SoK: Context and risk aware access control for zero trust systems

Evolving computing technologies such as cloud, edge computing, and the Internet of )ings (IoT) are creating a more complex, dispersed, and dynamic enterprise operational environment. New security enterprise architectures such as those based on the concept of Zero Trust (ZT) are emerging to meet the challenges posed by these changes. ZT systems treat internal and external networks as untrusted and subject both to the same security checking and control to prevent data breaches and limit internal lateral movement. Context awareness is a notion from the field of ubiquitous computing that is used to capture and react to the situation of an entity, based on the dynamics of a particular application or system context. )e idea has been incorporated into several access control models. However, the overlap between context-aware access control and zero-trust security has not been fully explored. In this SoK, we conduct a systematic examination of ZT, context awareness, and risk-based access control to explore the critical elements of each and to identify areas of overlap and synergy to enhance the operation and deployment of ZT systems.</p

A study of network intrusion detection systems using artificial intelligence/machine learning

The rapid growth of the Internet and communications has resulted in a huge increase in transmitted data. These data are coveted by attackers and they continuously create novel attacks to steal or corrupt these data. The growth of these attacks is an issue for the security of our systems and represents one of the biggest challenges for intrusion detection. An intrusion detection system (IDS) is a tool that helps to detect intrusions by inspecting the network traffic. Although many researchers have studied and created new IDS solutions, IDS still needs improving in order to have good detection accuracy while reducing false alarm rates. In addition, many IDS struggle to detect zero-day attacks. Recently, machine learning algorithms have become popular with researchers to detect network intrusion in an efficient manner and with high accuracy. This paper presents the concept of IDS and provides a taxonomy of machine learning methods. The main metrics used to assess an IDS are presented and a review of recent IDS using machine learning is provided where the strengths and weaknesses of each solution is outlined. Then, details of the different datasets used in the studies are provided and the accuracy of the results from the reviewed work is discussed. Finally,observations, research challenges and future trends are discussed. </p

Improving Type 2 Diabetes Patient Health Outcomes with Individualized Continuing Medical Education for Primary Care

<p><strong>Article full text</strong></p> <p><br> The full text of this article can be found <a href="https://link.springer.com/article/10.1007/s13300-016-0176-9"><b>here</b>.</a><br> <br> <strong>Provide enhanced digital features for this article</strong><br> If you are an author of this publication and would like to provide additional enhanced digital features for your article then please contact <u>[email protected]</u>.<br> <br> The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content.<br> <br> Other enhanced features include, but are not limited to:<br> • Slide decks<br> • Videos and animations<br> • Audio abstracts<br> • Audio slides<u></u></p> <p> </p

Machine learning for smart environments in B5G networks: Connectivity and QoS

The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works

Table_7_Engineering Artificial Somatosensation Through Cortical Stimulation in Humans.DOCX

<p>Sensory feedback is a critical aspect of motor control rehabilitation following paralysis or amputation. Current human studies have demonstrated the ability to deliver some of this sensory information via brain-machine interfaces, although further testing is needed to understand the stimulation parameters effect on sensation. Here, we report a systematic evaluation of somatosensory restoration in humans, using cortical stimulation with subdural mini-electrocorticography (mini-ECoG) grids. Nine epilepsy patients undergoing implantation of cortical electrodes for seizure localization were also implanted with a subdural 64-channel mini-ECoG grid over the hand area of the primary somatosensory cortex (S1). We mapped the somatotopic location and size of receptive fields evoked by stimulation of individual channels of the mini-ECoG grid. We determined the effects on perception by varying stimulus parameters of pulse width, current amplitude, and frequency. Finally, a target localization task was used to demonstrate the use of artificial sensation in a behavioral task. We found a replicable somatotopic representation of the hand on the mini-ECoG grid across most subjects during electrical stimulation. The stimulus-evoked sensations were usually of artificial quality, but in some cases were more natural and of a cutaneous or proprioceptive nature. Increases in pulse width, current strength and frequency generally produced similar quality sensations at the same somatotopic location, but with a perception of increased intensity. The subjects produced near perfect performance when using the evoked sensory information in target acquisition tasks. These findings indicate that electrical stimulation of somatosensory cortex through mini-ECoG grids has considerable potential for restoring useful sensation to patients with paralysis and amputation.</p

Table_6_Engineering Artificial Somatosensation Through Cortical Stimulation in Humans.DOCX

<p>Sensory feedback is a critical aspect of motor control rehabilitation following paralysis or amputation. Current human studies have demonstrated the ability to deliver some of this sensory information via brain-machine interfaces, although further testing is needed to understand the stimulation parameters effect on sensation. Here, we report a systematic evaluation of somatosensory restoration in humans, using cortical stimulation with subdural mini-electrocorticography (mini-ECoG) grids. Nine epilepsy patients undergoing implantation of cortical electrodes for seizure localization were also implanted with a subdural 64-channel mini-ECoG grid over the hand area of the primary somatosensory cortex (S1). We mapped the somatotopic location and size of receptive fields evoked by stimulation of individual channels of the mini-ECoG grid. We determined the effects on perception by varying stimulus parameters of pulse width, current amplitude, and frequency. Finally, a target localization task was used to demonstrate the use of artificial sensation in a behavioral task. We found a replicable somatotopic representation of the hand on the mini-ECoG grid across most subjects during electrical stimulation. The stimulus-evoked sensations were usually of artificial quality, but in some cases were more natural and of a cutaneous or proprioceptive nature. Increases in pulse width, current strength and frequency generally produced similar quality sensations at the same somatotopic location, but with a perception of increased intensity. The subjects produced near perfect performance when using the evoked sensory information in target acquisition tasks. These findings indicate that electrical stimulation of somatosensory cortex through mini-ECoG grids has considerable potential for restoring useful sensation to patients with paralysis and amputation.</p

Table_5_Engineering Artificial Somatosensation Through Cortical Stimulation in Humans.DOCX

<p>Sensory feedback is a critical aspect of motor control rehabilitation following paralysis or amputation. Current human studies have demonstrated the ability to deliver some of this sensory information via brain-machine interfaces, although further testing is needed to understand the stimulation parameters effect on sensation. Here, we report a systematic evaluation of somatosensory restoration in humans, using cortical stimulation with subdural mini-electrocorticography (mini-ECoG) grids. Nine epilepsy patients undergoing implantation of cortical electrodes for seizure localization were also implanted with a subdural 64-channel mini-ECoG grid over the hand area of the primary somatosensory cortex (S1). We mapped the somatotopic location and size of receptive fields evoked by stimulation of individual channels of the mini-ECoG grid. We determined the effects on perception by varying stimulus parameters of pulse width, current amplitude, and frequency. Finally, a target localization task was used to demonstrate the use of artificial sensation in a behavioral task. We found a replicable somatotopic representation of the hand on the mini-ECoG grid across most subjects during electrical stimulation. The stimulus-evoked sensations were usually of artificial quality, but in some cases were more natural and of a cutaneous or proprioceptive nature. Increases in pulse width, current strength and frequency generally produced similar quality sensations at the same somatotopic location, but with a perception of increased intensity. The subjects produced near perfect performance when using the evoked sensory information in target acquisition tasks. These findings indicate that electrical stimulation of somatosensory cortex through mini-ECoG grids has considerable potential for restoring useful sensation to patients with paralysis and amputation.</p

Additional file 1: Figures S1–S5: Figure S1. of Umbilical cord blood androgen levels and ASD-related phenotypes at 12 and 36 months in an enriched risk cohort study

Scatterplot between ln-transformed testosterone (T), androstenedione (A4), and dehydroepiandrostenedione (DHEA) levels by infant sex. Figure S2. Scatterplot between ln-transformed umbilical cord androstenedione level and total AOSI score by infant sex. Figure S3. Scatterplot between ln-transformed DHEA level and total AOSI score by infant sex. Figure S4. Scatterplot between ln-transformed androstenedione level and total SRS raw score by infant sex. Figure S5. Scatterplot between ln-transformed DHEA level and total SRS raw score by infant sex. Figure S6. Scatterplot between ln-transformed androstenedione (A4) level and total AOSI score by the older affected sibling’s sex. Figure S7. Scatterplot between ln-transformed androstenedione (A4) level and total SRS score by the older affected sibling’s sex. Figure S8. Scatterplot between ln-transformed DHEA level and total AOSI score by the older affected sibling’s sex. Figure S9. Scatterplot between ln-transformed DHEA level and total SRS raw score by the older affected sibling’s sex. Tables S1–S3: Table S1. Study characteristics comparison across two outcome measures. Table S2. Total and infant sex-stratified adjusted models of androgen levels with 12- and 36-month outcomes. Table S3. Adjusted models of androgen levels with 12- and 36-month outcomes stratified by the older affected sibling’s sex. (PDF 430 kb

Synthetic Macromolecular Antibiotic Platform for Inhalable Therapy against Aerosolized Intracellular Alveolar Infections

Lung-based intracellular bacterial infections remain one of the most challenging infectious disease settings. For example, the current standard for treating <i>Franciscella tularensis</i> pneumonia (tularemia) relies on administration of oral or intravenous antibiotics that poorly achieve and sustain pulmonary drug bioavailability. Inhalable antibiotic formulations are approved and in clinical development for upper respiratory infections, but sustained drug dosing from inhaled antibiotics against alveolar intracellular infections remains a current unmet need. To provide an extended therapy against alveolar intracellular infections, we have developed a macromolecular therapeutic platform that provides sustained local delivery of ciprofloxacin with controlled dosing profiles. Synthesized using RAFT polymerization, these macromolecular prodrugs characteristically have high drug loading (16–17 wt % drug), tunable hydrolysis kinetics mediated by drug linkage chemistry (slow-releasing alkyllic vs fast-releasing phenolic esters), and, in general, represent new fully synthetic nanotherapeutics with streamlined manufacturing profiles. In aerosolized and completely lethal <i>F.t. novicida</i> mouse challenge models, the fast-releasing ciprofloxacin macromolecular prodrug provided high cure efficiencies (75% survival rate under therapeutic treatment), and the importance of release kinetics was demonstrated by the inactivity of the similar but slow-releasing prodrug system. Pharmacokinetics and biodistribution studies further demonstrated that the efficacious fast-releasing prodrug retained drug dosing in the lung above the MIC over a 48 h period with corresponding <i>C</i>_max/MIC and AUC_0–24h/MIC ratios being greater than 10 and 125, respectively; the thresholds for optimal bactericidal efficacy. These findings identify the macromolecular prodrug platform as a potential therapeutic system to better treat alveolar intracellular infections such as <i>F. tularensis</i>, where positive patient outcomes require tailored antibiotic pharmacokinetic and treatment profiles