Intrusion Detection and Prevention for ZigBee-Based Home Area Networks in Smart Grids

Jokar, Paria; Leung, Victor C. M.

doi:10.1109/tsg.2016.2600585

Cited by 60 publications

(37 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other works focus on the proposal of innovative intrusion detection systems, designed to protect ZigBee based IoT networks. [56] introduces ABAS, an anomaly based protection system analyzing network traffic to classify anomalous behavior, while [57] makes use of machine learning algorithms to detect running attacks. [58] uses fuzzy methods based on a finite state machine to detect possible vulnerabilities.…”

Section: Internet Of Things Network May Adopt Different Communicatiomentioning

confidence: 99%

Evaluating Security of Low-Power Internet of Things Networks

al.¹

2019

IJCDS

View full text Add to dashboard Cite

Internet of Things (IoT) is one of the most prominent technologies on the Internet. Simple objects gain the ability to store, process and exchange information among themselves or with external entities, by observing and controlling the environment. Thanks to the rapid development of this innovation, IoT opens possibilities to a huge number of objects and applications that promise to improve our daily life. The main scenarios of the development of IoT are home automation/domestic and Industrial IoT. According to such scenarios, several applications could be implemented: from smart thermostats, light bulbs, refrigerators, ovens, door window sensors to volumetric, flow, heat and connected data processing devices. Since this is a new phenomenon, it has not yet been studied and analyzed for its entirety, also due to the lack of a definitive standard that can provide an overview of these devices. The objective of this paper is to implement different well-known attacks against IoT networks, by adopting the ZigBee communication protocol to analyze devices and network security. For our aim, we have considered different scenarios involving an attacker aiming to dismantle the IoT network (jamming, flooding DoS), retrieve sensitive information (sniffing, brute force password crack) and to actively communicate on the network to impersonate legitimate nodes (replay). Such exploitation provides us the ability to analyze the effects of attacks designed to target common wireless networks, when they are perpetrated against IoT environments. Obtained results prove that IoT devices and networks (often embedded in sensitive environments such as hospitals or critical infrastructures) are vulnerable to several attacks.

show abstract

Section: Internet Of Things Network May Adopt Different Communicatiomentioning

confidence: 99%

Evaluating Security of Low-Power Internet of Things Networks

al.¹

2019

IJCDS

View full text Add to dashboard Cite

show abstract

“…Another protection algorithm proposed by Jokar and Leung and known as HANIDPS implements machine learning based intrusion detection and prevention system. HANIDPS analyzes the network traffic and compares it with a normal in order to detect a running threat [40]. A similar approach may analyze energy consumption [41] to identify running attacks.…”

Section: Related Workmentioning

confidence: 99%

Remotely Exploiting AT Command Attacks on ZigBee Networks

Vaccari

Cambiaso

Aiello

2017

Security and Communication Networks

View full text Add to dashboard Cite

Internet of Things networks represent an emerging phenomenon bringing connectivity to common sensors. Due to the limited capabilities and to the sensitive nature of the devices, security assumes a crucial and primary role. In this paper, we report an innovative and extremely dangerous threat targeting IoT networks. The attack is based on Remote AT Commands exploitation, providing a malicious user with the possibility of reconfiguring or disconnecting IoT sensors from the network. We present the proposed attack and evaluate its efficiency by executing tests on a real IoT network. Results demonstrate how the threat can be successfully executed and how it is able to focus on the targeted nodes, without affecting other nodes of the network.

show abstract

“…Jokar et al discuss intrusion detection and prevention system by using Zigbee for the home area network grids that follow the IEEE 802.15.4 standard. It analyzes a network to know whether it is in normal or intrusive state and able to prevent various attacks . Although the researchers have used the neural network techniques, the neural network‐based IDSs need to enhance the detection accuracy and precision.…”

Section: Introductionmentioning

confidence: 99%

Intrusion detection in RFID system using computational intelligence approach for underground mines

Gautam

2018

Int J Communication

View full text Add to dashboard Cite

The radio frequency identification technology (RFID) is commonly used for object tracking and monitoring. In this paper, we discuss a model for intrusion detection system based on RFID to identify the abnormal behavior of underground mines' toxic gases. This model consists of various types of sensor nodes that are integrated with RFID tag, which are deployed in the underground mines by using Zigbee protocol. It consists of coordinators, routers, and sensor nodes, according to different capabilities and the probabilities of intrusive activities that occur in underground mines. It can detect the real-time abnormal

show abstract

Intrusion Detection and Prevention for ZigBee-Based Home Area Networks in Smart Grids

Cited by 60 publications

References 18 publications

Evaluating Security of Low-Power Internet of Things Networks

Evaluating Security of Low-Power Internet of Things Networks

Remotely Exploiting AT Command Attacks on ZigBee Networks

Intrusion detection in RFID system using computational intelligence approach for underground mines

Contact Info

Product

Resources

About