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DATA - Differential Address Trace Analysis
2018
Krypto-Tag
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PerfWeb: How to Violate Web Privacy with Hardware Performance Events
[article]
2017
arXiv
pre-print
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The browser history reveals highly sensitive information about users, such as financial status, health conditions, or political views. Private browsing modes and anonymity networks are consequently important tools to preserve the privacy not only of regular users but in particular of whistleblowers and dissidents. Yet, in this work we show how a malicious application can infer opened websites from Google Chrome in Incognito mode and from Tor Browser by exploiting hardware performance events
arXiv:1705.04437v1
fatcat:m77wwcuiyncstdwttk2jwxx7fq
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... s). In particular, we analyze the browsers' microarchitectural footprint with the help of advanced Machine Learning techniques: k-th Nearest Neighbors, Decision Trees, Support Vector Machines, and in contrast to previous literature also Convolutional Neural Networks. We profile 40 different websites, 30 of the top Alexa sites and 10 whistleblowing portals, on two machines featuring an Intel and an ARM processor. By monitoring retired instructions, cache accesses, and bus cycles for at most 5 seconds, we manage to classify the selected websites with a success rate of up to 86.3%. The results show that hardware performance events can clearly undermine the privacy of web users. We therefore propose mitigation strategies that impede our attacks and still allow legitimate use of HPEs.
Ontoclick: a Chrome web browser extension to facilitate biomedical knowledge curation
[article]
2021
bioRxiv
pre-print
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Knowledge curation from the biomedical literature is very valuable but can be a repetitive and laborious process. The paucity of user-friendly tools is one of the reasons for the lack of widespread adoption of good biomedical knowledge curation practices. Here we present Ontoclick, a Chrome web browser extension that streamlines the process of annotating a text span with a relevant ontology term. We hope this tool will make biocuration more accessible to a wider audience of biomedical
doi:10.1101/2021.03.04.433993
fatcat:furz6rt4rrfnhe4ow3solh4wgy
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... s. Ontoclick is freely available under the GPL-3.0 license on the Chrome Web Store. Source code and documentation are available at: https://github.com/azankl/Ontoclick Contact: andreas.zankl@sydney.edu.au
Mining Skeletal Phenotype Descriptions from Scientific Literature
2013
PLoS ONE
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Phenotype descriptions are important for our understanding of genetics, as they enable the computation and analysis of a varied range of issues related to the genetic and developmental bases of correlated characters. The literature contains a wealth of such phenotype descriptions, usually reported as free-text entries, similar to typical clinical summaries. In this paper, we focus on creating and making available an annotated corpus of skeletal phenotype descriptions. In addition, we present
doi:10.1371/journal.pone.0055656
pmid:23409017
pmcid:PMC3568099
fatcat:lw5xpqm2njf47jkw5fyq55tgsu
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... evaluate a hybrid Machine Learning approach for mining phenotype descriptions from free text. Our hybrid approach uses an ensemble of four classifiers and experiments with several aggregation techniques. The best scoring technique achieves an F-1 score of 71.52%, which is close to the state-of-the-art in other domains, where training data exists in abundance. Finally, we discuss the influence of the features chosen for the model on the overall performance of the method.
Decomposing Phenotype Descriptions for the Human Skeletal Phenome
2013
Biomedical Informatics Insights
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Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. The intrinsic value and knowledge captured within such descriptions can only be expressed by taking advantage of their inner structure that implicitly combines qualities and anatomical entities. We present a meta-model (the Phenotype Fragment Ontology) and a processing pipeline that enable together the automatic decomposition and
doi:10.4137/bii.s10729
pmid:23440304
pmcid:PMC3572876
fatcat:hunhhvsisnfinkbvsedfnwif4m
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... tion of phenotype descriptions for the human skeletal phenome. We use this approach to showcase the usefulness of the generic concept of phenotype decomposition by performing an experimental study on all skeletal phenotype concepts defined in the Human Phenotype Ontology. ‡ ywords: human skeletal phenome, phenotype decomposition, phenotype segmentation, ontologies Biomedical Informatics Insights 2013:6 1-14 Biomedical Informatics Insights 2013:
Experiences with Modeling Composite Phenotypes in the SKELETOME Project
[chapter]
2012
Lecture Notes in Computer Science
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Semantic annotation of patient data in the skeletal dysplasia domain (e.g., clinical summaries) is a challenging process due to the structural and lexical differences existing between the terms used to describe radiographic findings. In this paper we propose an ontology aimed at representing the intrinsic structure of such radiographic findings in a standard manner, in order to bridge the different lexical variations of the actual terms. Furthermore, we describe and evaluate an algorithm
doi:10.1007/978-3-642-35173-0_6
fatcat:kfkxbxoypfbplpftqlrhzycmqu
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... of mapping concepts of this ontology to exact or broader terms in the main phenotype ontology used in the bone dysplasia domain.
AutoLock: Why Cache Attacks on ARM Are Harder Than You Think
[article]
2017
arXiv
pre-print
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Attacks on the microarchitecture of modern processors have become a practical threat to security and privacy in desktop and cloud computing. Recently, cache attacks have successfully been demonstrated on ARM based mobile devices, suggesting they are as vulnerable as their desktop or server counterparts. In this work, we show that previous literature might have left an overly pessimistic conclusion of ARM's security as we unveil AutoLock: an internal performance enhancement found in inclusive
arXiv:1703.09763v1
fatcat:daykpvsb2jh4znhcex35i6mucq
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... he levels of ARM processors that adversely affects Evict+Time, Prime+Probe, and Evict+Reload attacks. AutoLock's presence on system-on-chips (SoCs) is not publicly documented, yet knowing that it is implemented is vital to correctly assess the risk of cache attacks. We therefore provide a detailed description of the feature and propose three ways to detect its presence on actual SoCs. We illustrate how AutoLock impedes cross-core cache evictions, but show that its effect can also be compensated in a practical attack. Our findings highlight the intricacies of cache attacks on ARM and suggest that a fair and comprehensive vulnerability assessment requires an in-depth understanding of ARM's cache architectures and rigorous testing across a broad range of ARM based devices.
Supervised segmentation of phenotype descriptions for the human skeletal phenome using hybrid methods
2012
BMC Bioinformatics
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Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. In order to fully capture the intrinsic value and knowledge expressed within them, we need to take advantage of their inner structure, which implicitly combines qualities and anatomical entities. The first step in this process is the segmentation of the phenotype descriptions into their atomic elements. Results: We present a two-phase hybrid
doi:10.1186/1471-2105-13-265
pmid:23061930
pmcid:PMC3495645
fatcat:hvpmzhouvbhkpn2ebrswcu4hnq
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... egmentation method that combines a series individual classifiers using different aggregation schemes (set operations and simple majority voting). The approach is tested on a corpus comprised of skeletal phenotype descriptions emerged from the Human Phenotype Ontology. Experimental results show that the best hybrid method achieves an F-Score of 97.05% in the first phase and F-Scores of 97.16% / 94.50% in the second phase. Conclusions: The performance of the initial segmentation of anatomical entities and qualities (phase I) is not affected by the presence / absence of external resources, such as domain dictionaries. From a generic perspective, hybrid methods may not always improve the segmentation accuracy as they are heavily dependent on the goal and data characteristics.
Undermining User Privacy on Mobile Devices Using AI
[article]
2020
arXiv
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Over the past years, literature has shown that attacks exploiting the microarchitecture of modern processors pose a serious threat to the privacy of mobile phone users. This is because applications leave distinct footprints in the processor, which can be used by malware to infer user activities. In this work, we show that these inference attacks are considerably more practical when combined with advanced AI techniques. In particular, we focus on profiling the activity in the last-level cache
arXiv:1811.11218v2
fatcat:y6lcfhriujekxmznrbwuk2xlvm
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... C) of ARM processors. We employ a simple Prime+Probe based monitoring technique to obtain cache traces, which we classify with Deep Learning methods including Convolutional Neural Networks. We demonstrate our approach on an off-the-shelf Android phone by launching a successful attack from an unprivileged, zeropermission App in well under a minute. The App thereby detects running applications with an accuracy of 98% and reveals opened websites and streaming videos by monitoring the LLC for at most 6 seconds. This is possible, since Deep Learning compensates measurement disturbances stemming from the inherently noisy LLC monitoring and unfavorable cache characteristics such as random line replacement policies. In summary, our results show that thanks to advanced AI techniques, inference attacks are becoming alarmingly easy to implement and execute in practice. This once more calls for countermeasures that confine microarchitectural leakage and protect mobile phone applications, especially those valuing the privacy of their users.
Optimal management of complications associated with achondroplasia
2014
The Application of Clinical Genetics
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Achondroplasia is the most common form of skeletal dysplasia, resulting in disproportionate short stature, and affects over 250,000 people worldwide. Individuals with achondroplasia demonstrate a number of well-recognized anatomical features that impact on growth and development, with a complex array of medical issues that are best managed through a multidisciplinary team approach. The complexity of this presentation, whereby individual impairments may impact upon multiple activity and
doi:10.2147/tacg.s51485
pmid:25053890
pmcid:PMC4104450
fatcat:tjqoaurjnrg4vksnn5hnw7ogt4
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... tion areas, requires consideration and discussion under a broad framework to gain a more thorough understanding of the experience of this condition for individuals with achondroplasia. This paper examines the general literature and research evidence on the medical and health aspects of individuals with achondroplasia and presents a pictorial model of achondroplasia based on The International Classification of Functioning, Disability, and Health (ICF). An expanded model of the ICF will be used to review and present the current literature pertaining to the musculoskeletal, neurological, cardiorespiratory, and ear, nose, and throat impairments and complications across the lifespan, with discussion on the impact of these impairments upon activity and participation performance. Further research is required to fully identify factors influencing participation and to help develop strategies to address these factors.
Evolutionary Comparison Provides Evidence for Pathogenicity of RMRP Mutations
2005
PLoS Genetics
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Cartilage-hair hypoplasia (CHH) is a pleiotropic disease caused by recessive mutations in the RMRP gene that result in a wide spectrum of manifestations including short stature, sparse hair, metaphyseal dysplasia, anemia, immune deficiency, and increased incidence of cancer. Molecular diagnosis of CHH has implications for management, prognosis, follow-up, and genetic counseling of affected patients and their families. We report 20 novel mutations in 36 patients with CHH and describe the
doi:10.1371/journal.pgen.0010047
pmid:16244706
pmcid:PMC1262189
fatcat:gqo6mcvbxfdqrnpuiqplntx6dq
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... ed phenotypic spectrum. Given the high mutational heterogeneity (62 mutations reported to date), the high frequency of variations in the region (eight single nucleotide polymorphisms in and around RMRP), and the fact that RMRP is not translated into protein, prediction of mutation pathogenicity is difficult. We addressed this issue by a comparative genomic approach and aligned the genomic sequences of RMRP gene in the entire class of mammals. We found that putative pathogenic mutations are located in highly conserved nucleotides, whereas polymorphisms are located in non-conserved positions. We conclude that the abundance of variations in this small gene is remarkable and at odds with its high conservation through species; it is unclear whether these variations are caused by a high local mutation rate, a failure of repair mechanisms, or a relaxed selective pressure. The marked diversity of mutations in RMRP and the low homozygosity rate in our patient population indicate that CHH is more common than previously estimated, but may go unrecognized because of its variable clinical presentation. Thus, RMRP molecular testing may be indicated in individuals with isolated metaphyseal dysplasia, anemia, or immune dysregulation.
Semantic Similarity-Driven Decision Support in the Skeletal Dysplasia Domain
[chapter]
2012
Lecture Notes in Computer Science
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Biomedical ontologies have become a mainstream topic in medical research. They represent important sources of evolved knowledge that may be automatically integrated in decision support methods. Grounding clinical and radiographic findings in concepts defined by a biomedical ontology, e.g., the Human Phenotype Ontology, enables us to compute semantic similarity between them. In this paper, we focus on using such similarity measures to predict disorders on undiagnosed patient cases in the bone
doi:10.1007/978-3-642-35173-0_11
fatcat:ge427radlrezzf6q2khpdak7c4
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... plasia domain. Different methods for computing the semantic similarity have been implemented. All methods have been evaluated based on their support in achieving a higher prediction accuracy. The outcome of this research enables us to understand the feasibility of developing decision support methods based on ontology-driven semantic similarity in the skeletal dysplasia domain.
Visualising A Skeletal Dysplasia Knowledgebase
2007
International Conference on Medical Information Visualisation - BioMedical Visualisation (MediVis 2007)
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Skeletal dysplasias affect around 4 million people worldwide. Various nosologies exist for describing and classifying their clinical, radiological, and genetic features. A methodological framework is needed to establish a single consolidated nosology for skeletal dysplasias based on the existing multiple classification systems.. Once established, the terms used can be linked to an existing database of exemplar x-ray images and explored interactively. As a proof-of-concept, a pilot study was
doi:10.1109/medivis.2007.21
fatcat:winzhet7p5h33k2hcbhuq5ukim
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... ucted to investigate the potential in both establishing a consolidated nosology and visualisation of the results. This paper reports on a preliminary methodological framework for proceeding and initial visualisation results which go some way towards demonstrating the potential of such a system. The aim of this project is to assist clinicians to make more accurate diagnoses of skeletal dysplasias and to foster translational research. This is set against the background of an existing unwieldy classification system.
The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain
2012
BMC Bioinformatics
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Skeletal dysplasias are a rare and heterogeneous group of genetic disorders affecting skeletal development. Patients with skeletal dysplasias suffer from many complex medical issues including degenerative joint disease and neurological complications. Because the data and expertise associated with this field is both sparse and disparate, significant benefits will potentially accrue from the availability of an ontology that provides a shared conceptualisation of the domain knowledge and enables
doi:10.1186/1471-2105-13-50
pmid:22449239
pmcid:PMC3338382
fatcat:flu5hsohtvahhmd5kwfec4es6u
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... ta integration, cross-referencing and advanced reasoning across the relevant but distributed data sources. Results: We introduce the design considerations and implementation details of the Bone Dysplasia Ontology. We also describe the different components of the ontology, including a comprehensive and formal representation of the skeletal dysplasia domain as well as the related genotypes and phenotypes. We then briefly describe SKELETOME, a community-driven knowledge curation platform that is underpinned by the Bone Dysplasia Ontology. SKELETOME enables domain experts to use, refine and extend and apply the ontology without any prior ontology engineering experience-to advance the body of knowledge in the skeletal dysplasia field. Conclusions: The Bone Dysplasia Ontology represents the most comprehensive structured knowledge source for the skeletal dysplasias domain. It provides the means for integrating and annotating clinical and research data, not only at the generic domain knowledge level, but also at the level of individual patient case studies. It enables links between individual cases and publicly available genotype and phenotype resources based on a community-driven curation process that ensures a shared conceptualisation of the domain knowledge and its continuous incremental evolution.
How to Break Secure Boot on FPGA SoCs Through Malicious Hardware
[chapter]
2017
Lecture Notes in Computer Science
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Embedded IoT devices are often built upon large system on chip computing platforms running a significant stack of software. For certain computation-intensive operations such as signal processing or encryption and authentication of large data, chips with integrated FPGAs, FPGA SoCs, which provide high performance through configurable hardware designs, are used. In this contribution, we demonstrate how an FPGA hardware design can compromise the important secure boot process of the main software
doi:10.1007/978-3-319-66787-4_21
fatcat:n2fz4op665caba27jyp55u6pma
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... stem to boot from a malicious network source instead of an authentic signed kernel image. This significant and new threat arises from the fact that the CPU and FPGA are connected to the same memory bus, so that FPGA hardware designs can interfere with secure boot routines on FPGA SoCs that are without any interruption on regular SoCs. An enabling factor is that integrated hardware designs are likely bought from external partners and there is a realistic lack of security review at the system integrators. This facilitates flaws or even unwanted functionality in such hardware designs. We perform a proof of concept on a Xilinx Zynq-7000 FPGA SoC, and the threat can be generalized to other devices. We also present as effective mitigation, an easy-to-review and re-usable wrapper module which prevents any unauthorized memory access by included hardware designs.
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