Secure Localization and Velocity Estimation in Mobile IoT Networks With Malicious Attacks

Li, Yunfei; Ma, Shaodan; Yang, Guanghua; Wong, Kai-Kit

doi:10.1109/jiot.2020.3036849

Cited by 23 publications

(5 citation statements)

References 39 publications

(76 reference statements)

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“…A WLS-based algorithm was proposed also in [117], showing to be particularly effective in countering the impact of attackers who manipulate the transmission power of anchors. In the work [118], these threats were formulated as an intractable maximum a posteriori problem, considering a practical model of attack and uncertainties. The proposed algorithm iteratively approximates the true posterior distribution, providing closed-form estimates of position and velocity while identifying malicious nodes.…”

Section: Authenticitymentioning

confidence: 99%

Trustworthy Localization in IoT Networks: A Survey of Localization Techniques, Threats, and Mitigation

Pettorru,

Pilloni,

Martalò

2024

Sensors

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The Internet of Things (IoT) has revolutionized the world, connecting billions of devices that offer assistance in various aspects of users’ daily lives. Context-aware IoT applications exploit real-time environmental, user-specific, or situational data to dynamically adapt to users’ needs, offering tailored experiences. In particular, Location-Based Services (LBS) exploit geographical information to adapt to environmental settings or provide recommendations based on users’ and nodes’ positions, thus delivering efficient and personalized services. To this end, there is growing interest in developing IoT localization systems within the scientific community. In addition, due to the sensitivity and privacy inherent to precise location information, LBS introduce new security challenges. To ensure a more secure and trustworthy system, researchers are studying how to prevent vulnerabilities and mitigate risks from the early design stages of LBS-empowered IoT applications. The goal of this study is to carry out an in-depth examination of localization techniques for IoT, with an emphasis on both the signal-processing design and security aspects. The investigation focuses primarily on active radio localization techniques, classifying them into range-based and range-free algorithms, while also exploring hybrid approaches. Next, security considerations are explored in depth, examining the main attacks for each localization technique and linking them to the most interesting solutions proposed in the literature. By highlighting advances, analyzing challenges, and providing solutions, the survey aims to guide researchers in navigating the complex IoT localization landscape.

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Section: Authenticitymentioning

confidence: 99%

Trustworthy Localization in IoT Networks: A Survey of Localization Techniques, Threats, and Mitigation

Pettorru,

Pilloni,

Martalò

2024

Sensors

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“…A vibrational message passing algorithm is applied to check the network iteratively and find the closed convergence of attacks. The challenging problem is formulated with true posterior distribution on malicious nodes [13][14][15][16][17].…”

Section: Literature Surveymentioning

confidence: 99%

Detection of Phishing in Internet-of-Things Using Hybrid Deep Belief Network

Ashwini¹,

Kumar²

2023

Intelligent Automation &Amp; Soft Computing

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Increase in the use of internet of things owned devices is one of the reasons for increased network traffic. While connecting the smart devices with publicly available network many kinds of phishing attacks are able to enter into the mobile devices and corrupt the existing system. The Phishing is the slow and resilient attack stacking techniques probe the users. The proposed model is focused on detecting phishing attacks in internet of things enabled devices through a robust algorithm called Novel Watch and Trap Algorithm (NWAT). Though Predictive mapping, Predictive Validation and Predictive analysis mechanism is developed. For the test purpose Canadian Institute of cyber security (CIC) dataset is used for creating a robust prediction model. This attack generates a resilience corruption works that slowly gathers the credential information from the mobiles. The proposed Predictive analysis model (PAM) enabled NWAT algorithm is used to predict the phishing probes in the form of suspicious process happening in the IoT networks. The prediction system considers the peer-to-peer communication window open for the established communication, the suspicious process and its pattern is identified by the new approach. The proposed model is validated by finding the prediction accuracy, Precision, recalls F1score, error rate, Mathew's Correlation Coefficient (MCC) and Balanced Detection Rate (BDR). The presented approach is comparatively analyzed with the state-of-the-art approach of existing system related to various types of Phishing probes.

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“…When a certain sensor node is compromised, the attackers can manipulate relevant information for dealing with the fundamental limitations presented in Section III such as the location of sensor nodes and measurements, which could lead to poor localization accuracy with unfortunate results. Although there are several works addressing the security in localization problems [230][231][232][233], they mostly assume ideal scenarios without considering the availability of reference nodes, MPCs, and NLOS conditions. In a similar way, most of the works that deal with fundamental limitations assume that all the sensor nodes provide reliable information, e.g, their position.…”

Section: Securitymentioning

confidence: 99%

Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

Najarro¹,

Song²,

Kim³

2021

Preprint

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With the advances in new technological trends and the reduction in prices of sensor nodes, wireless sensor networks (WSNs) and their applications are proliferating in several areas of our society such as healthcare, industry, farming, and housing. Accordingly, in recent years attention on localization has increased significantly since it is one of the main facets in any WSN. In a nutshell, localization is the process in which the position of any sensor node is retrieved by exploiting measurements from and between sensor nodes. Several techniques of localization have been proposed in the literature with different localization accuracy, complexity, and hence different applicability. The localization accuracy is limited by fundamental limitations, theoretical and practical, that restrict the localization accuracy regardless of the technique employed in the localization process. In this paper, we pay special attention to such fundamental limitations from the theoretical and practical points of view and provide a comprehensive review of the state-of-the-art solutions that deal with such limitations. Additionally, discussion on the theoretical and practical limitations together with their recent solutions, remaining challenges, and perspectives are presented.

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Secure Localization and Velocity Estimation in Mobile IoT Networks With Malicious Attacks

Cited by 23 publications

References 39 publications

Trustworthy Localization in IoT Networks: A Survey of Localization Techniques, Threats, and Mitigation

Trustworthy Localization in IoT Networks: A Survey of Localization Techniques, Threats, and Mitigation

Detection of Phishing in Internet-of-Things Using Hybrid Deep Belief Network

Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

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