A first-principles study has been performed to investigate the structural and electronic properties of theGaAs1-xBixsystem. The simulations are based upon the generalized gradient approximation (GGA) within the framework of density functional theory (DFT). Calculations are performed to different Bi concentrations. The lattice constant ofGaAs1-xBixincreases with Bi concentration while the alloy remains in the zinc-blende structure. The band gap ofGaAs1-xBixclearly shrinks with the Bi concentration. The optical transition of Bi dopant in GaAs exhibits a red shift. Besides, other important optical constants, such as the dielectric function, reflectivity, refractive index, and loss function also change significantly.

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.