Bio-inspired Evolutionary Sensory system for Cyber-Physical System defense

Azab, Mohamed; Eltoweissy, Mohamed

doi:10.1109/ths.2012.6459829

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…As shown in Section 3, the main advantage of having such level of autonomic control and management is the ability to predict some of the sensor feedback based on the analysis of the overall network feedback [14][15][16]. Such ability facilitates optimizing the sensor power usage by controlling the activation periods of sensors leading to much better sensor utilization expanding the lifetime of the entire network and reducing the system cost.…”

Section: Introductionmentioning

confidence: 99%

System-Aware Smart Network Management for Nano-Enriched Water Quality Monitoring

et al. 2016

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This paper presents a comprehensive water quality monitoring system that employs a smart network management, nano-enriched sensing framework, and intelligent and efficient data analysis and forwarding protocols for smart and system-aware decision making. The presented system comprises two main subsystems, a data sensing and forwarding subsystem (DSFS), and Operation Management Subsystem (OMS). The OMS operates based on real-time learned patterns and rules of system operations projected from the DSFS to manage the entire network of sensors. The main tasks of OMS are to enable real-time data visualization, managed system control, and secure system operation. The DSFS employs a Hybrid Intelligence (HI) scheme which is proposed through integrating an association rule learning algorithm withfuzzylogic and weighted decision trees. The DSFS operation is based on profiling and registering raw data readings, generated from a set of optical nanosensors, as profiles of attribute-value pairs. As a case study, we evaluate our implemented test bed via simulation scenarios in a water quality monitoring framework. The monitoring processes are simulated based on measuring the percentage of dissolved oxygen and potential hydrogen (PH) in fresh water. Simulation results show the efficiency of the proposed HI-based methodology at learning different water quality classes.

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Section: Introductionmentioning

confidence: 99%

System-Aware Smart Network Management for Nano-Enriched Water Quality Monitoring

et al. 2016

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“…As shown in the results, the main advantage of having such level of autonomic control and management is the ability to predict some of the sensor feedback based on the analysis of the overall network feedback [ 14 , 15 , 16 ]. Such ability facilitates optimizing the sensor power usage by controlling the activation periods leading to much better sensor utilization expanding the lifetime of the entire network and reducing the system cost.…”

Section: Introductionmentioning

confidence: 99%

Nano-Enriched and Autonomous Sensing Framework for Dissolved Oxygen

Shehata

Azab

Kandas

et al. 2015

Sensors

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This paper investigates a nano-enhanced wireless sensing framework for dissolved oxygen (DO). The system integrates a nanosensor that employs cerium oxide (ceria) nanoparticles to monitor the concentration of DO in aqueous media via optical fluorescence quenching. We propose a comprehensive sensing framework with the nanosensor equipped with a digital interface where the sensor output is digitized and dispatched wirelessly to a trustworthy data collection and analysis framework for consolidation and information extraction. The proposed system collects and processes the sensor readings to provide clear indications about the current or the anticipated dissolved oxygen levels in the aqueous media.

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