Introduction to the Internet of Things security: Standardization and research challenges

Elbouanani, Salim; Kiram, My Ahmed El; Achbarou, Omar

doi:10.1109/isias.2015.7492741

Cited by 18 publications

(13 citation statements)

References 12 publications

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“…2) Internet of Things: Internet of Things (IoT) [46] is a network of physical devices, sensors, home appliances, and other electronic devices that can connect to the Internet and transfer data freely. The main concept behind IoT is to connect devices (virtually or physically) with a unique ID seamlessly.…”

Section: Sdn For Emerging Technologiesmentioning

confidence: 99%

A comprehensive survey of interface protocols for software defined networks

Latif

Sharif

et al. 2020

Journal of Network and Computer Applications

114

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Software Defined Networks has seen tremendous growth and deployment in different types of networks. Compared to traditional networks it decouples the control logic from network layer devices, and centralizes it for efficient traffic forwarding and flow management across the domain. This multilayered architecture has data forwarding devices at the bottom in data plane, which are programmed by controllers in the control plane. The high level application or management plane interacts with control layer to program the whole network and enforce different policies. The interaction among these layers is done through interfaces which work as communication/programming protocols. In this survey, we present a comprehensive study of such interfaces available for southbound, northbound, and east/westbound communication. We have classified each type into different categories based on their properties and capabilities. Virtualization of networks devices is a common practice in Software Defined Networks. This paper also analyzes interface solution which work with different virtualization schemes. In addition, the paper highlights a number of short term and long term research challenges and open issues related to SDN interfaces.

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Section: Sdn For Emerging Technologiesmentioning

confidence: 99%

A comprehensive survey of interface protocols for software defined networks

Latif

Sharif

et al. 2020

Journal of Network and Computer Applications

114

View full text Add to dashboard Cite

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“…For example, the average speed and flow of cars in a certain road are negatively correlated because, when the flow (number) of cars increases at a certain timestamp, the average speed of cars decreases. The correlation matrix between these two attributes will be as follows in (2)…”

Section: B Differentiation Between An Event and Noisementioning

confidence: 99%

“…Things can comprise smart phones, tablets, washing machines, refrigerators, etc. IoT is a network system which connects different communication devices with the internet to establish rapid, reliable, and real time information interchange that assists in intelligent management [2]. The objects capture data about the surrounding environment to monitor certain phenomena such as temperature and humidity.…”

Section: Introductionmentioning

confidence: 99%

A Correlation based Approach to Differentiate between an Event and Noise in Internet of Things

ElMenshawy¹,

Helmy²

2018

ijacsa

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Internet of Things (IoT) is considered a huge enhancement in the field of information technology. IoT is the integration of physical devices which are embedded with electronics, software, sensors, and connectivity that allow them to interact and exchange data. IoT is still in its beginning so it faces a lot of obstacles ranging from data management to security concerns. Regarding data management, sensors generate huge amounts of data that need to be handled efficiently to have successful employment of IoT applications. Detection of data anomalies is a great challenge that faces the IoT environment because, the notion of anomaly in IoT is domain dependent. Also, the IoT environment is susceptible to a high noise rate. Actually, there are two main sources of anomalies, namely: an event and noise. An event refers to a certain incident which occurred at a specific time, whereas noise denotes an error. Both event and noise are considered anomalies as they deviate from the remaining data points, but actually they have two different interpretations. To the best of our knowledge, no research exists addressing the question of how to differentiate between an event and noise in IoT. As a result, in this paper, an algorithm is proposed to differentiate between an event and noise in the IoT environment. At first, anomalies are detected using exponential moving average technique, then the proposed algorithm is applied to differentiate between an event and noise. The algorithm uses the sensors' values and correlation existence between sensors to detect whether the anomaly is an event or noise. Moreover, the algorithm was applied on a real traffic dataset of size 5000 records to evaluate its effectiveness and the experiments showed promising results.

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“…A thing denotes an object in the real world which has an identity and can be embedded into a communication network. As a result, objects can be managed remotely, permitting integration between the physical and virtual worlds (Elbouanani et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…(1) Comprehensive perception: Sensors capture data anytime and anyplace. (2) Reliable transmission: Objects access information networks and achieve robust information interaction (3) Intelligent processing: Analyze the huge quantities of sensors' data by using various technologies and attain intelligent decision making and control (Elbouanani et al, 2015;Ray et al, 2016) The IoT paradigm allows for:…”

Section: Introductionmentioning

confidence: 99%

A Clustering based Approach for Contextual Anomaly Detection in Internet of Things

ElMenshawy¹,

Helmy²,

El-Tazi³

2019

Journal of Computer Science

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Internet of Things (IoT) is a network which connects different communication devices with the internet to attain quick, robust and realtime information transfer and communication, achieving intelligent management. IoT is still in its infancy so it faces numerous challenges varying from data management to security concerns. Sensors generate enormous quantities of data that need to be handled efficiently to have successful deployment of IoT applications. Concerning data management, a great challenge that faces the IoT environment is the detection of contextual anomalies. Contextual anomaly detection is a sophisticated task because the context has to be taken into consideration in the anomaly detection process rather than checking only the deviation of the data value as in point anomaly detection. As a result, in this paper, a novel clustering based algorithm is proposed to detect contextual anomalies in Internet of Things. Attributes were separated into two different categories, namely contextual attributes and behavioral attributes. K-Means clustering technique was applied on the contextual and behavioral attributes separately, then the intersection between the contextual and behavioral clusters was used to detect the contextual anomalies. Moreover, the algorithm was applied on a real room occupation dataset of size around 20,000 records and the experiments showed promising results.

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Introduction to the Internet of Things security: Standardization and research challenges

Cited by 18 publications

References 12 publications

A comprehensive survey of interface protocols for software defined networks

A comprehensive survey of interface protocols for software defined networks

A Correlation based Approach to Differentiate between an Event and Noise in Internet of Things

A Clustering based Approach for Contextual Anomaly Detection in Internet of Things

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