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Inferring characteristic phenotypes via class association rule mining in the bone dysplasia domain., , , and . J. Biomed. Informatics, (2014)Breaking TrustZone Memory Isolation through Malicious Hardware on a Modern FPGA-SoC., , , and . ASHES@CCS, page 3-12. ACM, (2019)Earthquake - A NoC-based optimized differential cache-collision attack for MPSoCs., , , and . DATE, page 648-653. IEEE, (2018)Capturing domain knowledge from multiple sources: the rare bone disorders use case., , , and . J. Biomed. Semant., (2015)The Human Phenotype Ontology in 2017., , , , , , , , , and 49 other author(s). Nucleic Acids Res., 45 (Database-Issue): D865-D876 (2017)PerfWeb: How to Violate Web Privacy with Hardware Performance Events., , , and . ESORICS (2), volume 10493 of Lecture Notes in Computer Science, page 80-97. Springer, (2017)Semantic interestingness measures for discovering association rules in the skeletal dysplasia domain., , , and . J. Biomed. Semant., (2014)The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain., , and . BMC Bioinform., (2012)AutoLock: Why Cache Attacks on ARM Are Harder Than You Think., , , , , and . USENIX Security Symposium, page 1075-1091. USENIX Association, (2017)Undermining User Privacy on Mobile Devices Using AI., , , , , and . AsiaCCS, page 214-227. ACM, (2019)