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  7. Singh, S.K. ; Roy, P. ; Raman, B. ; Nagabhushan, P. (Ed.)
    Fingerprint-based authentication has been successfully adopted in a wide range of applications, including law enforcement and immigration, due to its numerous advantages over traditional password-based authentication. However, despite the usability and accuracy of this technology, some significant concerns still exist, which can potentially hinder its further adoption. For instance, a subject’s fingerprint is permanently associated with an individual and, once stolen, cannot be replaced, thus compromising biometric-based authentication. To mitigate this concern, we propose a multi-factor authentication approach that integrates type 1 and type 3 authentication factors into a fingerprint-based personal identification number, or FingerPIN. To authenticate, a subject ismore »required to present a sequence of fingerprints corresponding to the digits of the PIN, based on a predefined secret mapping between digits and fingers. We conduct a vulnerability analysis of the proposed scheme, and demonstrate that it is robust to the compromise of one or more of the subject’s fingerprints.« less
  8. Graph synthesis is a long-standing research problem. Many deep neural networks that learn about latent characteristics of graphs and generate fake graphs have been proposed. However, in many cases their scalability is too high to be used to synthesize large graphs. Recently, one work proposed an interesting scalable idea to learn and generate random walks that can be merged into a graph. Due to its difficulty, however, the random walk-based graph synthesis failed to show state-of-the-art performance in many cases. We present an improved random walk-based method by using negative random walks. In our experiments with 6 datasets and 8more »baseline methods, our method shows the best performance in almost all cases. We achieve both high scalability and generation quality.« less
  9. Singhal, A. ; Vaidya, J. (Ed.)
    By virtualizing proprietary hardware networking devices, Network Functions Virtualization (NFV) allows agile and cost-effective deployment of diverse network services for multiple tenants on top of the same physical infrastructure. As NFV relies on virtualization, and as an NFV stack typically involves several levels of abstraction and multiple co-resident tenants, this new technology also unavoidably leads to new security threats. In this paper, we take the first step toward modeling and mitigating security threats unique to NFV. Specifically, we model both cross-layer and co-residency attacks on the NFV stack. Additionally, we mitigate such threats through optimizing the virtual machine (VM) placementmore »with respect to given constraints. The simulation results demonstrate the effectiveness of our solution.« less