IoT Security Framework for Smart Water System

Pacheco, Jesús; Ibarra, Daniela; Vijay, Ashamsa; Hariri, Salim

doi:10.1109/aiccsa.2017.85

Cited by 34 publications

(35 citation statements)

References 21 publications

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“…Both scenarios will make use of the system's resources, methods, and data to initiate the attack. In this research, the security of an IoT application is considered with respect to the local and public networks [35]. Local networks include controllers and devices, communications and gateways, while public networks include IoT services and applications.…”

Section: B Identification Of Attack Surfacementioning

confidence: 99%

“…1 an attack surface can be derived as shown in Table 1. This work focuses on the security of a Fog node (Gateway) implemented on a Raspberry Pi 3 configured to perform communications between other Fog nodes and IoT subsystems such as the Smart Water Testbed introduced in [35]. Fog nodes security is crucial to develop trustworthy IoT applications and services, providing resiliency and preventing cyber threats to be disseminated among other IoT subsystems.…”

Section: B Identification Of Attack Surfacementioning

confidence: 99%

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Artificial Neural Networks-Based Intrusion Detection System for Internet of Things Fog Nodes

et al. 2020

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The Internet of Things (IoT) represents a mean to share resources (memory, storage computational power, data, etc.) between computers and mobile devices, as well as buildings, wearable devices, electrical grids, and automobiles, just to name few. The IoT is leading to the development of advanced information services that will require large storage and computational power, as well as real-time processing capabilities. The integration of IoT with emerging technologies such as Fog Computing can complement these requirements with pervasive and cost-effective services capable of processing largescale geo-distributed information. In any IoT application, communication availability is essential to deliver accurate and useful information, for instance, to take actions during dangerous situations, or to manage critical infrastructures. IoT components like gateways, also called Fog Nodes, face outstanding security challenges as the attack surface grows with the number of connected devices requesting communication services. These Fog nodes can be targeted by an attacker, preventing the nodes from delivering important information to the final users or to perform accurate automated actions. This paper introduces an Anomaly Behavior Analysis Methodology based on Artificial Neural Networks, to implement an adaptive Intrusion Detection System (IDS) capable of detecting when a Fog node has been compromised, and then take the required actions to ensure communication availability. The experimental results reveal that the proposed approach has the capability for characterizing the normal behavior of Fog Nodes despite its complexity due to the adaptive scheme, and also has the capability of detecting anomalies due to any kind of sources such as misuses, cyber-attacks or system glitches, with high detection rate and low false alarms. INDEX TERMS Anomaly behavior, cyber security, fog computing, IoT, neural networks.

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Section: B Identification Of Attack Surfacementioning

confidence: 99%

Section: B Identification Of Attack Surfacementioning

confidence: 99%

Artificial Neural Networks-Based Intrusion Detection System for Internet of Things Fog Nodes

et al. 2020

Self Cite

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“…They also showed the procedure to use the threat model in order to protect or secure gateway which is the necessary part of the communication gateway. The functionality of this method is based on the concept that it utilizes a profile that is developed to accurately and characterizes the normal operations of gateway [9]. As per analysis, it is demonstrated that proposed approach of ABAIDS can detect both known and unknown attacks with high detection rates and low false positive alarms.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy Efficient Technique for Data Aggregation in Internet of Things

Awasthi¹,

Kaur²

2020

IJRTE

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The IOT network is the decentralized type of network which can sense the information and pass it to base station. Due to small size of the sensor nodes, the energy consumption is the major issue of the network. The LEACH is the energy efficient protocol which can divide whole network into fixed size clusters. In each cluster, cluster heads are selected which can transmit data to base station. In this research work, the LEACH protocol is improved to reduce energy consumption of the wireless sensor networks. In the proposed improvement, the cache nodes are deployed which can aggregate data from the cluster heads and then pass data to base station. The simulation of the proposed technique is done in MATLAB and results are compared with the existing approach in terms of certain parameters. It is analyzed that proposed technique performs well as compared to existing technique.

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“…The smart water applications include water pipeline monitoring, water quality in open water source, smart water meter reading, IoT security for smart water system(SWS) etc. In order to ensure the integrity of customer information, security of the devices and data passed through the network, a framework and methodology were developed [37]. Water quality monitoring of open water sources was another application that was implemented using IoT devices.…”

Section: A Smart Water Systemmentioning

confidence: 99%

IoT Technology for Smart Water System

Radhakrishnan

2018

2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference On

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A serious drop in ensuring the water quality in the distribution system is a factor that affects public health. This could lead to increase in biological and non-biological contents, change in colour and odour of the water. These contaminants cause a serious threat to the whole water ecosystem. The conventional methods of analyzing the water quality require much time and labour. So there is a need to monitor and protect the water with a real time water quality monitoring system in order to make active measurements to reduce contamination. The growth of the technology had helped in developing efficient methods to solve many serious issues in real-time. Internet of things (IoT) has achieved a great focus due to its faster processing and intelligence. This paper focuses on discussing the architecture, applications and need of IoT in water management system.

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IoT Security Framework for Smart Water System

Cited by 34 publications

References 21 publications

Artificial Neural Networks-Based Intrusion Detection System for Internet of Things Fog Nodes

Artificial Neural Networks-Based Intrusion Detection System for Internet of Things Fog Nodes

Energy Efficient Technique for Data Aggregation in Internet of Things

IoT Technology for Smart Water System

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