Jonathan Graf, Shawn C. Eastwood, S. Yanushkevich, R. Ferber
{"title":"Risk Inference Models for Security Applications","authors":"Jonathan Graf, Shawn C. Eastwood, S. Yanushkevich, R. Ferber","doi":"10.1109/EST.2019.8806210","DOIUrl":"https://doi.org/10.1109/EST.2019.8806210","url":null,"abstract":"This paper focuses on the causal graph models for machine reasoning and its applications to risk assessment in biometrics. Specifically, we consider probabilistic inference performed on video data, images, speech and other human biometric data. In our approach, called the Multi-metric Inference Engine, the Bayesian network are constructed using different metrics of uncertainty, such as point probability, interval probability, fuzzy probability, and Dempster-Shafer model. We demonstrate the Inference Engine techniques using biometric-enabled security scenarios and propose a software tool for experimental study.","PeriodicalId":102238,"journal":{"name":"2019 Eighth International Conference on Emerging Security Technologies (EST)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116183661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Efficient Hardware Design for Combined AES and AEGIS","authors":"Amit Sardar, Bijoy Das, D. R. Chowdhury","doi":"10.1109/EST.2019.8806225","DOIUrl":"https://doi.org/10.1109/EST.2019.8806225","url":null,"abstract":"This paper presents an integrated design of AES, the block cipher standard and AEGIS, an AES based authenticated encryption. Our design tries to exploit the common functionalities of AES and AEGIS to achieve both confidentiality as well as confidentiality and authenticity together. The proposed design provides a cost-effective implementation on various FPGA platforms, and it achieves both the goals by using a minimum amount of extra resources compared to the stand-alone AES and AEGIS design. The performance of our design implementation has been compared with the similar design work, and it has been shown that the throughput and frequency of our design outperform the best result available in the literature.","PeriodicalId":102238,"journal":{"name":"2019 Eighth International Conference on Emerging Security Technologies (EST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124556203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatio-Temporal Texture Features for Presentation Attack Detection in Biometric Systems","authors":"S. Pan, F. Deravi","doi":"10.1109/EST.2019.8806220","DOIUrl":"https://doi.org/10.1109/EST.2019.8806220","url":null,"abstract":"Spatio-temporal information is valuable as a discriminative cue for presentation attack detection, where the temporal texture changes and fine-grained motions (such as eye blinking) can be indicative of some types of spoofing attacks. In this paper, we propose a novel spatio-temporal feature, based on motion history, which can offer an efficient way to encapsulate temporal texture changes. Patterns of motion history are used as primary features followed by secondary feature extraction using Local Binary Patterns and Convolutional Neural Networks, and evaluated using the Replay Attack and CASIA-FASD datasets, demonstrating the effectiveness of the proposed approach.","PeriodicalId":102238,"journal":{"name":"2019 Eighth International Conference on Emerging Security Technologies (EST)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123325130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}