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A Framework for Enhancing Deep Neural Networks Against Adversarial Malware.

, , , and . IEEE Trans. Netw. Sci. Eng., 8 (1): 736-750 (2021)

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Computational complexity characterization of protecting elections from bribery., , , , , , , and . Theor. Comput. Sci., (2021)Election with Bribed Voter Uncertainty: Hardness and Approximation Algorithm., , , , and . AAAI, page 2572-2579. AAAI Press, (2019)Enhancing Anonymity via Market Competition., , and . ITCC (1), page 30-34. IEEE Computer Society, (2004)Data-Driven Characterization and Detection of COVID-19 Themed Malicious Websites., , , , and . ISI, page 1-6. IEEE, (2020)ConMan: A Connection Manipulation-based Attack Against Bitcoin Networking., , , and . CNS, page 101-109. IEEE, (2021)SARR: A Cybersecurity Metrics and Quantification Framework (Keynote).. SciSec, volume 13005 of Lecture Notes in Computer Science, page 3-17. Springer, (2021)VulDeePecker: A Deep Learning-Based System for Vulnerability Detection., , , , , , , and . NDSS, The Internet Society, (2018)Friendly Observers Ease Off-Line E-Cash., , and . CARDIS, volume 180 of IFIP Conference Proceedings, page 3-18. Kluwer, (2000)VABKS: Verifiable attribute-based keyword search over outsourced encrypted data., , and . INFOCOM, page 522-530. IEEE, (2014)Non-interactive editable signatures for assured data provenance., and . CODASPY, page 145-156. ACM, (2011)