Selective Jamming of LoRaWAN using Commodity Hardware

Long range, low power networks are rapidly gaining acceptance in the Internet of Things (IoT) due to their ability to economically support long-range sensing and control applications while providing multi-year battery life. LoRa is a key example of this new class of network and is being deployed at large scale in several countries worldwide. As these networks move out of the lab and into the real world, they expose a large cyber-physical attack surface. Securing these networks is therefore both critical and urgent. This paper highlights security issues in LoRa and LoRaWAN that arise due to the choice of a robust but slow modulation type in the protocol. We exploit these issues to develop a suite of practical attacks based around selective jamming. These attacks are conducted and evaluated using commodity hardware. The paper concludes by suggesting a range of countermeasures that can be used to mitigate the attacks.Comment: Mobiquitous 2017, November 7-10, 2017, Melbourne, VIC, Australi

In silico Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19

Background: There is pressing urgency to identify therapeutic targets and drugs that allow treating COVID-19 patients effectively.Methods: We performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19.Results: We screened 1,584 high-confidence immune system proteins in ACE2 and TMPRSS2 co-expressing cells, finding 25 potential therapeutic targets significantly overexpressed in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs, obtaining several approved drugs, compounds under investigation, and experimental compounds with the highest area under the receiver operating characteristics.Conclusion: After being effectively analyzed in clinical trials, these drugs can be considered for treatment of severe COVID-19 patients. Scripts can be downloaded at

Novel 1.6 MHz swept source for realtime volumetric in-vivo OCT imaging of the human retina

In this report, a swept source optical coherence tomography (SS-OCT) instrument, equipped with a novel, multi-MHz tuning range swept source is presented. The source, based on an electrically pumped Micro Electro Mechanical System Vertical Cavity Surface Emitting Laser (MEMS-VCSEL) technology, is able to operate at 1.6 MHz with bidirectional sweeping, and emits light at a central wavelength of 1060 nm with a wavelength tuning range of 30 nm at -3 dB. The capabilities of the SS are investigated, and characterized, using an OCT instrument equipped with pupil tracking capabilities. The source provides an experimental axial resolution of 30 μm measured in air. From measuring the sensitivity drop-off, an axial imaging range longer than 90 mm was inferred. To estimate the wavenumber tuning non-linearities of the source and generate images, the Complex Master-Slave (CMS) method was employed. CMS also allowed for real-time visualization of the en-face images of the human retina, in-vivo, without computing the whole volume. By using the novel SS, in-vivo real-time images of the human retina are produced at 4 Hz volume rate when paired with a 2-D orthogonal galvanometer scanner. The increase in speed for A-scan and volume acquisition tends to reduce fragmented and blurry images. Apart from a montage of en-face images generated in real-time from various axial positions, we also present Bscans produced with a galvanometer scanner driven at 1 kHz from the optic nerve area