| 1. |
- Atif, Yacine, 1967-, et al.
(författare)
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Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection
- 2017
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Konferensbidrag (refereegranskat)abstract
- Critical infrastructures (CIs) are becoming increasingly sophisticated with embedded cyber-physical systems (CPSs) that provide managerial automation and autonomic controls. Yet these advances expose CI components to new cyber-threats, leading to a chain of dysfunctionalities with catastrophic socio-economical implications. We propose a comprehensive architectural model to support the development of incident management tools that provide situation-awareness and cyber-threats intelligence for CI protection, with a special focus on smart-grid CI. The goal is to unleash forensic data from CPS-based CIs to perform some predictive analytics. In doing so, we use some AI (Artificial Intelligence) paradigms for both data collection, threat detection, and cascade-effects prediction.
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| 2. |
- Ferati, Mexhid, et al.
(författare)
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Tackling the Sustainability of Digital Aging Innovations Through Design Thinking and Systems Thinking Perspectives
- 2021
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Ingår i: ICT for Health, Accessibility and Wellbeing. - Cham : Springer. - 9783030942083 - 9783030942090 ; , s. 179-184
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Bokkapitel (refereegranskat)abstract
- The digitalization of society brings many opportunities and challenges, especially on how we organize the welfare society in the future. This becomes especially pertinent as we are heading toward a global increase of older people, which will strain healthcare and bring the challenge of building sustainable solutions. In this paper, we argue that the unsustainable solutions within healthcare are due to them being defined and ‘solved’ with a single approach or approaches used in silos. We advocate that a more sustainable solution could be achieved by combining systems thinking and design thinking perspectives throughout the entire process—from problem definition to solution offering. A benefit of such combined perspectives is the ability to develop a shared context among all stakeholders, which helps uncover unique tacit knowledge from their experience. This will serve as a solid foundation to generate unconventional ideas that will lead to sustainable and satisfactory solutions.
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| 3. |
- Atif, Yacine, 1967-, et al.
(författare)
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Internet of Things data analytics for parking availability prediction and guidance
- 2020
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Ingår i: European transactions on telecommunications. - : Wiley-Blackwell Publishing Inc.. - 1124-318X .- 2161-3915 .- 2161-5748. ; 31
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Tidskriftsartikel (refereegranskat)abstract
- Cutting-edge sensors and devices are increasingly deployed within urban areas to make-up the fabric of transmission control protocol/internet protocol con- nectivity driven by Internet of Things (IoT). This immersion into physical urban environments creates new data streams, which could be exploited to deliver novel cloud-based services. Connected vehicles and road-infrastructure data are leveraged in this article to build applications that alleviate notorious parking and induced traffic-congestion issues. To optimize the utility of parking lots, our proposed SmartPark algorithm employs a discrete Markov-chain model to demystify the future state of a parking lot, by the time a vehicle is expected to reach it. The algorithm features three modular sections. First, a search pro- cess is triggered to identify the expected arrival-time periods to all parking lots in the targeted central business district (CBD) area. This process utilizes smart-pole data streams reporting congestion rates across parking area junc- tions. Then, a predictive analytics phase uses consolidated historical data about past parking dynamics to infer a state-transition matrix, showing the transfor- mation of available spots in a parking lot over short periods of time. Finally, this matrix is projected against similar future seasonal periods to figure out the actual vacancy-expectation of a lot. The performance evaluation over an actual busy CBD area in Stockholm (Sweden) shows increased scalability capa- bilities, when further parking resources are made available, compared to a baseline case algorithm. Using standard urban-mobility simulation packages, the traffic-congestion-aware SmartPark is also shown to minimize the journey duration to the selected parking lot while maximizing the chances to find an available spot at the selected lot.
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