613 research outputs found
Mind the tracker you wear:a security analysis of wearable health trackers
No full textWearable tracking devices have gained widespread usage and popularity because of the valuable services they offer, monitoring human's health parameters and, in general, assisting persons to take a better care of themselves. Nevertheless, the security risks associated with such devices can represent a concern among consumers, because of the sensitive information these devices deal with, like sleeping patterns, eating habits, heart rate and so on. In this paper, we analyse the key security and privacy features of two entry level health trackers from leading vendors (Jawbone and Fitbit), exploring possible attack vectors and vulnerabilities at several system levels. The results of the analysis show how these devices are vulnerable to several attacks (perpetrated with consumer-level devices equipped with just bluetooth and Wi-Fi) that can compromise users' data privacy and security, and eventually call the tracker vendors to raise the stakes against such attacks
SafeDroid: A Distributed Malware Detection Service for Android
No full textAndroid platform has become a primary target for malware. In this paper we present SafeDroid, an open source distributed service to detect malicious apps on Android by combining static analysis and machine learning techniques. It is composed by three micro-services, working together, combining static analysis and machine learning techniques. SafeDroid has been designed as a user friendly service, providing detailed feedback in case of malware detection. The detection service is optimized to be lightweight and easily updated. The feature set on which the micro-service of detection relies on on has been selected and optimized in order to focus only on the most distinguishing characteristics of the Android apps. We present a prototype to show the effectiveness of the detection mechanism service and the feasibility of the approach
Prediction of Water Logging Using Analytical Solutions—A Case Study of Kalisindh Chambal River Linking Canal
No full textCopyright © 2013 Dipak N. Kongre, Rohit Goyal. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The canals are designed to transport water to meet irrigation and other water demands or to divert water from surplus basins to deficient basins to meet the ever increasing water demands. Though the positives of canal network are increase in agricultural output and improvement in quality of life, the negatives of canal introduction and irrigation, along its route, are inherent problems of water logging and salinity due to seepage from canals and the irrigation, when not managed properly. To plan strategies to prevent waterlogging and salinity, it is necessary to predict, in advance, the probable area which would be affected due to seepage. This paper presents a methodology to predict the area prone to water logging due to seepage from canal by using 2D seepage solutions to 3D field problem. The available analytical solutions for seepage from canals founded on pervious medium and asymmetrically placed drains, have been utilized. The area, prone to waterlogging, has been mapped using GIS
Analysing a central implementation of an electronic lab notebook (eLabFTW) at the University of Innsbruck
No full textauthor: Rohit KarthikeyanMasterarbeit University of Innsbruck 202
Analysing a central implementation of an electronic lab notebook (eLabFTW) at the University of Innsbruck
No full textauthor: Rohit KarthikeyanMasterarbeit University of Innsbruck 202
Utilizing photoswitchable lipids to photoregulate facilitated ion transport across membranes
No full textAuthor Rohit YadavDissertation Johannes Kepler Universität Linz 2025Arbeit gesperr
Utilizing photoswitchable lipids to photoregulate facilitated ion transport across membranes
No full textAuthor Rohit YadavDissertation Johannes Kepler Universität Linz 2025Arbeit gesperr
COVID-19: Time Series Datasets India versus World
No full textThis dataset consists of COVID-19 time series data of India since March 24th, 2020.
The data set is for all the States and Union Territories of India and is divided into five parts, including
i) Confirmed cases;
ii) Death Count;
iii) Recovered Cases;
iv) Temperature of that place; and
v) Percentage humidity in the region.
The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020.
The end user can contact the corresponding author (Rohit Salgotra : [email protected]) for more details.
.
The Authors can Refer to and CITE our latest Papers on COVID:
1. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming." Chaos, Solitons & Fractals (2020): 109945.
2. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries." Chaos, Solitons & Fractals 140 (2020): 110118.
3. Mousavi, Mohsen, et al. "COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features." IEEE Computational Intelligence Magazine 15.4 (2020): 34-50.
.
[Dataset is updated Once a Week
COVID-19: Time Series Datasets India versus World
No full textThis dataset consists of COVID-19 time series data of India since 24th March 2020.
The data set is for all the States and Union Territories of India and is divided into five parts, including
i) Confirmed cases;
ii) Death Count;
iii) Recovered Cases;
iv) Temperature of that place; and
v) Percentage humidity in the region.
The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020.
The end user can contact the corresponding author (Rohit Salgotra : [email protected]) for more details.
.
The Authors can Refer to and CITE our latest Papers on COVID:
1. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming." Chaos, Solitons & Fractals (2020): 109945.
2. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries." Chaos, Solitons & Fractals 140 (2020): 110118.
3. Mousavi, Mohsen, et al. "COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features." IEEE Computational Intelligence Magazine 15.4 (2020): 34-50.
.
[Dataset is updated Once a Week
COVID-19: Time Series Datasets India versus World
No full textThis dataset consists of COVID-19 time series data of India since March 24th, 2020.
The data set is for all the States and Union Territories of India and is divided into five parts, including
i) Confirmed cases;
ii) Death Count;
iii) Recovered Cases;
iv) Temperature of that place; and
v) Percentage humidity in the region.
The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020.
The end user can contact the corresponding author (Rohit Salgotra : [email protected]) for more details.
.
The Authors can Refer to and CITE our latest Papers on COVID:
1. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming." Chaos, Solitons & Fractals (2020): 109945.
2. Salgotra, Rohit, Mostafa Gandomi, and Amir H. Gandomi. "Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries." Chaos, Solitons & Fractals 140 (2020): 110118.
3. Mousavi, Mohsen, et al. "COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features." IEEE Computational Intelligence Magazine 15.4 (2020): 34-50.
.
[Dataset is updated Once a Week
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