Course:LIBR559A/Wei, G., Shao, J., Xiang, Y., Zhu, P., & Lu, R. (2015)

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Citation

Wei, G., Shao, J., Xiang, Y., Zhu, P., & Lu, R. (2015). Obtain confidentiality or/and authenticity in big data by ID-based generalized signcryption. Information Sciences, 318, 111-122. doi:10.1016/j.ins.2014.05.034

Annotation

The purpose of Wei, Shao, Xiang and et al.'s article is to offer a new security solution to big data through an ID-based generalized signcription. Big Data is useful in order to mine information, but there are concerns regarding how that information is mined and if the information is fake. To mitigate these concerns, security solutions like encryption and signatures are used. Wei, Shao, and et al.'s (2015) main concern about current solutions in “Obtain confidentiality or/and authenticity in big data by ID-based generalized signcription” is, “In general, to achieve the authenticity and confidentiality alone, the basic tools are signature and encryption, respectively. While to achieve the both properties together, the traditional approach of either ‘‘signature-then-encryption’’ or ‘‘encryption-then-signature’’ will be applied. However, this kind of traditional approach incurs high computational cost and communication overhead” (pg.111). They desire a new security model based on existing generalized signcription technology because it would be more efficient (Wei, Shao, Xiang and et al, 2015, pg.112). Their goal is to obtain an identity-based signcription scheme that will allow for a greater flexibility between encryption schemes, signature schemes, and signcription schemes (Wei, Shao, Xiang and et al., 2015, pg.112).

Wei, Shao, Xiang and et al. methods are to use existing techniques developed by Kushwah and Lal, Brent Waters, and Ran Canati and et al. to obtain their new identity-based signcription (Wei, Shao, Xiang and et al., 2015, pg.112). They identified formulas and backed up their claims based on proofs from other scholars to work with DBDH and CDH assumptions (Wei, Shao, Xiang and et al., 2015, pg. 122). The authors' framework was quantitative in nature and the theoretical focus was based on previously established models.

Security is important to those whose data is being mined, and the authors present schemes to help mitigate the fears of what is done with the information. The work the authors have done contributes to the social studies of library and information by showing a backend understanding of what happens to data when it goes through different encryption processes. It provides new ways to think about how data and security are viewed.

Keywords

Big Data, Signcription

Page Author: Elizabeth Moyer