A Mobile Code-driven Trust Mechanism for detecting internal attacks in sensor node-powered IoT

A multitude of smart things and wirelessly connected Sensor Nodes (SNs) have pervasively facilitated the use of smart applications in every domain of life. Along with the bounties of smart things and applications, there are hazards of external and internal attacks. Unfortunately, mitigating internal attacks is quite challenging, where network lifespan (w.r.t. energy consumption at node level), latency, and scalability are the three main factors that influence the efficacy of security measures. Furthermore, most of the security measures provide centralized solutions, ignoring the decentralized nature of SN-powered Internet of Things (IoT) deployments. This paper presents an energy-efficient decentralized trust mechanism using a blockchain-based multi-mobile code-driven solution for detecting internal attacks in sensor node-powered IoT. The results validate the better performance of the proposed solution over existing solutions with 43.94% and 2.67% less message overhead in blackhole and greyhole attack scenarios, respectively. Similarly, the malicious node detection time is reduced by 20.35% and 11.35% in both blackhole and greyhole attacks. Both of these factors play a vital role in improving network lifetime.

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An Enhanced Trust Mechanism with Consensus-Based False Information Filtering Algorithm against Bad-Mouthing Attacks and False-Praise Attacks in WSNs

Electronics ◽

10.3390/electronics8111359 ◽

2019 ◽

Vol 8 (11) ◽

pp. 1359 ◽

Cited By ~ 3

Author(s):

Suh ◽

Cho

Keyword(s):

Sensor Node ◽

Information Filtering ◽

Human Society ◽

False Information ◽

Security Vulnerabilities ◽

Trust Mechanism ◽

Filtering Algorithm ◽

Software Modules ◽

Neighbor List ◽

Local Storage

To defend against insider attacks in wireless sensor networks (WSNs), trust mechanisms (TMs) using the notion of trust in human society have been proposed and are still actively researched. In the WSN with a trust mechanism (TM), each sensor node evaluates the trustworthiness of its neighbor sensors based on their behaviors, for example packet forwarding, and collaborates only with trustworthy neighbors while removing untrustworthy neighbor from its neighbor list. The reputation system (RS) is an advanced type of trust mechanism that evaluates the trustworthiness of a node by additionally considering neighbor nodes’ observations or evaluations about it. However, intelligent inside attackers in WSNs can discover the security vulnerabilities of trust mechanisms by examining the operations of TM (or RS), because the software modules of the TM (or RS) are installed and operating in their local storage and memory, and thus, they can avoid detection by the trust mechanisms. Bad-mouthing attacks and false-praise attacks are well-known examples of such intelligent insider attacks. We observed that existing trust mechanisms do not have effective countermeasures to defend against such attacks. In this paper, we propose an enhanced trust mechanism with a consensus-based false information filtering algorithm (TM-CFIFA) that can effectively defend against bad-mouthing attacks and false-praise attacks. According to our experiment results, compared with an existing representative RS model, our TM-CFIFA shortened the detection time of a packet drop attacker, which is supported by a false-praise attacker by at least 83%, and also extended the lifetime of a victim sensor node that is under bad-mouthing attacks by at least 15.8%.

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Cluster Based Trust Mechanism for Mitigation of Internal Attacks in Mobile Ad Hoc Networks

International Journal of Soft Computing ◽

10.3923/ijscomp.2012.294.301 ◽

2012 ◽

Vol 7 (6) ◽

pp. 294-301

Author(s):

R. Murugan ◽

A. Shanmugam

Keyword(s):

Ad Hoc Networks ◽

Mobile Ad Hoc Networks ◽

Ad Hoc ◽

Trust Mechanism ◽

Mobile Ad Hoc ◽

Hoc Networks ◽

Internal Attacks

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A Data Driven Trust Mechanism Based on Blockchain in IoT Sensor Networks for Detection and Mitigation of Attacks

Journal of Trends in Computer Science and Smart Technology - September 2019 ◽

10.36548/jtcsst.2021.1.006 ◽

2021 ◽

Vol 3 (1) ◽

pp. 59-69

Author(s):

Sivaganesan D

Keyword(s):

Black Hole ◽

Sensor Nodes ◽

Data Driven ◽

Security Measures ◽

Malicious Nodes ◽

Trust Mechanism ◽

Proposed Model ◽

Smart Things ◽

Message Overhead ◽

Internal Attacks

Utilization of smart applications in various domains is facilitated pervasively by sensor nodes (SN) that are connected in a wireless manner and a number of smart things. Hazards due to internal and external attacks exist along with the advantages of the smart things and its applications. Security measures are influenced by three main factors namely scalability, latency and network lifespan, without which mitigation of internal attacks is a challenge. The deployment of SN based Internet of things (IoT) is decentralized in nature. However, centralized solutions and security measures are provided by most researchers. A data driven trust mechanism based on blockchain is presented in this paper as a decentralized and energy efficient solution for detection of internal attacks in IoT powered SNs. In grey and black hole attack settings, the message overhead is improved using the proposed model when compared to the existing solutions. In both grey and black hole attacks, the time taken for detection of malicious nodes is also reduced considerably. The network lifetime is improved significantly due to the enhancement of these factors.

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HyperLedger Fabric-Based Proactive Defense against Inside Attackers in the WSN With Trust Mechanism

Electronics ◽

10.3390/electronics9101659 ◽

2020 ◽

Vol 9 (10) ◽

pp. 1659

Author(s):

Kyeongsun Cho ◽

Youngho Cho

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Sensor Node ◽

Communication Channel ◽

Sensor Nodes ◽

Wireless Sensor ◽

Trust Mechanism ◽

Proposed Model ◽

Defense Model ◽

Packet Drop

In Wireless Sensor Networks (WSNs), the Trust Mechanism (TM) is used to defend against insider attacks by measuring the trustworthiness of all inside sensor nodes in the network. Thus, each sensor node with TM observes its neighbor nodes’ behaviors, evaluates their trustworthiness as numeric trust values, and captures untrustworthy nodes as inside attackers. Although the defense performance of trust mechanisms can be further improved by sharing the information about inside attackers detected by TM with all sensor nodes, the detected inside attacker list must be securely shared with and stored in all sensor nodes in the WSN. However, according to our survey, we observed that most existing studies simply assume that the communication channel for sharing the attacker detection list is reliable and trusted even in the presence of inside attackers in the WSN. In this paper, we propose and implement a proactive defense model that integrates the HyperLedger Fabric and trust mechanism to defend against inside attackers by securely sharing the detected inside attacker list with all sensor nodes in the WSN. In addition, we conduct comparative experiments to show that our proposed model can better defend against inside attackers than an existing trust mechanism. According to our experimental results, our proposed model could lower the attack damage (the number of packet drops) caused by an inside packet drop attacker by 59 to 67% compared to an existing trust mechanism.

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