SoK: A Systematic Review of TEE Usage for Developing Trusted Applications

Trusted Execution Environments (TEEs) are a feature of modern central processing units (CPUs) that aim to provide a high assurance, isolated environment in which to run workloads that demand both confidentiality and integrity. Hardware and software components in the CPU isolate workloads, commonly referred to as Trusted Applications (TAs), from the main operating system (OS). This article aims to analyse the TEE ecosystem, determine its usability, and suggest improvements where necessary to make adoption easier. To better understand TEE usage, we gathered academic and practical examples from a total of 223 references. We summarise the literature and provide a publication timeline, along with insights into the evolution of TEE research and deployment. We categorise TAs into major groups and analyse the tools available to developers. Lastly, we evaluate trusted container projects, test performance, and identify the requirements for migrating applications inside them.Comment: In The 18th International Conference on Availability, Reliability and Security (ARES 2023), August 29 -- September 01, 2023, Benevento, Italy. 15 page

Comparison between the values of intra-ocular pressure measured by Goldmann applanation tonometer and Air-Puff non-contact tonometer and their relationship with central corneal thickness

Objective: Glaucoma is a sight threatening disorder. Measuring the IOP with accuracy plays a pivotal role in diagnosing and monitoring glaucoma. The purpose of this study was to compare the values of non-contact tonometer; air-puff and GAT (Goldmann Applanation Tonometer) along with its correlation to central corneal thickness (CCT), in various IOP (intra-ocular pressure) groups. Methods: Cross-sectional, prospective study. 311 patients were enrolled in this study. IOP was taken in all patients with APT and GAT. CCT was also measured. Data was analyzed and correlated with the help of Bland-Altman, Pearson correlation and intraclass correlation analysis regarding APT, GAT and CCT, using SPSS 24.0 software. Results: The median IOP measured by APT and GAT was 14mmHg (range: 37) and 12mmHg (range: 16) where as the median CCT was 534µ (range: 44), respectively. At low (<10mm of Hg) and normal IOP (10-20mm of Hg) both instruments showed similar results but at higher IOP (21-30mm of Hg) GAT is concluded more accurate (P=<0.001). Conclusion: GAT showed a high agreement with APT over a wide range of IOP. However, at moderate and higher group of IOP, APT revealed overestimation of IOP compared to GAT. CCT also plays a significant role. Continuous..

Added value upshot of barley amalgamation in wheat flour to boost the physico-chemical quality attributes of flat bread

This study was directed to incorporate barley flour derived from hulled barley variety “Jau-17” in the whole wheat flour to develop chapatti. Five different samples of flour blend for chapatti production were made by adding barley (at the rate of 0, 5, 10, 15, 20 and 25%) into the whole wheat flour and their proximate analyses and other quality variables (protein, fat, ash, gluten, energy, phytates and beta-glucan contents) were determined. The same analyses were also performed for the chapattis made from the flour of these blends including the evaluation of sensory parameters for product acceptability. A significant increase in protein, ash, energy and beta-glucans content and a significant decrease in gluten, carbohydrates and phytates were observed in flour blends. A similar trend was observed in chapatti characteristics. Fat contents increased, however, in a non-significant manner in flour blends and chapati. Sensory attributes illustrated that chapatti developed from 20% barley incorporation into wheat flour had good nutritional quality and acceptability

An Atypical Case of Silent Aortic Dissection in a Peritoneal Dialysis Patient: A Case Report and Review of Literature

BACKGROUND: Aortic dissection presents with acute chest or back pain and is associated with high mortality. We present a case of aortic dissection with an atypical presentation in a peritoneal dialysis patient, and the challenges met with peritoneal dialysis. CASE REPORT: A 53-year-old African American male presented with progressively worsening exertional dyspnea and orthopnea for 3 days without any history of chest pain. His chest x-ray showed mild pulmonary edema. He was admitted with a diagnosis of heart failure. Bedside echocardiogram revealed severe aortic regurgitation and concern for possible aortic dissection. Computed tomography of chest with contrast showed Stanford type-A aortic dissection extending from the aortic valve to the level of the left subclavian artery. Emergent surgery was performed. Postoperatively, the patient was managed in surgical and trauma intensive care unit to keep the blood pressure in the desired range. Initially, he was started on continuous veno-venous hemodialysis and later on transitioned to intermittent hemodialysis. He was switched back to peritoneal dialysis after 6 weeks of surgery. CONCLUSIONS: Atypical presentation of a silent aortic dissection without chest pain in the setting of renal failure and other co-morbidities emphasizes that dialysis patients are different from the general population. Sometimes the management needs to be modified from the conventional ways to achieve the high level of success

Meta-Analysis comparing outcomes and need for renal replacement therapy of Transcatheter aortic valve implantation versus surgical aortic valve replacement

Acute kidney injury (AKI) is commonly associated with aortic valve replacement. Surgical aortic valve replacement (SAVR) is a known risk factor for AKI but little is known about the short- and long-term effects of transcatheter aortic valve implantation (TAVI). The purpose of our analysis is to identify the short- and long-term effect of TAVI on renal out-comes. We searched Medline and PUB MED from January 1, 2000 to November 6, 2017for randomized control trials (RCTs) comparing TAVI to SAVR in patients with severe aortic stenosis. Three hundred sixty-nine trials were identified, 6 RCTs were included in our analysis. RevMan version 5.3 was used for statistical analysis. Heterogeneity is calculated using I2statistics. Primary outcomes were AKI within 30 days and 1 year of TAVI, and requirement for renal replacement therapy. We included 5,536 patients (2,796 inTAVI and 2,740 in SAVR arm) from 6 RCTs. Baseline characteristics were similar. There was reduced incidence of AKI at 30 days of TAVI compared with SAVR, 57 versus 133(odds ratio [OR] 0.40, confidence interval [CI] 0.28 to 0.56, p \u3c0.00001, I2= 7%) with no difference at 1 year (OR 0.65, CI 0.32 to 1.32, p = 0.23, I2= 76%) and need for renal replacement therapy OR 0.95, CI 0.50 to 1.80, p = 0.87, I2= 0%). The permanent pacemaker was more frequent in the TAVI arm compared with SAVR arm, 379 versus 110, (OR 3.75, CI 1.67 to 8.42, p = 0.001, I2= 89%). In conclusion, TAVI is associated with a reduction inAKIs at 30 days despite the exposure to contrast and a higher incidence of new permanent pacemaker placement

Real-Time DDoS Attack Detection System Using Big Data Approach

Currently, the Distributed Denial of Service (DDoS) attack has become rampant, and shows up in various shapes and patterns, therefore it is not easy to detect and solve with previous solutions. Classification algorithms have been used in many studies and have aimed to detect and solve the DDoS attack. DDoS attacks are performed easily by using the weaknesses of networks and by generating requests for services for software. Real-time detection of DDoS attacks is difficult to detect and mitigate, but this solution holds significant value as these attacks can cause big issues. This paper addresses the prediction of application layer DDoS attacks in real-time with different machine learning models. We applied the two machine learning approaches Random Forest (RF) and Multi-Layer Perceptron (MLP) through the Scikit ML library and big data framework Spark ML library for the detection of Denial of Service (DoS) attacks. In addition to the detection of DoS attacks, we optimized the performance of the models by minimizing the prediction time as compared with other existing approaches using big data framework (Spark ML). We achieved a mean accuracy of 99.5% of the models both with and without big data approaches. However, in training and testing time, the big data approach outperforms the non-big data approach due to that the Spark computations in memory are in a distributed manner. The minimum average training and testing time in minutes was 14.08 and 0.04, respectively. Using a big data tool (Apache Spark), the maximum intermediate training and testing time in minutes was 34.11 and 0.46, respectively, using a non-big data approach. We also achieved these results using the big data approach. We can detect an attack in real-time in few milliseconds

Assessments of Roof-Harvested Rainwater in Disctrict Dir Lower, Khyber Pakhtunkhwa Pakistan

The main objective of this study was to assess the quality and quantity of roof-harvested rainwater to overcome the water shortage problem in the study area. We also aimed to find health hazards associated with rainwater in the study area. For this purpose, rainwater samples were collected from five sites in the study area. The samples were analyzed using standard methods of the World Health Organization and the American Public Health Association in a laboratory. The analysis showed that all the physicochemical parameters were within the permissible limits of the WHO’s guidelines except pH, turbidity, and some trace metals such as iron (Fe) and lead (Pb). The mean values of pH range from 5.18 to 6.26, indicating slight acidity, while the highest mean turbidity was found at 5.77 NTU. Similarly, the highest mean concentrations of Fe and Pb were 0.95 mg/L and 0.056 mg/L, respectively, which was above the permissible limit of the WHO’s guidelines for drinking water. The annual rainwater-harvesting potential was assessed using the formula annual rainfall × roof area× runoff coefficient. The annual rainwater-harvesting potential of the study area was 56.803 L per household. At the same time, the average monthly rainwater-harvesting potential was 4733 L in the study area. This shows the potential for roof-harvested rainwater in the study area. A risk assessment of heavy metals showed that the rainwater of the study area is safe and does not pose any risk. This study concludes that rainwater is suitable for drinking and other domestic consumption if proper care is taken to clean the roof area and storage system and divert the first flush from the storage system

Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study an international prospective cohort study

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care. We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care