LoRaWAN device security and energy optimization

Resource-constrained devices are commonly connected to a network and become things that make up the Internet of Things (IoT). Many industries are interested in cost-effective, reliable, and cyber secure sensor networks due to the ever-increasing connectivity and benefits of IoT devices. The full advantages of IoT devices are seen in a long-range and remote context. However, current IoT platforms show many obstacles to achieve a balance between power efficiency and cybersecurity. Battery-powered sensor nodes can reliably send data over long distances with minimal power draw by adopting Long-Range (LoRa) wireless radio frequency technology. With LoRa, these devices can stay active for many years due to a low data bit rate and low power draw during device sleep states. An improvement built on top of LoRa wireless technology, Long-Range Wide Area Networks (LoRaWAN), introduces integrity and confidentiality of the data sent within the IoT network. Although data sent from a LoRaWAN device is encrypted, protocol and implementation vulnerabilities still exist within the network, resulting in security risks to the whole system. In this research, solutions to these vulnerabilities are proposed and implemented on a LoRaWAN testbed environment that contains devices, gateways, and servers. Configurations that involve the transmission of data using AES Round Reduction, Join Scheduling, and Metadata Hiding are proposed in this work. A power consumption analysis is performed on the implemented configurations, resulting in a LoRaWAN system that balances cybersecurity and battery life. The resulting configurations may be harnessed for usage in the safe, secure, and efficient provisioning of LoRaWAN devices in technologies such as Smart-Industry, Smart-Environment, Smart-Agriculture, Smart-Universities, Smart-Cities, et

A Re-Examination Of The Property Tax Burden

The property tax is the major source of own revenues for most city and county governments, yet economists have had very little definitive information to share with policymakers about the burden that it imposes on local citizens.  This is because most previous studies of property taxes have used a Suits index analysis which does not allow for any independent variables other than income.  We estimate a regression model using current income and various socio-demographic variables in order to take a more fine grained approach.  We use data obtained from the Florida Department of Revenue from 326,976 single family homeowners in four northeast Florida counties geo-coded with the 2010 block group census data.  We find that the property tax is regressive with respect to current income. With respect to demographic variables, we find that homeowners over the age of 65 pay a higher average tax rate based on their current incomes.  African Americans pay a lower tax rate than other races based on their current income. When we combine income and demographic variables to predict the tax rate paid by a hypothetical low socio-economic status household versus a high socio-economic status household, we find that the high SES household pays a higher average tax rate.  Thus, the demographic variables temper the regressivity of the property tax based on current income alone

A Leptin Fragment Mirrors the Cognitive Enhancing and Neuroprotective Actions of Leptin

J.H. is funded by The Anonymous Trust and Cunningham Trust. GD is funded by ARUK, DR received a University of St Andrews Research Internship. JAA is funded by the Carnegie Trust.A key pathology of Alzheimer’s disease (AD) is amyloid β (Aβ) accumulation which triggers synaptic impairments and neuronal death. Metabolic disruption is common in AD and recent evidence implicates impaired leptin function in AD. Thus the leptin system may be a novel therapeutic target in AD. Indeed, leptin has cognitive enhancing properties and it prevents the aberrant effects of Aβ on hippocampal synaptic function and neuronal viability. However as leptin is a large peptide, development of smaller leptin-mimetics may be the best therapeutic approach. Thus, we have examined the cognitive enhancing and neuroprotective properties of known bioactive leptin fragments. Here we show that the leptin (116-130) fragment, but not leptin (22-56), mirrored the ability of leptin to promote AMPA receptor trafficking to synapses and facilitate activity-dependent hippocampal synaptic plasticity. Administration of leptin (116-130) also mirrored the cognitive enhancing effects of leptin as it enhanced performance in episodic-like memory tests. Moreover, leptin (116-130) prevented hippocampal synaptic disruption and neuronal cell death in models of amyloid toxicity. These findings establish further the importance of the leptin system as a therapeutic target in AD.PostprintPeer reviewe

High "Normal" blood glucose is associated with decreased brain volume and cognitive performance in the 60s: the PATH through Life Study

Context:Type 2 diabetes is associated with cerebral atrophy, cognitive impairment and dementia. We recently showed higher glucose levels in the normal range not to be free of adverse effects and to be associated with greater hippocampal and amygdalar atrophy in older community-dwelling individuals free of diabetes.Objective:This study aimed to determine whether blood glucose levels in the normal range

Brain Deletion of Insulin Receptor Substrate 2 Disrupts Hippocampal Synaptic Plasticity and Metaplasticity

Diabetes mellitus is associated with cognitive deficits and an increased risk of dementia, particularly in the elderly. These deficits and the corresponding neurophysiological structural and functional alterations are linked to both metabolic and vascular changes, related to chronic hyperglycaemia, but probably also defects in insulin action in the brain. To elucidate the specific role of brain insulin signalling in neuronal functions that are relevant for cognitive processes we have investigated the behaviour of neurons and synaptic plasticity in the hippocampus of mice lacking the insulin receptor substrate protein 2 (IRS-2)

GIT2 Acts as a Potential Keystone Protein in Functional Hypothalamic Networks Associated with Age-Related Phenotypic Changes in Rats

The aging process affects every tissue in the body and represents one of the most complicated and highly integrated inevitable physiological entities. The maintenance of good health during the aging process likely relies upon the coherent regulation of hormonal and neuronal communication between the central nervous system and the periphery. Evidence has demonstrated that the optimal regulation of energy usage in both these systems facilitates healthy aging. However, the proteomic effects of aging in regions of the brain vital for integrating energy balance and neuronal activity are not well understood. The hypothalamus is one of the main structures in the body responsible for sustaining an efficient interaction between energy balance and neurological activity. Therefore, a greater understanding of the effects of aging in the hypothalamus may reveal important aspects of overall organismal aging and may potentially reveal the most crucial protein factors supporting this vital signaling integration. In this study, we examined alterations in protein expression in the hypothalami of young, middle-aged, and old rats. Using novel combinatorial bioinformatics analyses, we were able to gain a better understanding of the proteomic and phenotypic changes that occur during the aging process and have potentially identified the G protein-coupled receptor/cytoskeletal-associated protein GIT2 as a vital integrator and modulator of the normal aging process

Методология синтеза архитектуры программно-технического комплекса автоматизированной системы мониторинга обстановки

Предложен подход к проектированию архитектуры программно-технического комплекса автоматизированной системы мониторинга обстановки в реальном времени, основанный на классификации решаемых функциональных задач на основе методов кластерного анализа и выбранного множества признаков подобия. Разработанный подход позволяет из множества функций системы выделить подобные (по определенным признакам) и объединить их в архитектурные компоненты (унифицированные функциональные модули).Запропоновано підхід до проектування архітектури центру обробки інформації автоматизованої системи моніторингу середовища в реальному часі, що заснований на класифікації функціональних задач на підставі методів кластерного аналізу і обраної множини ознак схожості. Розроблений підхід дозволяє вибрати із множини функцій системи схожі (за певними ознаками) і поєднати їх в архітектурні компоненти (уніфіковані функціональні модулі).The approach to designing architecture of the information processing complex of the automated real time conditions monitoring system based on classification of functional tasks on the basis of methods of cluster analysis and the chosen set of similarity attributes is offered. The developed approach allows to allocate from a set of functions the systems similar (on certain attributes) and to unite them in architectural components (unified functional modules)