BFLIDS: Blockchain-Driven Federated Learning for Intrusion Detection in IoMT Networks.

The Internet of Medical Things (IoMT) has significantly advanced healthcare, but it has also brought about critical security challenges. Traditional security solutions struggle to keep pace with the dynamic and interconnected nature of IoMT systems. Machine learning (ML)-based Intrusion Detection Systems (IDS) have been increasingly adopted to counter cyberattacks, but centralized ML approaches pose privacy risks due to the single points of failure (SPoFs). Federated Learning (FL) emerges as a promising solution, enabling model updates directly on end devices without sharing private data with a central server. This study introduces the BFLIDS, a Blockchain-empowered Federated Learning-based IDS designed to enhance security and intrusion detection in IoMT networks. Our approach leverages blockchain to secure transaction records, FL to maintain data privacy by training models locally, IPFS for decentralized storage, and MongoDB for efficient data management. Ethereum smart contracts (SCs) oversee and secure all interactions and transactions within the system. We modified the FedAvg algorithm with the Kullback-Leibler divergence estimation and adaptive weight calculation to boost model accuracy and robustness against adversarial attacks. For classification, we implemented an Adaptive Max Pooling-based Convolutional Neural Network (CNN) and a modified Bidirectional Long Short-Term Memory (BiLSTM) with attention and residual connections on Edge-IIoTSet and TON-IoT datasets. We achieved accuracies of 97.43% (for CNNs and Edge-IIoTSet), 96.02% (for BiLSTM and Edge-IIoTSet), 98.21% (for CNNs and TON-IoT), and 97.42% (for BiLSTM and TON-IoT) in FL scenarios, which are competitive with centralized methods. The proposed BFLIDS effectively detects intrusions, enhancing the security and privacy of IoMT networks.

Opportunistic Sensor-Based Authentication Factors in and for the Internet of Things.

Communication between connected objects in the Internet of Things (IoT) often requires secure and reliable authentication mechanisms to verify identities of entities and prevent unauthorized access to sensitive data and resources. Unlike other domains, IoT offers several advantages and opportunities, such as the ability to collect real-time data through numerous sensors. These data contains valuable information about the environment and other objects that, if used, can significantly enhance authentication processes. In this paper, we propose a novel idea to building opportunistic sensor-based authentication factors by leveraging existing IoT sensors in a system of systems approach. The objective is to highlight the promising prospects of opportunistic authentication factors in enhancing IoT security. We claim that sensors can be utilized to create additional authentication factors, thereby reinforcing existing object-to-object authentication mechanisms. By integrating these opportunistic sensor-based authentication factors into multi-factor authentication schemes, IoT security can be substantially improved. We demonstrate the feasibility and effectivenness of our idea through illustrative experiments in a parking entry scenario, involving both mobile robots and cars, achieving high identification accuracy. We highlight the potential of this novel method to improve IoT security and suggest future research directions for formalizing and comparing our approach with existing techniques.

Network Security Prediction of Industrial Control Based on Projection Equalization Optimization Algorithm.

This paper predicts the network security posture of an ICS, focusing on the reliability of Industrial Control Systems (ICSs). Evidence reasoning (ER) and belief rule base (BRB) techniques are employed to establish an ICS network security posture prediction model, ensuring the secure operation and prediction of the ICS. This model first integrates various information from the ICS to determine its network security posture value. Subsequently, through ER iteration, information fusion occurs and serves as an input for the BRB prediction model, which necessitates initial parameter setting by relevant experts. External factors may influence the experts' predictions; therefore, this paper proposes the Projection Equalization Optimization (P-EO) algorithm. This optimization algorithm updates the initial parameters to enhance the prediction of the ICS network security posture through the model. Finally, industrial datasets are used as experimental data to improve the credibility of the prediction experiments and validate the model's predictive performance in the ICS. Compared with other methods, this paper's prediction model demonstrates a superior prediction accuracy. By further comparing with other algorithms, this paper has a certain advantage when using less historical data to make predictions.

Trustworthy High-Performance Multiplayer Games with Trust-but-Verify Protocol Sensor Validation.

Multiplayer online video games are a multibillion-dollar industry, to which widespread cheating presents a significant threat. Game designers compromise on game security to meet demanding performance targets, but reduced security increases the risk of potential malicious exploitation. To mitigate this risk, game developers implement alternative security sensors. The alternative sensors themselves become a liability due to their intrusive and taxing nature. Online multiplayer games with real-time gameplay are known to be difficult to secure due to the cascading exponential nature of many-many relationships among the components involved. Behavior-based security sensor schemes, or referees (a trusted third party), could be a potential solution but require frameworks to obtain the game state information they need. We describe our Trust-Verify Game Protocol (TVGP), which is a sensor protocol intended for low-trust environments and designed to provide game state information to help support behavior-based cheat-sensing detection schemes. We argue TVGP is an effective solution for applying an independent trusted referee capability to trust-lacking subdomains and demands high-performance requirements. Our experimental results validate high efficiency and performance standards for TVGP. We identify and discuss the operational domain assumptions of the TVGP validation testing presented here.

Perspectives of healthcare professionals and people living with HIV in dialogue: on information sharing to improve communication at the consultation.

We report on a qualitative Group Survey study involving four healthcare professionals (HCPs) and eight people living with HIV who were recipients of care in the United Kingdom (UK). The survey aimed to bring participants' perspectives into dialogue and establish consensus about how communication between HCPs delivering HIV care and their patients could be improved in the context of the routine care consultation. Responses from both parties were anonymously collated, thematically analysed, and shared back with participants in two subsequent survey rounds to support consensus-building on matters of concern and identify thematic insights. In this paper, we report three themes for informing future designs of tools and services to support communication between patients and HCPs: Patient-clinician relationship for trusted sharing; Self-reporting psychosocial information to support Whole-person care; and Perceived barriers for online trusted sharing with HCPs. Our findings highlight key areas of concern and further investigation is needed to understand how self-reported information may be meaningfully captured, interpreted and processed by HCPs in ways that are trusted by patients who voice privacy and security concerns.

Dataset explaining the comparative seasonal crop load and harvest quality of guava upon pruning strategies.

The dataset explained the details on how pruning techniques significantly affected the seasonal variations on fruit availability and edible quality of guava (Psidium guajava L.) under fluctuating sub-tropical weather conditions. The present pruning data also directed a way of enhancing lean season (off-season) harvest without sacrificing the main season yield and fruit quality. In detail, the pruning strategies included branch removal of 0 cm, 15 cm, 30 cm and 45 cm from shoot-tip once a year during spring (early March), monsoon (early June) and autumn (early September) starting with spring pruning. Over two consecutive years (2019-2020 and 2020-2021), the pruning treatments were assigned in triplicates following a randomized Complete Block Design (RCBD) where the same plants received the same treatments during observation period. Data on crop load like number of fruits and fruit yield per plant and fruit biochemical traits namely total soluble solids, titratable acidity, total sugars, vitamin C and fruit specific gravity were recorded. To assess the seasonal variations, data collection was performed continuously and grouped at quarter intervals i.e., March-May, June-August, September-November and December-February of the year. Plants under pruning produced greater number of flowers and fruits for superior yield and quality compared to non-pruned plants. Irrespective of pruning techniques, June-August and September-November quarters had superior yield over others, whereas March-May harvests retained utmost fruit quality. Considering pruning time, plants reserved maximum harvestable fruits in June-August quarter under spring pruning followed by March-May quarter for autumn pruning compared to other combinations. Moreover, fruit biochemical attributes were examined the best at March-May harvests under autumn pruning. Alongside, June-August and September-November periods exhibited superiority for yield over others when plants were pruned at 30 cm level, but 45 cm pruning had best yield at March-May quarter. Whether, fruits had notable TSS, sugars, vitamin C and specific gravity obtained during March-May period from 45 cm pruning treatment. June-August was noted to produce inferior quality fruits in guava.

Privacy preservation for federated learning in health care.

Artificial intelligence (AI) shows potential to improve health care by leveraging data to build models that can inform clinical workflows. However, access to large quantities of diverse data is needed to develop robust generalizable models. Data sharing across institutions is not always feasible due to legal, security, and privacy concerns. Federated learning (FL) allows for multi-institutional training of AI models, obviating data sharing, albeit with different security and privacy concerns. Specifically, insights exchanged during FL can leak information about institutional data. In addition, FL can introduce issues when there is limited trust among the entities performing the compute. With the growing adoption of FL in health care, it is imperative to elucidate the potential risks. We thus summarize privacy-preserving FL literature in this work with special regard to health care. We draw attention to threats and review mitigation approaches. We anticipate this review to become a health-care researcher's guide to security and privacy in FL.

Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision.

Genome-wide association studies (GWAS) serve as a crucial tool for identifying genetic factors associated with specific traits. However, ethical constraints prevent the direct exchange of genetic information, prompting the need for privacy preservation solutions. To address these issues, earlier works are based on cryptographic mechanisms such as homomorphic encryption, secure multi-party computing, and differential privacy. Very recently, federated learning has emerged as a promising solution for enabling secure and collaborative GWAS computations. This work provides an extensive overview of existing methods for GWAS privacy preserving, with the main focus on collaborative and distributed approaches. This survey provides a comprehensive analysis of the challenges faced by existing methods, their limitations, and insights into designing efficient solutions.

The effect of education level on depressive symptoms in Chinese older adults-parallel mediating effects of economic security level and subjective memory ability.

BACKGROUND: Depression in older adults needs urgent attention. Increased education level may reduce depressive symptoms in older adults, and that economic security level and subjective memory ability may also have an impact on depressive symptoms in older adults, but the mechanisms between education level and depressive symptoms in older adults are unclear. This study endeavors to investigate the parallel mediating roles of economic security level and subjective memory ability between education level and depressive symptoms in older adults. METHODS: A total of 4325 older adults people aged 60 years and above were selected from the China Family Panel Studies (CFPS) as the study population, and all data were analyzed using SPSS 25.0 software. Spearman correlation analysis was used to explore the correlation between the variables. Model 4 from the SPSS macro was used to assess the parallel mediating role of economic security level and subjective memory ability in the relationship between education level and depressive symptoms in older adults. RESULTS: Education level, economic security level, and subjective memory ability were significantly associated with depressive symptoms in older adults (p < 0.01). Educational level was a negative predictor of depressive symptoms (ß=-0.134, P < 0.001). Education level was a positive predictor of economic security level (ß = 0.467, P < 0.001) and subjective memory ability (ß = 0.224, P < 0.001). Education level, economic security level, and subjective memory ability were significant negative predictors of depressive symptoms (ß= -0.039, P < 0.05; ß= -0.122, P < 0.001; ß= -0.169, P < 0.001). Education level influenced depressive symptoms through parallel mediating effects of economic security level and subjective memory ability, with mediating effects accounting for 42.70% and 28.30% of the total effect, respectively. CONCLUSIONS: Education level not only directly influences depressive symptoms in older adults, but also indirectly through the economic security level and subjective memory ability. Educational level can reduce depressive symptoms in older adults by increasing their economic security level and enhancing their subjective memory ability. The findings of this study emphasize the importance of improving the educational level of the population as it affects people's mental health in old age.

The prevalence of physical and verbal violence among emergency medicine physicians in military hospitals vs non-military hospitals, Jeddah, Saudi Arabia: multi-center cross-sectional study.

INTRODUCTION: In healthcare settings, physical and verbal attacks are commonly encountered in the workplace among healthcare providers. Patients and patients' relatives and friends have been reported to be the perpetrators of workplace violence. Among all healthcare settings, emergency department (ED) have been designated as high-risk settings for violence, where more than one-quarter of emergency physicians reported that they were victims of physical assault. This study aimed to report the prevalence of workplace violence against emergency medicine physicians in military and non-military hospitals in Jeddah city. METHODOLOGY: A cross-sectional design has been used in this study. An electronic questionnaire was developed through the Google Form Platform and it included demographic data, the occurrence of verbal or physical violence in the workplace to participants, how many times they experienced this violence, the time of incidents, the location either inside or outside the hospital, whether the perpetrators were mostly patients, patient families, or friends, and whether they reported any violence or not. Categorical variables were used to describe frequencies and percentages, while descriptive statistics such as mean and 95% Confidence Interval (95% CI) were used to summarize the scale variables. P < 0.05 was considered for statistically significant differences. RESULTS: Among the 100 participants, 76 experienced either physical or verbal violence, or both. The remaining 24 did not experience any sort of violence. 83% of the physicians who have been physically violated were working in non-military hospitals. Of the 72 participants who had experienced verbal violence, 51 (70.8%) were working in a non-military hospital, while 21 (29.2%) were in a military hospital. The most common reason for not reporting was that the participants felt that reporting the violence incidence was useless. Moreover, 92% of participants chose "Train healthcare workers to deal with violent attacks" as a suggested helpful factor in decreasing the number of work-related violence. In addition, "Education of the public" and "Raising awareness of healthcare workers" were chosen as helpful factors as well by 91% and 90% of participants, respectively. CONCLUSION: This revealed that physicians in non-military hospitals experience higher levels of violence compared to their military counterparts. However, it is concerning that instances of violence are substantially under-reported across both military and non-military healthcare facilities.

Determinants of food insecurity among adults residing in peri-urban municipal settings in Flanders, Belgium.

Food insecurity is a global public health issue associated with noncommunicable diseases. Individual factors are strongly associated with food insecurity, but there is limited literature on the broader impact of both the social and food environments on food insecurity in non-English speaking European countries, given that the research was predominantly conducted in Anglophone settings. In addition, these studies have mostly been conducted in urban areas. Therefore, this study aimed to identify the main determinants of food insecurity among adults living in peri-urban areas in Flanders, Belgium. Data on socio-demographics, neighborhood social cohesion, social isolation, and perceived food environments were collected from 567 adults through a self-administered questionnaire, and objective data on the food environment were obtained through (commercial) databases on food outlets. Food insecurity was measured using the USDA Household Food Security Survey Module. Multivariable logistic regression models revealed that lower socioeconomic status (OR14.11,95%CI:4.72;61.11), reasonable (OR4.16,95%CI: 2.11;8.47) to poor and very poor (OR6.54,95%CI: 2.11;8.47) subjective health status, and living in private (OR7.01, 95% CI:3.0;17.0) or government-assisted (OR6.32,95%CI: 3.13;13.26) rental housing significantly increased the odds of food insecurity. Additionally, residing in a neighborhood with low (OR2.64, 95% CI:1.13;6.26) to medium (OR2.45,95% CI:1.21;5.11) social cohesion, having a neutral opinion (OR4.12,95%CI:1.51;11.54) about the availability of fruit and vegetables in one's neighborhood, and having an opinion that fruit and vegetable prices are too expensive (OR5.43,95% CI 2.26;14.4) significantly increased the odds of experiencing food insecurity. This study underscores the need for policies that consider factors related to social and food environments, in addition to individual factors, to effectively address food insecurity.

The Association of Socio-Economic Factors and Indigenous Crops on the Food Security Status of Farming Households in KwaZulu-Natal Province.

Indigenous crops have been proposed as part of a solution for household food security and sustainable farming systems. However, they have been overlooked and underutilised by households and farmers despite their potential contribution to household food security. The objective of this paper was to determine the association of socio-economic factors and indigenous crops with the household food security of farming households. About 260 farming households were selected using a simple random sampling procedure. The food security status was measured through the use of the Household Food Insecurity Access Scale (HFIAS). The Chi-square test and extended ordered probit regression model assessed the relationship of socio-economic factors and indigenous crops with household food security status. The results from the HFIAS showed that farming households were largely in the mildly and moderately food-insecure categories, with 34.2% and 36.2% of the sampled farmers found in these categories, respectively. The Chi-square test showed a statistically significant relationship between food security status and socio-economic factors. Young men and everyone were perceived to be the ones likely to consume indigenous crops. Consumption of indigenous crops was perceived to be associated with food security. The results also showed that farming experience is likely to positively contribute to the food security status of the farming households. Selling indigenous crops in a formal market is perceived to be associated with food security compared to selling in an informal market. This study concludes that consuming indigenous crops is likely associated with improved food security. Identifying an appropriate market for sales of indigenous crops is imperative. Government, extension officers, and nutritionists must conduct training workshops to encourage households to grow, market and buy indigenous crops. Government and policymakers need to include indigenous crops in the national food and nutrition security policy and create formal markets for indigenous crops.

Analysis of the Contribution of Home Gardens to Household Food Security in Limpopo Province, South Africa.

Addressing food security is one of the national priorities in South Africa, enshrined under the country's constitution, yet there is a growing percentage of households struggling to meet their food requirements. Food insecurity and malnutrition remain severe problems in rural communities and can be addressed through home gardening. This study aimed to assess the contributions of home gardens to food security in Limpopo Province. This study employed a quantitative research methodology. A total of 2043 rural households were selected using multistage stratified random sampling. The Household Food Insecurity Access Scale (HFIAS) was used to measure household food insecurity levels of home garden participants. Results showed that 46% of participants were food secure, 24% were severely food insecure, 17% were moderately food insecure and 13% were mildly food insecure. The results from the endogenous switching Poisson regression model showed that gender, household size, wage/salary, access to land, agriculture-related assistance and market distance had a positive influence on household food security of home garden participants. On the other hand, employment status and receiving any social relief had a negative association with household food security of home garden participants. The results also showed that employment status had a positive influence on the food security of home garden non-participants, while education, access to land, wage/salary and age had a negative influence. The results from average treatment effects (ATEs) showed that households that participated in home garden production had a negative and significant (p-value < 0.05) impact on household food insecurity. This study concludes that involvement in home gardening improves food security. Household food security can be enhanced through agricultural training and skills enhancement directed at increasing participation in home gardening in rural areas, thus addressing income and food security challenges. Agricultural education needs to be introduced and facilitated at school levels so that an understanding of food systems, nutrition and food security can be attained from younger age groups.

Mitigating cold stress in rice: a study of genotype performance and sowing time.

Rice (Oryza sativa L.) is an essential food for half of the global population and is vital in maintaining global food security. Climate change, increasing population and recent incident of COVID pandemic has generated financial burden and threaten the global food security. Due to theses factors rice cultivation also has to face significant challenges. frequent weather changes pose a considerable challenge to agricultural planning, which was previously relaying on consistent seasonal variations. In this context, rice cultivation is particularly sensitive to cold, where its development and productivity inhibited by low temperatures (< 18 °C). Developing rice varietes with low temprature tolerence and good yield potential is one of the major goals of current breeding efforts of plant scientists. For this purpose, short duration and early rice varieties are most favorable to avoid cold stress and yield more in less number of days. this study was designed to investigate the effect of low temperatures on different rice varieties. the study was designed to identify low temprature tolerent genotypes with early and regular cultivation. For this, thirty-four genotypes were evaluated in two gorwing seasons (2018-2019) with four different sowing times. Statistically sowing time showed significant interaction between all yield contributing parameters. The data indicate that exposure to low temperatures during the reproductive phase prolongs the maturation period of the crop, also length of the panicle and the fertility of the spikelets drops, resulting in a significant decrease in the production of sensitive varieties. Some varieties are more sensitive to cold stress compared to others. In the Egyptian context, Giza176, Sakha104, and Sakha107 are recommended for early cultivation, while the genotypes Giza 179, Sakha101, Sakha104, and GZ 9730-1-1-1-1 are indicated for the normal cultivation period. The Sakha104 variety is particularly notable, as it is recommended for both purposes. In addition, the data obtained in this study provide valuable information for selecting rice varieties suitable for double cropping in the North Delta of Egypt. This study also contributes to the existing literature, providing insights into the resilience of rice cultivation in the face of climate change.

Parental Involvement and Children's Subjective Well-Being: Mediating Roles of the Sense of Security and Autonomous Motivation in Chinese Primary School Students.

Parental involvement may influence the subjective well-being of primary school students, but the specific mechanisms remain unclear. This study explores the mechanisms between parental involvement and primary school students' subjective well-being. The current study investigated 340 fifth and sixth grade students and their parents from a primary school using the Parental Education Involvement Behavior Scale, the Well-Being Scale, the Sense of Security Scale, and the Learning Self-Regulation Scale. We found that (1) sense of security plays a complete mediating role between parental involvement and primary school students' subjective well-being; (2) autonomous motivation has a marginal mediating effect between parental involvement and subjective well-being of primary school students; and (3) sense of security and autonomous motivation play a chain mediating role between parents' educational involvement and primary school students' well-being. In conclusion, parental involvement appears to contribute to primary school children's subjective well-being, and this effect may be mediated individually and sequentially by the children's sense of security and autonomous motivation.

Association between food insecurity and long COVID in adults from southern Brazil: findings of the PAMPA cohort.

BACKGROUND: Social and economic factors, such as food insecurity, contribute to long coronavirus disease (COVID). During the pandemic, a significant rise in food insecurity was observed, both in Brazil and worldwide. We aimed to investigate the association between food insecurity and long COVID in Brazilian adults. METHODS: Cross-sectional study nested within the Prospective study About Mental and Physical Health in Adults (PAMPA) Cohort. Participants completed an online questionnaire in June 2022. We assessed food insecurity using the Brazilian Scale of Food Insecurity. Long COVID was defined as any post-coronavirus disease 2019 symptoms that persisted for at least 3 months after infection. RESULTS: A total of 956 participants were included (74.0% female, median age 36 (Interquartile Range [IQR] (29-45.7). The prevalence of food insecurity was 29.4%, and 77.8% had long COVID. Food insecurity was associated with an increased probability of long COVID (prevalence ratio [PR]: 1.15, 95% confidence interval [CI]: 1.08-1.22). Participants in food insecurity situations had a higher likelihood of experiencing neurological (PR: 1.19, 95% CI: 1.10-1.28), pulmonary (PR: 1.33, 95% CI: 1.17-1.52) and gastrointestinal (PR: 1.57, 95% CI: 1.31-1.88) symptoms after infection. CONCLUSIONS: Food insecurity was associated with long COVID. Governments must plan public policies to mitigate the effects of long COVID and food insecurity.

Exploring the viability of anti-microbial, superhydrophobic jute bags as an approach to sustainable food packaging system.

Jute in food packaging offers several advantages, including cost-effectiveness, biodegradability, renewability, and low environmental impact. Nevertheless, its hydrophilic characteristic makes it susceptible to airborne humidity and precipitation moisture. We combated this by chemically treating jute to make it water-resistant. The coated jute (WCA = âˆ¼162°) exhibits high mechanical endurance against exposure to air (>1 month), ultrasonic washing (6 h), brush scrubbing (>50 cycles), and mutual abrasion (>150 cycles), along with good thermal stability. During a 2-month experiment involving seed storage in an RH of 85%, wheat grains stored in the coated bag showed 8.08% less moisture content than that stored in control. Furthermore, the preserved grains in the control jute exhibited altered colour, texture, and fungal development. Additionally, compared to the control, the coated jute delivers >50% bacterial growth reduction in 48 h. The proposed jute offers a sustainable packaging solution that promotes eco-friendly practices and reduces plastic waste.

Evaluation of Food Security in North China Based on Food Production Level.

This paper focuses on county-level grain production and food security in North China; selects 17 indicators from both climatic conditions and human activities; applies yield fluctuation coefficients, spatial econometric modelling, the random forest method, and factor analysis to study the characteristics of grain production in North China and the influencing factors; and evaluates the situation of food security in North China based on grain production capacity. The following results were obtained: (1) The spatial and temporal changes in grain production located in North China from 2000 to 2020 are obvious. The grain output in North China from 2000 to 2020 maintains fluctuating growth at a rate of 0.38 × 1011 kg/10a. The east and south are the key areas for grain production in North China. Grain output was relatively stable except for 2003. with the cold spots of grain production being mainly in the northwestern area and the hot spots in the central and southern areas. (2) The changes in grain production in North China from 2000 to 2020 were less affected by climate and mainly influenced by human activity indicators. (3) As time progresses, the area of food shortage zones decreases in size, becoming evenly distributed and dispersed from the initial concentration in northern Hebei and most of Shanxi; the change in the supply-demand equilibrium zones is not obvious; and the area of surplus grain zones increases markedly in size, with a tendency to expand from the south and centre of the study area to the west and north. The grain production capacity of counties in the northwest and north is generally low, and even counties located in surplus grain areas have potential food security risks. However, in the east and south, due to their high grain production capacity, the per capita grain supply situation may be alleviated even in counties located in grain shortage areas. This study can deepen the understanding of the characteristics of food production in North China and enrich the research on food security. Analyses of factors influencing food production will improve a deeper understanding of food security. Food security evaluation based on food production capacity will contribute to a more precise and comprehensive understanding of the food security pattern in North China.

Development and Validation of a High-Performance Liquid Chromatography Diode Array Detector Method to Measure Seven Neonicotinoids in Wheat.

Neonicotinoids (NEOs), used as insecticides against aphids, whiteflies, lepidopterans, and beetles, have numerous detrimental impacts on human health, including chronic illnesses, cancer, infertility, and birth anomalies. Monitoring the residues in food products is necessary to guarantee public health and ecological balance. The present work validated a new method to measure seven neonicotinoid insecticides (acetamiprid ACT, clothianidin CLT, dinotefuran DNT, imidacloprid IMD, nitenpyram NTP, thiacloprid TCP, and thiamethoxan THT) in wheat. The analytical procedure was based on simple and fast wheat sample cleanup using solid-phase extraction (SPE) to remove interferents and enrich the NEOs, alongside the NEOs' separation and quantification by reverse-phase chromatography coupled with a diode array detector (DAD). The validation process was validated using the accuracy profile strategy, a straightforward decision tool based on the measure of the total error (bias plus standard deviation) of the method. Our results proved that, in the future, at least 95% of the results obtained with the proposed method would fall within the ±15% acceptance limits. The test's cost-effectiveness, rapidity, and simplicity suggest its use for determining the levels of acetamiprid, clothianidin, dinotefuran, imidacloprid, nitenpyram, thiacloprid, and thiamethoxam in routine analyses of wheat.