The Dynamically Modified BoW Algorithm Used in Assessing Clicks in Online Ads

Gabryel, Marcin; Przybyszewski, Krzysztof

doi:10.1007/978-3-030-20915-5_32

Cited by 6 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, Meghanath et al [28] proposed a new contextual outlier detection technology (ConOut) and applied it to the advertising domain to identify fraudulent publishers. Besides, the work in [30] presents Bag-of-Words algorithm to assess clicks in online advertising system, which is based on the concept of text search methods. However, the outlier detection technology in [28] and the Bag-of-Words algorithm in [30] involve users' real username and address of the visitor, which reveals user's identity privacy.…”

Section: Statistical Analysis-based Schemesmentioning

confidence: 99%

“…Besides, the work in [30] presents Bag-of-Words algorithm to assess clicks in online advertising system, which is based on the concept of text search methods. However, the outlier detection technology in [28] and the Bag-of-Words algorithm in [30] involve users' real username and address of the visitor, which reveals user's identity privacy.…”

Section: Statistical Analysis-based Schemesmentioning

confidence: 99%

“…However, the dataset used for training is easy to be mixed with fraudulent clicks in these schemes, causing the process of training a model to be susceptible to adversarial attack [23]. ence, statistical analysis-based schemes [1,10,[24][25][26][27][28][29][30][31][32] aim to mitigate the adversarial attacks. For instance, the schemes in [10,25] predict malicious crowdsourcing platforms by clustering algorithms.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

BCFDPS: A Blockchain-Based Click Fraud Detection and Prevention Scheme for Online Advertising

Lyu

Zhou

et al. 2022

Security and Communication Networks

View full text Add to dashboard Cite

Online advertising, which depends on consumers’ click, creates revenue for media sites, publishers, and advertisers. However, click fraud by criminals, i.e., the ad is clicked either by malicious machines or hiring people, threatens this advertising system. To solve the problem, many schemes are proposed which are mainly based on machine learning or statistical analysis. Although these schemes mitigate the problem of click fraud, several problems still exist. For example, some fraudulent clicks are still in the wild since their schemes only discover the fraudulent clicks with a probability approaching but not 100%. Also, the process of detecting a click fraud is executed by a single publisher, which makes a chance for the publisher to obtain illegal income by deceiving advertisers and media sites. Besides, the identity privacy of consumers is also exposed because the schemes deal with the plain text of consumers’ real identity. Therefore, in this paper, a blockchain-based click fraud detection and prevention scheme (BCFDPS) for online advertising is proposed to deal with the above problems. Specifically, the BCFDPS mainly introduces bilinear pairing to implicitly verify whether a consumer’s real digital identity is contained in a click message to significantly avoid click fraud and employs a consortium blockchain to ensure the transparency of the detection and prevention process. In our scheme, the clicks by machines or fraud ones by a human can be accurately detected and prevented by media sites, publishers, and advertisers. Furthermore, ciphertext-policy attribute-based encryption is adopted to protect the identity privacy of consumers. The implementation and evaluation results show that compared with the existing click fraud detection and prevention schemes based on machine learning and statistical analysis, BCFDPS achieves detection of each fraudulent click with a probability of 100% and consumes lower computation cost; furthermore, BCFDPS adds functions of consumers’ privacy protection and click fraud detection and prevention, compared to the existing blockchain-based online advertising scheme, by introducing limited communication cost ( 4,984 bytes) at lower storage cost.

show abstract