Evaluation of the Factors Affecting Classification Performance in Class Imbalance Problem

In binary classification, when the distribution of numbers in the class is imbalanced, we are aimed to increase the accuracy of classification in classification methods. In our study, simulated data sets and actual data sets are used. In the simulation, the "BinNor" package in the R project, which produces both numerical and categorical data, was utilized. When simulation work is planned, three different effects are considered which may affect the classification performance. These are: sample size, correlation structure and class imbalance rates. Scenarios were created by considering these effects. Each scenario was repeated 1000 times and 10-fold cross-validation was applied. CART, SVM and RF methods have been used in the classification of data sets obtained from both simulation and actual data sets. SMOTE, SMOTEBoost and RUSBoost were used to decrease or completely remove the imbalance of the data before the classification methods were applied. Specificity, sensitivity, balanced accuracy and F-measure were used as performance measures. The simulation results: the imbalance rate increases from 10 to 30, the effect of the 3 algorithms on the classification methods is similar accuracy. Because the class imbalance has become balanced

Falcon Down: Breaking Falcon Post-Quantum Signature Scheme through Side-Channel Attacks

Abstract—This paper proposes the first side-channel attack on FALCON—a NIST Round-3 finalist for the post-quantum digital signature standard. We demonstrate a known-plaintext attack that uses the electromagnetic measurements of the device to extract the secret signing keys, which then can be used to forge signatures on arbitrary messages. The proposed attack targets the unique floating-point multiplications within FALCON’s Fast Fourier Transform through a novel extend-and-prune strategy that extracts the sign, mantissa, and exponent variables without false positives. The extracted floating-point values are then mapped back to the secret key’s coefficients. Our attack, notably, does not require pre-characterizing the power profile of the target device or crafting special inputs. Instead, the statistical differences on obtained traces are sufficient to successfully execute our proposed differential electromagnetic analysis. The results on an ARM-Cortex-M4 running the FALCON NIST’s reference software show that approximately 10k measurements are sufficient to extract the entire key

A Hardware-Software Co-Design for the Discrete Gaussian Sampling of FALCON Digital Signature

Sampling random values from a discrete Gaussian distribution with high precision is a major and computationally intensive operation of upcoming or existing cryptographic standards. FALCON is one such algorithm that the National Institute of Standards and Technology chose to standardize as a next-generation, quantum-secure digital signature algorithm. The discrete Gaussian sampling of FALCON has both flexibility and efficiency needs—it constitutes 72% of total signature generation in reference software and requires sampling from a variable mean and standard deviation. Unfortunately, there are no prior works on accelerating this complete sampling procedure. In this paper, we propose a hardware-software co-design for accelerating FALCON’s discrete Gaussian sampling subroutine. The proposed solution handles the flexible computations for setting the variable parameters in software and executes core operations with low latency, parameterized, and custom hardware. The hardware parameterization allows trading off area vs. performance. On a Xilinx SoC FPGA Architecture, the results show that compared to the reference software, our solution can accelerate the sampling up to 9.83× and the full signature scheme by 2.7×. Moreover, we quantified that our optimized multiplier circuits can improve the throughput over a straightforward implementation by 60%

Group Handover for Drone-Mounted Base Stations

The widespread use of new technologies such as the Internet of things (IoT) and machine type communication(MTC) forces an increase on the number of user equipments(UEs) and MTC devices that are connecting to mobile networks. Inherently, as the number of UEs inside a base station's (BS) coverage area surges, the quality of service (QoS) tends to decline. The use of drone-mounted BS (UxNB) is a solution in places where UEs are densely populated, such as stadiums. UxNB emerges as a promising technology that can be used for capacity injection purposes in the future due to its fast deployment. However, this emerging technology introduces a new security issue. Mutual authentication, creating a communication channel between terrestrial BS and UxNB, and fast handover operations may cause security issues in the use of UxNB for capacity injection. This new protocol also suggests performing UE handover from terrestrial to UxNB as a group. To the best of the authors' knowledge, there is no authentication solution between BSs according to LTE and 5G standards. The proposed scheme provides a solution for the authentication of UxNB by the terrestrial BS. Additionally, a credential sharing phase for each UE in handover is not required in the proposed method. The absence of a credential sharing step saves resources by reducing the number of communications between BSs. Moreover, many UE handover operations are completed in concise time within the proposed group handover method

RevEAL: Single-Trace Side-Channel Leakage of the SEAL Homomorphic Encryption Library

This paper demonstrates the first side-channel attack on homomorphic encryption (HE), which allows computing on encrypted data. We reveal a power-based side-channel leakage of Microsoft SEAL prior to v3.6 that implements the Brakerski/Fan-Vercauteren (BFV) protocol. Our proposed attack targets the Gaussian sampling in the SEAL’s encryption phase and can extract the entire message with a single power measurement. Our attack works by (1) identifying each coefficient index being sampled, (2) extracting the sign value of the coefficients from control-flow variations, (3) recovering the coefficients with a high probability from data-flow variations, and (4) using a Blockwise Korkine-Zolotarev (BKZ) algorithm to efficiently explore and estimate the remaining search space. Using real power measurements, the results on a RISC-V FPGA implementation of the SEAL (v3.2) show that the proposed attack can reduce the plaintext encryption security level from 2ˆ128 to 2ˆ4.4. Therefore, as HE gears toward real-world applications, such attacks and related defenses should be considered

Single-Trace Side-Channel Attacks on ω-Small Polynomial Sampling: With Applications to NTRU, NTRU Prime, and CRYSTALS-DILITHIUM

This paper proposes a new single-trace side-channel attack on lattice-based post-quantum protocols. We target the ω-small polynomial sampling of NTRU, NTRU Prime, and CRYSTALS-DILITHIUM algorithm implementations (which are NIST Round-3 finalists and alternative candidates), and we demonstrate the vulnerabilities of their sub-routines to a power-based side-channel attack. Specifically, we reveal that the sorting implementation in NTRU/NTRU Prime and the shuffling in CRYSTALS-DILITHIUM\u27s ω-small polynomial sampling process leaks information about the ‘-1’, \u270’, or ’+1\u27 assignments made to the coefficients. We further demonstrate that these assignments can be found within a single power measurement and that revealing them allows secret and session key recovery for NTRU/NTRU Prime, while reducing the challenge polynomial\u27s entropy for CRYSTALS-DILITHIUM. We execute our proposed attacks on an ARM Cortex-M4 microcontroller running the reference software submissions from NIST Round-3 software packages. The results show that our attacks can extract coefficients with a success rate of 99.78% for NTRU and NTRU Prime, reducing the search space to 2^41 or below. For CRYSTALS-DILITHIUM, our attack recovers the coefficients’ signs with over 99.99% success, reducing rejected challenge polynomials’ entropy between 39 to 60 bits. Our work informs the proposers about the single-trace vulnerabilities of their software and urges them to develop single-trace resilient software for low-cost microcontrollers

Fabrication of ethosuximide loaded alginate/polyethylene oxide scaffolds for epilepsy research using 3D-printing method

Epilepsy is a medical condition that causes seizures and impairs the mental and physical activities of patients. Unfortunately, over one-third of patients do not receive adequate relief from oral Antiepileptic Drugs (AEDs) and continue to experience seizures. In addition to that, long term usage of Antiepileptic Drugs can cause a range of side effects. To overcome this problem, the precision of 3D printing technology is combined with the controlled release capabilities of biodegradable polymers, allowing for tailored and localized AED delivery to specific seizure sites. As a result of this novel technique, therapeutic outcomes can be enhanced, side effects of AEDs are minimized, and patient-specific dosage forms can be created. This study focused on the use of ethosuximide, an antiepileptic drug, at different concentrations (10, 13, and 15 mg) loaded into 3D-printed sodium alginate and polyethylene oxide scaffolds. The scaffolds contained varying concentrations (0.25%, 0.50%, and 0.75% w/v) and had varying pores created by 3D patterning sizes from 159.86 ± 19.9 µm to 240.29 ± 10.7 µm to optimize the releasing system for an intracranial administration. The addition of PEO changed the Tg and Tm temperatures from 65°C to 69°C and from 262°C to 267°C, respectively. Cytotoxicity assays using the human neuroblastoma cell line (SH-SY5Y) showed that cell metabolic activity reached 130% after 168 h, allowing the cells to develop into mature neural cells. In vitro testing demonstrated sustained ethosuximide release lasting 2 hours despite crosslinking with 3% CaCl2. The workpaves the way for the use of ethosuximide -loaded scaffolds for treating epilepsy

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication