Ghost-in-ZigBee: Energy Depletion Attack on ZigBee-Based Wireless Networks

Cao, Xianghui; Shila, Devu Manikantan; Cheng, Yu; Yang, Zequ; Zhou, Yuqing; Chen, Jiming

doi:10.1109/jiot.2016.2516102

Cited by 112 publications

(51 citation statements)

References 30 publications

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“…Ning et al [38] proposed a hierarchical authentication architecture to provide anonymous data transmission in IoT networks. Cao et al [39] highlighted the impact and importance of ghost attacks on ZigBee based IoT devices. Chen et al [40] proposed an autonomic model-driven cyber security management approach for IoT systems, which can be used to estimate, detect, and respond to cyberattacks with little or no human intervention.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the increases in low frequency, low profile IoTbased attacks [39], TDTC capabilities in detection of U2R and R2L attacks are useful in incident detection and handling. With the widespread adoption of IoT devices and services in our data-centric and Internet-connected societies, ensuring the security of IoT infrastructure is important to ensure a secure and stable society.…”

Section: B Real-world Applicationsmentioning

confidence: 99%

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A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks

Pajouh

Javidan

Khayami

et al. 2019

IEEE Trans. Emerg. Topics Comput.

350

157

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Abstract-With increasing reliance on Internet of Things (IoT) devices and services, the capability to detect intrusions and malicious activities within IoT networks is critical for resilience of the network infrastructure. In this paper, we present a novel model for intrusion detection based on two-layer dimension reduction and two-tier classification module, designed to detect malicious activities such as User to Root (U2R) and Remote to Local (R2L) attacks. The proposed model is using component analysis and linear discriminate analysis of dimension reduction module to spate the high dimensional dataset to a lower one with lesser features. We then apply a two-tier classification module utilizing Naïve Bayes and Certainty Factor version of K-Nearest Neighbor to identify suspicious behaviors. The experiment results using NSL-KDD dataset shows that our model outperforms previous models designed to detect U2R and R2L attacks.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: B Real-world Applicationsmentioning

confidence: 99%

A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks

Pajouh

Javidan

Khayami

et al. 2019

IEEE Trans. Emerg. Topics Comput.

350

157

View full text Add to dashboard Cite

show abstract

“…The author in [29] suggested a hierarchical authentication framework for managing anonymous information communication over IoT networks. The study in [30] emphasized on the prominence of ghost attacks over ZigBee based IoT devices and in [31], an automated modelbased security mechanism was suggested. This mechanism is utilized to predict, identify and counter cyber-attacks automatically with almost no manual intervention.…”

Section: Related Workmentioning

confidence: 99%

Anomaly based Intrusion Detection by Heuristics to Predict Intrusion Scope of IOT Network Transactions

Korani¹,

Reddy²

2018

IJET

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Conventional intrusion detection mechanisms face serious limitations in identifying heterogeneous and distributed type of intrusions over the IoT environment. This is due to inadequate resources and open deployment environment of IoT. Accordingly, ensuring data security and privacy are tough challenges in the practical context. This manuscript discusses various aspects of networking security and related challenges along with the concepts of system architecture. Further, endeavored to define a machine learning model that outlines two heuristics called Intrusion Scope Heuristic ( ish ), and benign scope heuristic ( bsh ), which further uses in predictive analysis to identify the IOT network transaction is prone to intrusion or benign. The experimental study revealed the significance of the proposal with maximal detection accuracy, and minimal miss rate.

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“…There is need to authenticate the user and the system and the methods and processes are evolving [9]. A method for preventing energy depletion security attacks with ZigBee is explained [10]. A review of security challenges and exiting architectures in the fast growing IoT system has been documented [11].…”

Section: Introductionmentioning

confidence: 99%

Security Framework for Managing Data Security within Point of Care Tests

Tulasidas¹,

Mackay²,

Hudson³

et al. 2017

JSEA

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Point of Care (PoC) devices and systems can be categorized into three broad classes (CAT 1, CAT 2, and CAT 3) based on the context of operation and usage. In this paper, the categories are defined to address certain usage models of the PoC device. PoC devices that are used for PoC testing and diagnostic applications are defined CAT 1 devices; PoC devices that are used for patient monitoring are defined as CAT 2 devices (PoCM); PoC devices that are used for as interfacing with other devices are defined as CAT 3 devices (PoCI). The PoCI devices provide an interface gateway for collecting and aggregating data from other medical devices. In all categories, data security is an important aspect. This paper presents a security framework concept, which is applicable for all of the classes of PoC operation. It outlines the concepts and security framework for preventing security challenges in unauthorized access to data, unintended data flow, and data tampering during communication between system entities, the user, and the PoC system. The security framework includes secure layering of basic PoC system architecture, protection of PoC devices in the context of application and network. Developing the security framework is taken into account of a thread model of the PoC system. A proposal for a low-level protocol is discussed. This protocol is independent of communications technologies, and it is elaborated in relation to providing security. An algorithm that can be used to overcome the threat challenges has been shown using the elements in the protocol. The paper further discusses the vulnerability scanning process for the PoC system interconnected network. The paper also presents a four-step process of authentication and authorization framework for providing the security for the PoC system. Finally, the paper concludes with the machine to machine (M2M) security viewpoint and discusses the key stakeholders within an actual deployment of the PoC system and its security challenges.

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Ghost-in-ZigBee: Energy Depletion Attack on ZigBee-Based Wireless Networks

Cited by 112 publications

References 30 publications

A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks

A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networks

Anomaly based Intrusion Detection by Heuristics to Predict Intrusion Scope of IOT Network Transactions

Security Framework for Managing Data Security within Point of Care Tests

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