The distributiveness and heterogeneity of today’s systems of systems, such as the Internet of Things (IoT), on-line banking systems, and contemporary emergency information systems, require the integration of access and usage control mechanisms, for managing the right of access both to the corresponding services, and the plethora of information that is generated in a daily basis. Usage Control (UCON) is such a mechanism, allowing the fine-grained policy based management of system resources, based on dynamic monitoring and evaluation of object, subject, and environmental attributes.
The work described in this website has been conducted within the project NeCS. This project has received funding from the European Union’s Horizon 2020 (H2020) research and innovation programme under the Grant Agreement no 675320. This website and the content displayed in it do not represent the opinion of the European Union, and the European Union is not responsible for any use that might be made of its content.
Modern interconnected systems of systems, such as the Internet of Things (IoT), demand the presence of access and usage control mechanisms which will be able to manage the right of access to the corresponding services, and the plethora of information being generated in a daily basis. The Usage Control (UCON) model offers the means for fine-grained dynamic control of access to specific resources, by monitoring and evaluating the attributes defined within a dedicated security policy.
Distributed environments such as Internet of Things, have an increasing need of introducing access and usage control mechanisms, to manage the rights to perform specific operations and regulate the access to the plethora of information daily generated by these devices. Defining policies which are specific to these distributed environments could be a challenging and tedious task, mainly due to the large set of attributes that should be considered, hence the upcoming of unforeseen conflicts or unconsidered conditions.
With the introduction of the Amazon Echo family and Google devices like Chromecast and Home the adoption of IoT devices in the household is bound to increase exponentially this year. While usability is at the front and centre of the experience to facilitate the adoption and use of these new devices, security and privacy are often an afterthought. As a consequence, a dangerous environment of opportunity is available for malicious actors to exploit vulnerable devices sitting in domestic houses.
On-demand ride services and the rideshare infrastructure primarily focus on the minimization of travel time and cost. However, the safety of riders is overlooked by service providers. For driver authentication, existing identity management methods typically check the driving license, which can be easily stolen, forged, or misused. Further, background checks are not performed at all; instead, social profiles and peer reviews are used to foster trust, thereby compromising the safety and security of riders.
Smartphones are the most popular and widespread personal devices. Apart from their conventional use, i.e., calling and texting, they have also been used to perform multiple security-sensitive activities, such as online banking and shopping, social networking, taking pictures and emailing. On a positive side, smartphones have improved the quality of life by providing multiple services that users desire, e.g., anytime-anywhere computing, etc. However, on the other side, they also pose security and privacy threats to the users’ stored data.
This paper introduces DialerAuth - a mechanism which leverages the way a smartphone user taps/enters any “text-independent" 10-digit number (replicating the dialing process) and the hand’s micro-movements she makes while doing so. DialerAuth authenticates the user on the basis of timing differences in the entered 10-digit strokes. DialerAuth provides enhanced security by leveraging the transparent and unobservable layer based on another