Achieving Efficient and Privacy-Preserving (<inline-formula><tex-math notation="LaTeX">$\alpha,\beta$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>β</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="lu-ieq1-3169386.gif"/></alternatives></inline-formula>)-Core Query Over Bipartite Graphs in Cloud

MLA

Guan, Yunguo, et al. “Achieving Efficient and Privacy-Preserving ($\alpha,\beta$α,β)-Core Query Over Bipartite Graphs in Cloud.” IEEE Transactions on Dependable and Secure Computing, vol. 20, no. 3, Jan. 2023, pp. 1979–93. EBSCOhost, https://doi.org/10.1109/TDSC.2022.3169386.

APA

Guan, Y., Lu, R., Zheng, Y., Zhang, S., Shao, J., & Wei, G. (2023). Achieving Efficient and Privacy-Preserving ($\alpha,\beta$α,β)-Core Query Over Bipartite Graphs in Cloud. IEEE Transactions on Dependable and Secure Computing, 20(3), 1979–1993. https://doi.org/10.1109/TDSC.2022.3169386

Chicago

Guan, Yunguo, Rongxing Lu, Yandong Zheng, Songnian Zhang, Jun Shao, and Guiyi Wei. 2023. “Achieving Efficient and Privacy-Preserving ($\alpha,\beta$α,β)-Core Query Over Bipartite Graphs in Cloud.” IEEE Transactions on Dependable and Secure Computing 20 (3): 1979–93. doi:10.1109/TDSC.2022.3169386.