New advances in securing cyberspace and curbing crowdturfing

Li, Gang; Niu, Wenjia; Batten, Lynn Margaret; Liu, Jiqiang

doi:10.1002/cpe.4162

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…In sum, most current work on cyber deception has characterized the network of actors who participate into the business, as well as developed technical methods of detecting the attacks after they have been executed (i.e., after the fact). However, the pre-kinetic events of the phenomenon have received less attention, and thus approaches that focus on the motivational and behavioral aspects of the problem have been called for [51]. In addition, prior work has examined the types of services offered by black-hat marketplaces [41], [52] but thus far, little attention has been given to how the crowd workers justify their involvement in taking part in deceptive work on behalf of the deceiver.…”

Section: Introductionmentioning

confidence: 99%

“This Is the Future of Advertising!” Or Is It? New Insights into the Justifiability of Deceptive Crowdwork in Cyberspace

Kauppila¹,

Soliman²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Unlike classical forms of deception where the deceiver deceives their victims directly, the crowdsourcing of cyber deception provides a powerful and cost-effective mechanism for deceivers to create and spread falsehood from the shadows. But for a mass deception campaign to be effective, the crowdworkers must rationalize (and willingly accept) their role in the deceptive act. What, then, could justify participation in a mass-deception campaign? To answer this question, we adopt the qualitative vignette approach and utilize neutralization theory as our guiding lens. Our results point to several neutralization techniques that crowdworkers could invoke to convincingly rationalize involvement in a cyber deception campaign. Importantly, the findings shed new light on a growing pessimism about work ethics in cyberspace which may lead some ordinary people into joining deception campaigns, believing it to be the future of advertising. We discuss the theoretical and practical implications of these novel insights. Background: the evolution of deceptionDeception is not a novel concern, and scholars have studied this behavior from various fields, including

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Section: Introductionmentioning

confidence: 99%

“This Is the Future of Advertising!” Or Is It? New Insights into the Justifiability of Deceptive Crowdwork in Cyberspace

Kauppila¹,

Soliman²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…More specifically, a set of paid posters can cooperate with good marketing to produce the expected results of positive or negative opinions to attract attention or stimulate curiosity. However, how to use social media to sell better still remains to be considered [4]. Modern malware uses advanced techniques to hide static and dynamic analysis tools.…”

Section: Introductionmentioning

confidence: 99%

The System of the Dissemination Characteristics of Internet Public Opinion Big Data Based on Artificial Intelligence

Liu

2022

Wireless Communications and Mobile Computing

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In the era we live in today, the network is often used to analyze a large number of complex systems. With the development of the information society, there are more and more ways to disseminate public information through social networks. Public opinion dissemination refers to the process of disseminating public opinion information through social networks. Because the dissemination of public opinion is the basis for the exchange of ideas among multiple communicators of public opinion, the network community will certainly have an impact on the dissemination and development of public opinion. This article is based on artificial intelligence to study the network public opinion big data dissemination characteristic analysis system, introduces the network public opinion analysis system based on the characteristics of the network public opinion, introduces in detail multiple methods and clustering algorithms for extracting the text information of Internet public opinion, and proposes the Kmeans + Canopy + semantic similarity algorithm, and uses the A event to compare the parameters of the network clustering coefficient, the correlation measure and the degree centrality measure, and the performance of the Kmeans + Canopy algorithm and the Kmeans + Canopy + semantic similarity algorithm. The results of the experiment found that the clustering coefficient of “People’s Daily” in the network dissemination of A event was 0.038, which was the highest among all nodes. It shows that 3.8% of the nodes established by the “People’s Daily” can interact one-to-one to deliver information and intelligence resources. Although the complexity of the algorithm has increased and the time consumed by the system has increased, the accuracy of clustering has been improved, especially for cultural articles, the accuracy rate has been as high as 75%, and entertainment articles can reach up to 70%, and stabilize at around 70%.

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Unethical but not illegal! A critical look at two-sided disinformation platforms: Justifications, critique, and a way forward

Soliman

Rinta-Kahila²

2023

Journal of Information Technology

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Crowdsourced disinformation represents a two-sided-market model wherein a platform organizer orchestrates the interaction between disinformation requesters and crowdworkers for a fee. Academic research and industry reports demonstrate that the disinformation business is thriving and that its consequences can be severe; however, research on this topic has focused mainly on developing technical methods to detect disinformation, while leaving the social aspects of the phenomenon unaddressed. In particular, very little is known about the discursive tactics that platforms apply to justify disinformation-service offerings such that these appear acceptable to potential customers. Taking a critical approach to the topic, the paper examines how platform organizers justify their disinformation services and to what extent the justifications given are valid. These questions are addressed via a unique dataset from 10 crowdsourcing platforms specializing in social-media-based reputation management. Drawing on the lens of accounts, the analysis suggests that these platforms employ six means of justification for persuasion purposes: the “claim of entitlement,” “defense of the necessity,” the “claim of ubiquity,” “language sanitization,” “appeal to professionalism,” and “appeal to codified rules.” Critical discourse analysis scrutinizing these accounts against the validity claims of comprehensibility, truth, sincerity, and legitimacy indicates that they cannot be considered valid. The paper discusses the implications of the findings and offers several recommendations designed for improving the status quo.

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New advances in securing cyberspace and curbing crowdturfing

Cited by 3 publications

References 4 publications

“This Is the Future of Advertising!” Or Is It? New Insights into the Justifiability of Deceptive Crowdwork in Cyberspace

“This Is the Future of Advertising!” Or Is It? New Insights into the Justifiability of Deceptive Crowdwork in Cyberspace

The System of the Dissemination Characteristics of Internet Public Opinion Big Data Based on Artificial Intelligence

Unethical but not illegal! A critical look at two-sided disinformation platforms: Justifications, critique, and a way forward

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