opposition. A conceptual model of information confrontation of virtual communities in social networking services has been developed, and it includes three-layer dynamics of the number of actors, growth of information resources of virtual communities and dynamics of spending resources for the confrontation conduct. The model also takes into account the peculiarities of the antagonistic conflict of virtual communities' actors through the choice of a differential equation that corresponds to the type of its dynamics. The offered conceptual model formalizes the behavior of virtual communities' actors in the conditions of antagonistic conflict. At the same time, it allows to investigate the peculiarities of using different strategies to carry out the information fight of virtual communities in social networking services, to choose optimal strategies, to predict the development of conflicts in the information space and to develop effective measures to counter threats to the state's information security.

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Social network security: Issues, challenges, threats, and solutions

Cited by 213 publications

References 47 publications

Multiple Interactive Attention Networks for Aspect-Based Sentiment Classification

Multiple Interactive Attention Networks for Aspect-Based Sentiment Classification

Integration of Emerging Technologies into Social Networks

The conceptual model of information confrontation of virtual communities in social networking services

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