High-Speed Hardware Architectures and FPGA Benchmarking of CRYSTALS-Kyber, NTRU, and Saber

Performance in hardware has typically played a significant role in differentiating among leading candidates in cryptographic standardization efforts. Winners of two past NIST cryptographic contests (Rijndael in case of AES and Keccak in case of SHA-3) were ranked consistently among the two fastest candidates when implemented using FPGAs and ASICs. Hardware implementations of cryptographic operations may quite easily outperform software implementations for at least a subset of major performance metrics, such as latency, number of operations per second, power consumption, and energy usage, as well as in terms of security against physical attacks, including side-channel analysis. Using hardware also permits much higher flexibility in trading one subset of these properties for another. This paper presents high-speed hardware architectures for four lattice-based CCA-secure Key Encapsulation Mechanisms (KEMs), representing three NIST PQC finalists: CRYSTALS-Kyber, NTRU (with two distinct variants, NTRU-HPS and NTRU-HRSS), and Saber. We rank these candidates among each other and compare them with all other Round 3 KEMs based on the data from the previously reported work

A Lightweight Implementation of Saber Resistant Against Side-Channel Attacks

The field of post-quantum cryptography aims to develop and analyze algorithms that can withstand classical and quantum cryptanalysis. The NIST PQC standardization process, now in its third round, specifies ease of protection against side-channel analysis as an important selection criterion. In this work, we develop and validate a masked hardware implementation of Saber key encapsulation mechanism, a third-round NIST PQC finalist. We first design a baseline lightweight hardware architecture of Saber and then apply side-channel countermeasures. Our protected hardware implementation is significantly faster than previously reported protected software and software/hardware co-design implementations. Additionally, applying side-channel countermeasures to our baseline design incurs approximately 2.9x and 1.4x penalty in terms of the number of LUTs and latency, respectively, in modern FPGAs

Implementation and Benchmarking of Round 2 Candidates in the NIST Post-Quantum Cryptography Standardization Process Using Hardware and Software/Hardware Co-design Approaches

Performance in hardware has typically played a major role in differentiating among leading candidates in cryptographic standardization efforts. Winners of two past NIST cryptographic contests (Rijndael in case of AES and Keccak in case of SHA-3) were ranked consistently among the two fastest candidates when implemented using FPGAs and ASICs. Hardware implementations of cryptographic operations may quite easily outperform software implementations for at least a subset of major performance metrics, such as speed, power consumption, and energy usage, as well as in terms of security against physical attacks, including side-channel analysis. Using hardware also permits much higher flexibility in trading one subset of these properties for another. A large number of candidates at the early stages of the standardization process makes the accurate and fair comparison very challenging. Nevertheless, in all major past cryptographic standardization efforts, future winners were identified quite early in the evaluation process and held their lead until the standard was selected. Additionally, identifying some candidates as either inherently slow or costly in hardware helped to eliminate a subset of candidates, saving countless hours of cryptanalysis. Finally, early implementations provided a baseline for future design space explorations, paving a way to more comprehensive and fairer benchmarking at the later stages of a given cryptographic competition. In this paper, we first summarize, compare, and analyze results reported by other groups until mid-May 2020, i.e., until the end of Round 2 of the NIST PQC process. We then outline our own methodology for implementing and benchmarking PQC candidates using both hardware and software/hardware co-design approaches. We apply our hardware approach to 6 lattice-based CCA-secure Key Encapsulation Mechanisms (KEMs), representing 4 NIST PQC submissions. We then apply a software-hardware co-design approach to 12 lattice-based CCA-secure KEMs, representing 8 Round 2 submissions. We hope that, combined with results reported by other groups, our study will provide NIST with helpful information regarding the relative performance of a significant subset of Round 2 PQC candidates, assuming that at least their major operations, and possibly the entire algorithms, are off-loaded to hardware

Oil pollution in the Vietnamese waters

Enumeration of hydrocarbon-degrading microorganisms (HDM) and their degradative capacity studies were carried out in area IV of South China Sea (Vietnamese water). Microbial most probable number (MPN) varied from 101 to 105 cell/ ml of surface seawater or gram of sediment. Some microbial communities and bacterial strains isolated from 97 collected samples show high hydrocarbon degradation and surfactant producing abilities. Preliminary results of our microbial study indicated that oil pollution in IV area was not found in 30 research stations. Slight oil contamination was observed in 28 survey stations

Oil pollution in the Vietnamese waters

Enumeration of hydrocarbon-degrading microorganisms (HDM) and their degradative capacity studies were carried out in area IV of South China Sea (Vietnamese water). Microbial most probable number (MPN) varied from 101 to 105 cell/ ml of surface seawater or gram of sediment. Some microbial communities and bacterial strains isolated from 97 collected samples show high hydrocarbon degradation and surfactant producing abilities. Preliminary results of our microbial study indicated that oil pollution in IV area was not found in 30 research stations. Slight oil contamination was observed in 28 survey stations

The role of nutritional risk evaluation in predicting adverse outcomes among patients with severe COVID-19 in Vietnam

IntroductionAs sufficient nutrition helps alleviate catabolic stress and modulate the systemic inflammatory response of the body, it plays an indispensable role in the good prognosis of critically ill patients. Thus, this study aimed to investigate the malnutrition of patients with severe COVID-19 and its association with adverse treatment outcomes.MethodsWe conducted a retrospective cross-sectional study in two provincial hospitals in Hanoi from February to April 2022. Participants were patients with severe COVID-19 admitted to the Intensive Care Unit (ICU). Malnutrition risk were evaluated by Nutritional Risk Screening-2002 (NRS), Global Leadership Initiative on Malnutrition (GLIM), Prognostic Nutritional Index (PNI), and the adverse prognosis was assessed by Acute Physiology and Chronic Health Evaluation II (APACHE II). The multivariate receiver-operating characteristic (ROC) curve was applied to estimate the predictive ability of those criteria regarding worse treatment results.ResultsThe percentages of malnutrition measured by NRS, GLIM, PNI, and BMI were 62.6, 51.5, 42.9, and 16.6%, respectively. Patients with more severe malnutrition assessed by GLIM, PNI, and having above target fasting blood glucose (FBG) (≥10.0 mmol/L) were more likely to have higher APACHE scores. PNI had a better diagnostic performance than NRS and BMI (AUC = 0.84, 0.81, and 0.82, respectively). In addition, FBG revealed a good prognostic implication (AUC = 0.84).ConclusionA relatively high percentage of patients experienced moderate and severe malnutrition regardless of screening tools. Individuals at higher risk of malnutrition and high FBG were predicted to have more adverse treatment outcomes. It is recommended that nutritional screening should be conducted regularly, and personalizing nutritional care strategies is necessary to meet patients’ nutrient demands and prevent other nutrition-related complications

Enhanced Private Sector Engagement for Tuberculosis Diagnosis and Reporting through an Intermediary Agency in Ho Chi Minh City, Viet Nam

Under-detection and -reporting in the private sector constitute a major barrier in Viet Nam’s fight to end tuberculosis (TB). Effective private-sector engagement requires innovative approaches. We established an intermediary agency that incentivized private providers in two districts of Ho Chi Minh City to refer persons with presumptive TB and share data of unreported TB treatment from July 2017 to March 2019. We subsidized chest x-ray screening and Xpert MTB/RIF testing, and supported test logistics, recording, and reporting. Among 393 participating private providers, 32.1% (126/393) referred at least one symptomatic person, and 3.6% (14/393) reported TB patients treated in their practice. In total, the study identified 1203 people with TB through private provider engagement. Of these, 7.6% (91/1203) were referred for treatment in government facilities. The referrals led to a post-intervention increase of +8.5% in All Forms TB notifications in the intervention districts. The remaining 92.4% (1112/1203) of identified people with TB elected private-sector treatment and were not notified to the NTP. Had this private TB treatment been included in official notifications, the increase in All Forms TB notifications would have been +68.3%. Our evaluation showed that an intermediary agency model can potentially engage private providers in Viet Nam to notify many people with TB who are not being captured by the current system. This could have a substantial impact on transparency into disease burden and contribute significantly to the progress towards ending TB

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

A Novel Method for Estimating Biomass and Carbon Sequestration in Tropical Rainforest Areas Based on Remote Sensing Imagery: A Case Study in the Kon Ha Nung Plateau, Vietnam

Forest ecosystems play a key role in sustaining life on this planet, given their functions in carbon storage, oxygen production, and the water cycle. To date, calculations of the biomass and carbon absorption capacity of forest ecosystems—especially tropical rainforests—have been quite limited, especially in Vietnam. By applying remote sensing materials, geographic information systems (GIS) facilitate the synchronized estimation of both biomass and ability of forest ecosystems to absorb carbon over large spatial ranges. In this study, we calculated the biomass of tropical rainforest vegetation in the Kon Ha Nung Plateau, Vietnam, according to four regression models based on Sentinel-2 satellite image data, forest reserve maps, and forest survey standard cell data (including 19 standard cells for 2016 and 44 standard cells for 2021). The results of the data comparison for the four biomass computing models (log-log, log-lin, lin-log, and lin-lin) demonstrated that the models with the highest accuracy were the lin-log model for 2016 (with a correlation coefficient of R2 = 0.76) and the lin-log model for 2021 (with a correlation coefficient of R2 = 0.765). Based on the analytical results and the selection of biomass estimation models, biomass maps were developed for the Kon Ha Nung Plateau area, Vietnam, in 2016 and 2021, with a predominant biomass value of 80–180 tons/ha (Mg/ha); furthermore, biomass fluctuations were analyzed for the period 2016–2021. Accordingly, the ability to absorb carbon and CO2 equivalents in this research area for 2016 and 2021 was calculated based on the estimated biomass values. In summary, we present a method for estimating biomass via four basic linear regression models for tropical rainforest areas based on satellite image data. This method can serve as a basis for managers to calculate and synchronize the payment of carbon services, which contributes to promoting the livelihoods of local people