1,721,022 research outputs found
A relation calculus for reasoning about t-probing security
No full textIn the context of side-channel attacks against cryptographic circuits, t-probing security characterizes the amount of information derivable about sensitive values (e.g., keys) by observing t output/internal values. Non-interference is a useful mathematical tool used by researchers to assess the probing security of a circuit which employs Boolean masking to protect itself from attacks. However, reasoning about non-interference still requires either difficult ratiocination or complex automatic tools. In this work, we propose a novel point of view to reason about non-interference, by exploiting the Walsh transform of a Boolean function. To this end, we introduce a calculus for mechanically reasoning about the shares of a variable and show that this formalism provides a lean algebraic explanation of known compositional patterns allowing for the discovery of new ones. Eventually, we show how this formalism can be applied to study the probing security of known cryptographic gadgets
Extended B-ALIF: Improving Anomaly Detection with Human Feedback
No full textAnomaly Detection is a task in engineering aiming at identifying deviations from expected patterns in data. Data-driven approaches have emerged in past recent years due to the fact that a model of complex system may be hard or impossible to be derived in many scenarios. Moreover, unsupervised approaches have been particularly appealing for practitioners and scientists given the typical unavailability of tagged data. Such approaches are often integrated in frameworks, like Decision Support Systems, that assist domain experts and operators in the monitoring task. Human presence, by providing a limited amount of feedback, can be leveraged as a valuable source of information to iteratively enhance detection performance. In this work we introduce Extended B-ALIF, a framework designed to incrementally select and integrate expert feedback into the Extended Isolation Forest anomaly detection model. This study extends Bayesian Active Learning Isolation Forest (B-ALIF), which originally proposed the same theoretical principles for another anomaly detection model, the Isolation Forest
On robust strong-non-interferent low-latency multiplications
Full text linkThe overarching goal of this work is to present new theoretical and practical tools to implement (Formula presented.) −probing security. In this work, a low-latency multiplication gadget that is secure against probing attacks that exploit logic glitches in the circuit is presented. The gadget is the first of its kind to present a 1-cycle input-to-output latency while belonging to the class of probing security by optimized composition gadgets [6]. In particular, the authors show that it is possible to construct robust- (Formula presented.) -strong-non-interferent gadgets without compromising on latency with a moderate increase in area. The authors provide a theoretical proof for the robustness of the gadget and show that, for (Formula presented.), the amount of randomness required can even be reduced without compromising on robustness
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Multiple complex developmental disorder (MCDD): Did we throw the baby out with the bathwater too fast? A systematic review
No full textBackground: Multiple complex developmental disorder (MCDD) manifests as early-onset impairment across different domains. Although it could appear as a transitional condition between autism and childhood-onset schizophrenia, interest in MCDD has progressively waned. This study attempts to discern MCDD current relevance to avoid “throwing the baby out with the bathwater” too fast. Methods: All available studies published up to January 2024 were retrieved and evaluated following on the PRISMA guidelines for systematic reviews using the term “multiple complex developmental disorder” or “MCDD”, without any filter for study design nor year of publication. Results: Only 16 studies were included and analyzed. Overall, a variable heterogeneity was observed in terms of country of investigation, study design, and clinical groups. Most of the included studies explored the construct of MCDD in developmental age, comparing MCDD mostly with autistic patients, and observing how the former group had higher levels of paranoia, illusions, and psychotic thoughts, whereas the latter showed more frequently difficulties in social interactions and stereotypical behaviors. Conclusion: Overall, these results showed how progressive changes in diagnostic criteria over time led MCDD to be abandoned as nosographic construct, leaving perhaps a diagnostic void between autism and psychotic disorders that needs to be further studied. A systematic review on the Multiple Complex Developmental Disorder (MCDD): a forgotten diagnosis between autism and schizophrenia
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
AcME-AD: Accelerated Model Explanations for Anomaly Detection
No full textPursuing fast and robust interpretability in anomaly detection is crucial, especially due to its significance in practical applications. Traditional anomaly detection methods excel in outlier identification but are often ‘black-boxes’, providing scant insights into their decision-making processes. This lack of transparency compromises their reliability and hampers their adoption in scenarios where comprehending the reasons behind anomaly detection is vital. At the same time, getting explanations quickly is paramount in practical scenarios. To bridge this gap, we present AcME-AD, a novel approach rooted in Explainable Artificial Intelligence principles, designed to clarify anomaly detection models for tabular data. AcME-AD transcends the constraints of model-specific or resource-heavy explainability techniques by delivering a model-agnostic, efficient solution for interpretability. It offers local feature importance scores and a what-if analysis tool, shedding light on the factors contributing to each anomaly, thus aiding root cause analysis and decision-making. This paper elucidates AcME-AD ’s foundation, its benefits over existing methods, and validates its effectiveness with tests on both synthetic and real datasets. AcME-AD’s implementation and experiment replication code is accessible in a public repository (https://github.com/dandolodavid/ACME/tree/master/notebook/anomaly_detection_notebook)
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