Comprehensive Security Analysis of CRAFT

CRAFT is a lightweight block cipher, designed to provide efficient protection against differential fault attacks. It is a tweakable cipher that includes 32 rounds to produce a ciphertext from a 64-bit plaintext using a 128-bit key and 64-bit public tweak. In this paper, compared to the designers\u27 analysis, we provide a more detailed analysis of CRAFT against differential and zero-correlation cryptanalysis, aiming to provide better distinguishers for the reduced rounds of the cipher. Our distinguishers for reduced-round CRAFT cover a higher number of rounds compared to the designers\u27 analysis. In our analysis, we observed that, for any number of rounds, the differential effect of CRAFT has an extremely higher probability compared to any differential trail. As an example, while the best trail for 11 rounds of the cipher has a probability of at least $2^{-80}$, we present a differential with probability $2^{-49.79}$, containing $2^{29.66}$ optimal trails, all with the same optimum probability of $2^{-80}$. Next, we use a partitioning technique, based on optimal expandable truncated trails to provide a better estimation of the differential effect on CRAFT. Thanks to this technique, we are able to find differential distinguishers for 9, 10, 11, 12, 13, and 14 rounds of the cipher in single tweak model with the probabilities of at least $2^{-40.20}$, $2^{-45.12}$, $2^{-49.79}$, $2^{-54.49}$, $2^{-59.13}$, and $2^{-63.80}$, respectively. These probabilities should be compared with the best distinguishers provided by the designers in the same model for 9 and 10 rounds of the cipher with the probabilities of at least $2^{-54.67}$ and $2^{-62.61}$, respectively. In addition, we consider the security of CRAFT against the new concept of related tweak zero-correlation (ZC) linear cryptanalysis and present a new distinguisher which covers 14 rounds of the cipher, while the best previous ZC distinguisher covered 13 rounds. Thanks to the related tweak ZC distinguisher for 14 rounds of the cipher, we also present 14 rounds integral distinguishers in related tweak mode of the cipher. Although the provided analysis does not compromise the cipher, we think it provides a better insight into the designing of CRAFT

Lessons learned from SARS-CoV and MERS-CoV : FDA-approved Abelson tyrosine-protein kinase 2 inhibitors may help us combat SARS-CoV-2

SARS-CoV-2 is a newly emerging infectious disease, which originated from Wuhan in the Hubei province of China in late December 2019 [1]. Since then, it has rapidly spread all over the world, and at the time of writing this letter, WHO statistics show more than 1,696,588 cases and 105,952 deaths confirmed across the world [2]. Although there is no specific therapy for SARS-CoV-2 infection [3], combination therapy with antiviral and anti-inflammatory drugs accompanied by supportive treatment have been used for SARS-CoV-2 patients [4]. The combination of well-known HIV protease inhibitors, such as ritonavir with lopinavir, has also been a common approach to treat SARS-CoV-2. Insufficient outcome in severe cases is, however, one of the main challenges associated with the current antiviral-based therapy for SARS-CoV-2 [5]. In view of the long period required for novel drug discovery and the desperate need for a prompt response to this pandemic infection, one must resort to repurposing FDA-approved drugs. In this direction, our experience with other close members of coronaviruses such as SARS and MERS has taught us that repurposing the current drugs is a reasonable strategy. Abelson tyrosine-protein kinase 2 (Abl2), the imatinib target, was required for efficient SARS-CoV and MERS-CoV replication in vitro [6]. Coleman et al. have shown that the imatinib target Abl2 is indispensable for efficient replication of SARS-CoV and MERS-CoV in vitro

An Approach toward Artificial Intelligence Alzheimer's Disease Diagnosis Using Brain Signals

Background: Electroencephalography (EEG) signal analysis is a rapid, low-cost, and practical method for diagnosing the early stages of dementia, including mild cognitive impairment (MCI) and Alzheimer’s disease (AD). The extraction of appropriate biomarkers to assess a subject’s cognitive impairment has attracted a lot of attention in recent years. The aberrant progression of AD leads to cortical detachment. Due to the interaction of several brain areas, these disconnections may show up as abnormalities in functional connectivity and complicated behaviors. Methods: This work suggests a novel method for differentiating between AD, MCI, and HC in two-class and three-class classifications based on EEG signals. To solve the class imbalance, we employ EEG data augmentation techniques, such as repeating minority classes using variational autoencoders (VAEs), as well as traditional noise-addition methods and hybrid approaches. The power spectrum density (PSD) and temporal data employed in this study’s feature extraction from EEG signals were combined, and a support vector machine (SVM) classifier was used to distinguish between three categories of problems. Results: Insufficient data and unbalanced datasets are two common problems in AD datasets. This study has shown that it is possible to generate comparable data using noise addition and VAE, train the model using these data, and, to some extent, overcome the aforementioned issues with an increase in classification accuracy of 2 to 7%. Conclusion: In this work, using EEG data, we were able to successfully detect three classes: AD, MCI, and HC. In comparison to the pre-augmentation stage, the accuracy gained in the classification of the three classes increased by 3% when the VAE model added additional data. As a result, it is clear how useful EEG data augmentation methods are for classes with smaller sample numbers

An Approach toward Artificial Intelligence Alzheimer’s Disease Diagnosis Using Brain Signals

Background: Electroencephalography (EEG) signal analysis is a rapid, low-cost, and practical method for diagnosing the early stages of dementia, including mild cognitive impairment (MCI) and Alzheimer’s disease (AD). The extraction of appropriate biomarkers to assess a subject’s cognitive impairment has attracted a lot of attention in recent years. The aberrant progression of AD leads to cortical detachment. Due to the interaction of several brain areas, these disconnections may show up as abnormalities in functional connectivity and complicated behaviors. Methods: This work suggests a novel method for differentiating between AD, MCI, and HC in two-class and three-class classifications based on EEG signals. To solve the class imbalance, we employ EEG data augmentation techniques, such as repeating minority classes using variational autoencoders (VAEs), as well as traditional noise-addition methods and hybrid approaches. The power spectrum density (PSD) and temporal data employed in this study’s feature extraction from EEG signals were combined, and a support vector machine (SVM) classifier was used to distinguish between three categories of problems. Results: Insufficient data and unbalanced datasets are two common problems in AD datasets. This study has shown that it is possible to generate comparable data using noise addition and VAE, train the model using these data, and, to some extent, overcome the aforementioned issues with an increase in classification accuracy of 2 to 7%. Conclusion: In this work, using EEG data, we were able to successfully detect three classes: AD, MCI, and HC. In comparison to the pre-augmentation stage, the accuracy gained in the classification of the three classes increased by 3% when the VAE model added additional data. As a result, it is clear how useful EEG data augmentation methods are for classes with smaller sample numbers

The unfinished agenda of communicable diseases among children and adolescents before the COVID-19 pandemic, 1990-2019: a systematic analysis of the Global Burden of Disease Study 2019

BACKGROUND: Communicable disease control has long been a focus of global health policy. There have been substantial reductions in the burden and mortality of communicable diseases among children younger than 5 years, but we know less about this burden in older children and adolescents, and it is unclear whether current programmes and policies remain aligned with targets for intervention. This knowledge is especially important for policy and programmes in the context of the COVID-19 pandemic. We aimed to use the Global Burden of Disease (GBD) Study 2019 to systematically characterise the burden of communicable diseases across childhood and adolescence. METHODS: In this systematic analysis of the GBD study from 1990 to 2019, all communicable diseases and their manifestations as modelled within GBD 2019 were included, categorised as 16 subgroups of common diseases or presentations. Data were reported for absolute count, prevalence, and incidence across measures of cause-specific mortality (deaths and years of life lost), disability (years lived with disability [YLDs]), and disease burden (disability-adjusted life-years [DALYs]) for children and adolescents aged 0-24 years. Data were reported across the Socio-demographic Index (SDI) and across time (1990-2019), and for 204 countries and territories. For HIV, we reported the mortality-to-incidence ratio (MIR) as a measure of health system performance. FINDINGS: In 2019, there were 3·0 million deaths and 30·0 million years of healthy life lost to disability (as measured by YLDs), corresponding to 288·4 million DALYs from communicable diseases among children and adolescents globally (57·3% of total communicable disease burden across all ages). Over time, there has been a shift in communicable disease burden from young children to older children and adolescents (largely driven by the considerable reductions in children younger than 5 years and slower progress elsewhere), although children younger than 5 years still accounted for most of the communicable disease burden in 2019. Disease burden and mortality were predominantly in low-SDI settings, with high and high-middle SDI settings also having an appreciable burden of communicable disease morbidity (4·0 million YLDs in 2019 alone). Three cause groups (enteric infections, lower-respiratory-tract infections, and malaria) accounted for 59·8% of the global communicable disease burden in children and adolescents, with tuberculosis and HIV both emerging as important causes during adolescence. HIV was the only cause for which disease burden increased over time, particularly in children and adolescents older than 5 years, and especially in females. Excess MIRs for HIV were observed for males aged 15-19 years in low-SDI settings. INTERPRETATION: Our analysis supports continued policy focus on enteric infections and lower-respiratory-tract infections, with orientation to children younger than 5 years in settings of low socioeconomic development. However, efforts should also be targeted to other conditions, particularly HIV, given its increased burden in older children and adolescents. Older children and adolescents also experience a large burden of communicable disease, further highlighting the need for efforts to extend beyond the first 5 years of life. Our analysis also identified substantial morbidity caused by communicable diseases affecting child and adolescent health across the world. FUNDING: The Australian National Health and Medical Research Council Centre for Research Excellence for Driving Investment in Global Adolescent Health and the Bill & Melinda Gates Foundation

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Comprehensive security analysis of CRAFT

CRAFT is a lightweight block cipher, designed to provide efficient protection against differential fault attacks. It is a tweakable cipher that includes 32 rounds to produce a ciphertext from a 64-bit plaintext using a 128-bit key and 64-bit public tweak. In this paper, compared to the designers’ analysis, we provide a more detailed analysis of CRAFT against differential and zero-correlation cryptanalysis, aiming to provide better distinguishers for the reduced rounds of the cipher. Our distinguishers for reduced-round CRAFT cover a higher number of rounds compared to the designers’ analysis. In our analysis, we observed that, for any number of rounds, the differential effect of CRAFT has an extremely higher probability compared to any differential trail. As an example, while the best trail for 11 rounds of the cipher has a probability of at least 2−80, we present a differential with probability 2−49.79, containing 229.66 optimal trails, all with the same optimum probability of 2−80. Next, we use a partitioning technique, based on optimal expandable truncated trails to provide a better estimation of the differential effect on CRAFT. Thanks to this technique, we are able to find differential distinguishers for 9, 10, 11, 12, 13, and 14 rounds of the cipher in single tweak model with the probabilities of at least 2−40.20, 2−45.12, 2−49.79, 2−54.49, 2−59.13, and 2−63.80, respectively. These probabilities should be compared with the best distinguishers provided by the designers in the same model for 9 and 10 rounds of the cipher with the probabilities of at least 2−54.67 and 2−62.61, respectively. In addition, we consider the security of CRAFT against the new concept of related tweak zero-correlation (ZC) linear cryptanalysis and present a new distinguisher which covers 14 rounds of the cipher, while the best previous ZC distinguisher covered 13 rounds. Thanks to the related tweak ZC distinguisher for 14 rounds of the cipher, we also present 14 rounds integral distinguishers in related tweak mode of the cipher. Although the provided analysis does not compromise the cipher, we think it provides a better insight into the designing of CRAFT