IoT Sentinel: Automated Device-Type Identification for Security Enforcement in IoT

With the rapid growth of the Internet-of-Things (IoT), concerns about the security of IoT devices have become prominent. Several vendors are producing IP-connected devices for home and small office networks that often suffer from flawed security designs and implementations. They also tend to lack mechanisms for firmware updates or patches that can help eliminate security vulnerabilities. Securing networks where the presence of such vulnerable devices is given, requires a brownfield approach: applying necessary protection measures within the network so that potentially vulnerable devices can coexist without endangering the security of other devices in the same network. In this paper, we present IOT SENTINEL, a system capable of automatically identifying the types of devices being connected to an IoT network and enabling enforcement of rules for constraining the communications of vulnerable devices so as to minimize damage resulting from their compromise. We show that IOT SENTINEL is effective in identifying device types and has minimal performance overhead

Privacy-preserving data sharing via probabilistic modeling

Differential privacy allows quantifying privacy loss resulting from accession of sensitive personal data. Repeated accesses to underlying data incur increasing loss. Releasing data as privacy-preserving synthetic data would avoid this limitation but would leave open the problem of designing what kind of synthetic data. We propose formulating the problem of private data release through probabilistic modeling. This approach transforms the problem of designing the synthetic data into choosing a model for the data, allowing also the inclusion of prior knowledge, which improves the quality of the synthetic data. We demonstrate empirically, in an epidemiological study, that statistical discoveries can be reliably reproduced from the synthetic data. We expect the method to have broad use in creating high-quality anonymized data twins of key datasets for research.Peer reviewe

Telecobalt Machine Beam Intensity Modulation with Aluminium Compensating Filter Using Missing Tissue Approach

Introduction: The present study aimed to generate intensity-modulated beams with Aluminium compensating filters for a conventional telecobalt machine based on the outputs of a treatment planning system (TPS) performing forward planning and cannot simulate directly the compensating filter. Materials and Methods: In order to achieve the beam intensity modulation during treatment planning with the TPS, we used a bolus placed on the surface of a tissue-equivalent phantom. The treatment plans replicated on the telecobalt machine with the bolus were represented with compensating filters placed at a certain distance from the phantom surface. An equation was proposed for the conversion of the bolus thickness to the compensating filter thickness such that any point within the phantom would receive the planned dose. Correction factors were introduced into the proposed equation to account for the influences of field size, treatment depth, and applied bolus thickness. The proposed equation was obtained based on the analyses of empirical data measured in a full scatter water phantom with and without the compensating filter.  Results: According to the results, the dosimetric verification of the proposed approach outputs in a solid water phantom with calibrated Gafchromic EBT2 films were comparable to that of the TPS with deviation of ±4.73% (mean: 2.98±1.05%). Conclusion: As the findings of the present study indicated, the discrepancy between the measured doses and TPS-estimated doses was within the tolerance of ±5%, which is recommended for dose delivery in external beam radiotherapy. Therefore, the proposed approach is recommended for clinical application

Differentially private Bayesian learning on distributed data

Many applications of machine learning, for example in health care, would benefit from methods that can guarantee privacy of data subjects. Differential privacy (DP) has become established as a standard for protecting learning results. The standard DP algorithms require a single trusted party to have access to the entire data, which is a clear weakness, or add prohibitive amounts of noise. We consider DP Bayesian learning in a distributed setting, where each party only holds a single sample or a few samples of the data. We propose a learning strategy based on a secure multi-party sum function for aggregating summaries from data holders and the Gaussian mechanism for DP. Our method builds on an asymptotically optimal and practically efficient DP Bayesian inference with rapidly diminishing extra cost.Peer reviewe

A systematic study of the effect of graphene oxide and reduced graphene oxide on the thermal degradation behavior of acrylonitrile-butadiene rubber in air and nitrogen media

Thermal degradation of acrylonitrile-butadiene rubber (NBR)-graphene oxide (GO)/reduced graphene Oxide (G) composites (NBR-GO/G) was studied in air O2(g) and nitrogen N2(g) media at ∼800°C, using Thermal Gravimetric Analysis (TGA/DTG). The char yield of the composites was high the in N2(g) medium. This was associated with lower weight loss (%) and higher maximum degradation temperatures, Tmax(°C). Doyle simple kinetic approach was used for the first time to estimate the degradation kinetics of the NBR-GO/G composites and large amounts of activation energy Ea (KJ/mol) was observed, particularly for the NBR-GO composites. In O2(g) medium, severe degradation of NBR occurred irrespective of the GO/G-filler content. This suggested that insignificant char yield was produced to protect the scission of the NBR backbone, as decomposition of the main chain seemed to have been accelerated by the high oxygenated moieties (C–O–C, –O–C=O and O–H) decorating GO/G-sheets. For instance, NBR showed ∼89, ∼21 and ∼86 % weight residue, Wr (%) than G0.1, G0.5 and G1 respectively and ∼154, ∼350, ∼92 % higher than the respective GO0.1, GO0.5 and GO1 samples. Although, NBR-G recorded higher Wr(%) than NBR-GO, NBR-GO generally slowed the degradation of NBR than NBR-G composites, possibly due to the presence of high concentration of interactions (NBR—Sx—GO—S—NBR and NBR—O—Hσ+—N σ−—C—NBR) which raised the Ea (KJ/mol) barrier for decomposition. The high thermal stability and compression set (%) properties of NBR-GO/G composites obtained as compared to pure NBR indicated that solution processing techniques used in this current work was very effective than those compounded with melt mixing methods or with GO/G-functionalized nanoparticles. Therefore, this present study provides insights on tailoring rubber-graphene based materials for thermally harsh and high pressure applications such as; oil/gas drilling hose, oil/gas seals, gasket and tire tread materials

IoT Sentinel Demo: Automated Device-Type Identification for Security Enforcement in IoT

The emergence of numerous new manufacturers producing devices for the Internet-of-Things (IoT) has given rise to new security concerns. Many IoT devices exhibit security flaws making them vulnerable for attacks and manufacturers have difficulties in providing appropriate security patches to their products in a timely and user-friendly manner. In this paper, we present our implementation of IoT Sentinel, which is a system aimed at protecting the user's network from vulnerable IoT devices. IoT Sentinel automatically identifies vulnerable devices when they are first introduced to the network and enforces appropriate traffic filtering rules to protect other devices from the threats originating from the vulnerable devices

Cost of inappropriate prescriptions for uncomplicated malaria in Ghana

Abstract Background Malaria remains a common course of morbidity in many sub-Saharan African countries. While treatment options have improved in recent times, inappropriate prescription seems conventional among providers, increasing the burden on patients and society. This study examined the cost of inappropriate prescriptions for uncomplicated malaria treatment in Ghana. Methods This study used retrospective data collected from January to December 2016 in 27 selected facilities, under different ownership in three regions of the country, mainly Volta, Upper East and Brong Ahafo. Stratified random sampling technique was used to extract 1625 outpatient folders of patients diagnosed and treated for malaria. Two physicians independently reviewed patient folders according to the stated diagnoses. Malaria prescriptions were described as inappropriate when they do not adhere to the standard treatment guidelines. The economic cost was mainly treatment cost which was sourced as medication cost. Total and average costs for country were calculated using sample estimates and the total number of uncomplicated malaria cases that received inappropriate prescriptions. Results The study revealed that patients received an average of two prescriptions per malaria episode. Artemether-lumefantrine (AL) was the major malaria medication (79.5%) prescribed to patients. Other medications usually antibiotics and vitamins and minerals were included in the prescription. More than 50% of prescribers did not follow the guidelines for prescribing medications to clients. By facility type, inappropriate prescription was high in the CHPS compounds (59.1%) and by ownership, government (58.3%), private (57.5%) and mission facilities (50.7%). Thus, about 55% of malaria prescriptions were evaluated as inappropriate during the review period, which translates into economic cost of approximately US$4.52 million for the entire country in 2016. The total cost of inappropriate prescription within the study sample was estimated at US$1,088.42 while the average cost was US$1.20. Conclusion Inappropriate prescription for malaria is a major threat to malaria management in Ghana. It presents a huge economic burden to the health system. Training and strict enforcement of prescribers’ adherence to the standard treatment guideline is highly recommended

Rabies: knowledge, attitudes and practices in the Suhum municipality of Ghana

Aim: The world is racing behind time to get dog-mediated human rabies eradicated by 2030. In response, Ghana has developed a rabies control strategy that awaits implementation. The Ghana chapter of Rabies in West Africa piloted a 3-year One Health rabies control programme in Suhum Municipality of the Eastern Region, Ghana. Questionnaires were administered as part of the exercise to gather information on local rabies-related perceptions and practices, with the aim of identifying knowledge, attitude, and practice gaps that may antagonise control efforts and endanger human life.Methods: A cross-sectional study was conducted from March to November 2020. The study involved 316 conveniently sampled households (individual per household) from three randomly selected sub-municipalities in Suhum Municipality. Data were analysed with IBM SPSS version 26.Results: Of the 316 households interviewed, 82% (n = 259) of respondents were aware of rabies, of which 78.8% (n = 204) were found to have good knowledge about rabies. Rabies awareness was significantly associated with age (P = 0.004), sex (P = 0.042), and level of education (P = 0.0405). Although a majority (76.8%) of dog bite victims reported to the hospital, only 7.1% practiced wound cleansing while a significant number (32.2%) were involved in several myth-laden traditional remedies.Conclusion: This study found that most of the respondents are aware and have good knowledge about rabies. However, their practices in disease prevention and control were poor. Continued and strengthened education through One-Health collaboration of stakeholders and the cooperation of the local community will be required for effective rabies control

Comparative efficacy of low-dose versus standard-dose azithromycin for patients with yaws: a randomised non-inferiority trial in Ghana and Papua New Guinea

Summary: Background: A dose of 30 mg/kg of azithromycin is recommended for treatment of yaws, a disease targeted for global eradication. Treatment with 20 mg/kg of azithromycin is recommended for the elimination of trachoma as a public health problem. In some settings, these diseases are co-endemic. We aimed to determine the efficacy of 20 mg/kg of azithromycin compared with 30 mg/kg azithromycin for the treatment of active and latent yaws. Methods: We did a non-inferiority, open-label, randomised controlled trial in children aged 6–15 years who were recruited from schools in Ghana and schools and the community in Papua New Guinea. Participants were enrolled based on the presence of a clinical lesion that was consistent with infectious primary or secondary yaws and a positive rapid diagnostic test for treponemal and non-treponemal antibodies. Participants were randomly assigned (1:1) to receive either standard-dose (30 mg/kg) or low-dose (20 mg/kg) azithromycin by a computer-generated random number sequence. Health-care workers assessing clinical outcomes in the field were not blinded to the patient's treatment, but investigators involved in statistical or laboratory analyses and the participants were blinded to treatment group. We followed up participants at 4 weeks and 6 months. The primary outcome was cure at 6 months, defined as lesion healing at 4 weeks in patients with active yaws and at least a four-fold decrease in rapid plasma reagin titre from baseline to 6 months in patients with active and latent yaws. Active yaws was defined as a skin lesion that was positive for Treponema pallidum ssp pertenue in PCR testing. We used a non-inferiority margin of 10%. This trial was registered with ClinicalTrials.gov, number NCT02344628. Findings: Between June 12, 2015, and July 2, 2016, 583 (65·1%) of 895 children screened were enrolled; 292 patients were assigned a low dose of azithromycin and 291 patients were assigned a standard dose of azithromycin. 191 participants had active yaws and 392 had presumed latent yaws. Complete follow-up to 6 months was available for 157 (82·2%) of 191 patients with active yaws. In cases of active yaws, cure was achieved in 61 (80·3%) of 76 patients in the low-dose group and in 68 (84·0%) of 81 patients in the standard-dose group (difference 3·7%; 95% CI −8·4 to 15·7%; this result did not meet the non-inferiority criterion). There were no serious adverse events reported in response to treatment in either group. The most commonly reported adverse event at 4 weeks was gastrointestinal upset, with eight (2·7%) participants in each group reporting this symptom. Interpretation: In this study, low-dose azithromycin did not meet the prespecified non-inferiority margin compared with standard-dose azithromycin in achieving clinical and serological cure in PCR-confirmed active yaws. Only a single participant (with presumed latent yaws) had definitive serological failure. This work suggests that 20 mg/kg of azithromycin is probably effective against yaws, but further data are needed. Funding: Coalition for Operational Research on Neglected Tropical Diseases