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Crowdsourcing Under Data Poisoning Attacks: A Comparative Study
[chapter]
2020
Lecture Notes in Computer Science
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In this paper, we propose a comprehensive data poisoning attack taxonomy for truth inference in crowdsourcing and systematically evaluate the state-of-the-art truth inference methods under various data ...
In addition to the variable quality of the contributed data, a potential challenge presented to crowdsourcing applications is data poisoning attacks where malicious users may intentionally and strategically ...
In the Waze example, attackers might want to take the road with the least traffic by deceiving Waze application to wrongly indicate there is heavy traffic on that specific road. ...
doi:10.1007/978-3-030-49669-2_18
fatcat:xnytdkglavfh5f2ixm7euz2wwy
Combating Software and Sybil Attacks to Data Integrity in Crowd-Sourced Embedded Systems
2014
ACM Transactions on Embedded Computing Systems
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Data integrity becomes imperative as malicious participants can launch software and Sybil attacks modifying the sensing platform and data. ...
To address these attacks, we develop (i) a Trusted Sensing Peripheral (TSP) enabling collection of high-integrity raw or aggregated data, and participation in applications requiring additional modalities ...
importance of different targets and the strategic behavior of attackers. ...
doi:10.1145/2629338
fatcat:ttwzbvbgcfcbzk2zjylegme424
Traffic networks are vulnerable to disinformation attacks
2021
Scientific Reports
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Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation. ...
Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. ...
Acknowledgements Gururaghav Raman and Jimmy Chih-Hsien Peng were supported in part by the National Research Foundation Singapore (https ://www.nrf.gov.sg/) through grant NRF2018-SR2001-018. ...
doi:10.1038/s41598-021-84291-w
pmid:33674635
pmcid:PMC7935872
fatcat:elbc7azzwzhvboqorylhzsjm2a
Traffic networks are vulnerable to disinformation attacks
[article]
2020
arXiv
pre-print
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Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation. ...
Nevertheless, a disinformation-based attack on critical infrastructure has never been studied to date. ...
Nevertheless, the possibility that a malicious actor could use disinformation in a targeted attack to influence social behavior within a limited time has not been considered to date. ...
arXiv:2003.03723v1
fatcat:b2uzb2emlrds3l3fa7qesvx5ku
TruthTrust: Truth Inference-Based Trust Management Mechanism on a Crowdsourcing Platform
2021
Sensors
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Defending against malicious attacks is an important issue in crowdsourcing, which has been extensively addressed by existing methods, e.g., verification-based defense mechanisms, data analysis solutions ...
Moreover, we propose a reverse mechanism to improve the resistance under attacks. ...
[17] proposed two mechanisms (MD and CG) to detect the cheating behaviors of workers. ...
doi:10.3390/s21082578
pmid:33916964
fatcat:lcm2xhkgufgbdb3mm3djdkmbzi
Leveraging Intelligent Transportation Systems and Smart Vehicles Using Crowdsourcing: An Overview
2020
Smart Cities
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In this paper, we review and discuss the architecture and types of ITS crowdsourcing. ...
Afterward, we provide an overview of cutting edge work associated with ITS crowdsourcing challenges. ...
Its Crowdsourcing Use Cases
Infrastructure Monitoring for Improvement The authors of [19] developed a mobile phone-based sensing system to detect bumps and other anomalous behavior while driving a ...
doi:10.3390/smartcities3020018
fatcat:dg57ehkvurbpdahp6wvuabk6xm
Incentive Mechanisms for Participatory Sensing
2016
ACM transactions on sensor networks
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Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing. ...
In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. ...
Hereafter, we refer to this kind of malicious behavior as a location-spoofing attack. Figure 4 depicts the functioning scheme of FakeLocator and an example of a location-spoofing attack. ...
doi:10.1145/2888398
fatcat:bsixa53xebdkdbmedqt77cxsie
Road Traffic Poisoning of Navigation Apps: Threats and Countermeasures
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2002.05051v2 fatcat:zxtxsyykd5a3bfcbgypxefpwxiOther Versions
However, technological progress in virtualization technologies and Software-Defined Radios recently enabled new attack vectors, namely, road traffic poisoning. ...
These attacks open up several dreadful scenarios, which are addressed in this contribution by identifying the associated challenges and proposing innovative countermeasures. ...
Device cooperation is proposed in [10] to detect and mitigate GPS spoofing attacks. ...
arXiv:2002.05051v3
fatcat:hwwqbf4bc5b4ljbqljd6nwt4ay
Haze: Privacy-Preserving Real-Time Traffic Statistics
[article]
2013
arXiv
pre-print
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., Waze reported 30 million users in 2013) since they aggregate real-time road traffic updates from actual users traveling on the roads. ...
We show that Haze is effective in practice by developing a prototype implementation and performing experiments on a real-world dataset of car trajectories. ...
Acknowledgments This research was supported in part by the National Science Foundation under grants IIS-1212508 and CNS-1228485.
REFERENCES ...
arXiv:1309.3515v1
fatcat:gweem5txx5a6lmqx3dik4hzs24
Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges
[article]
2015
arXiv
pre-print
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Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing. ...
In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. ...
Hereafter, we refer to this kind of malicious behavior as a location-spoofing attack. Figure 4 depicts the functioning scheme of FakeLocator and an example of a location-spoofing attack. ...
arXiv:1502.07687v3
fatcat:ykgrtdt3vnez5hiht463viu7wa
FIRST: A Framework for Optimizing Information Quality in Mobile Crowdsensing Systems
[article]
2018
arXiv
pre-print
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One of the biggest challenges in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior. ...
Experimental results demonstrate that FIRST reduces significantly the impact of three security attacks (i.e., corruption, on/off, and collusion), by achieving a classification accuracy of almost 80% in ...
ACKNOWLEDGEMENT This material is based upon work supported by the National Science Foundation under grant no. CNS-1545037, CNS-1545050, and DGE-1433659. ...
arXiv:1804.11147v1
fatcat:tjwbn3fwlvfsrortnqifjbpfx4
Enabling Fairness-Aware and Privacy-Preserving for Quality Evaluation in Vehicular Crowdsensing: A Decentralized Approach
2021
Security and Communication Networks
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In addition, machine learning and TEE are utilized to evaluate the quality of data collected by the sensors in a privacy-preserving and fair way, eliminating human subject judgement of the sensing solutions ...
The smart contracts paradigm in blockchain enforces correct and automatic program execution for task processing. ...
On the other hand, a malicious worker may try to obtain the task rewards without contributing enough time and resources, which is known as a freeriding attack. ese two attacks have an impact on the fairness ...
doi:10.1155/2021/9678409
fatcat:dzkjkjpq75at7fdaopkztew3te
Securing the Internet of Things in the Age of Machine Learning and Software-defined Networking
2018
IEEE Internet of Things Journal
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2018 pre-print arXiv:1803.05022v1 fatcat:l2zjgrbfdvbcdnnhghwbyqz3tmOther Versions
Traditional approaches where security is applied as an afterthought and as a "patch" against known attacks are insufficient. ...
In this paper, we first provide a taxonomy and survey the state of the art in IoT security research, and offer a roadmap of concrete research challenges related to the application of machine learning and ...
This aspect, joint with the hardly predictable behavior of malicious entities, hinders significantly the design and development of effective threat detection systems. ...
doi:10.1109/jiot.2018.2846040
fatcat:xjjdi43i2bfnta5e5c6fcuamdy
Quality of Information in Mobile Crowdsensing
2017
ACM transactions on sensor networks
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As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. ...
In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. ...
Another crucial issue in mobile crowdsensing, also studied in the context of generic crowdsourcing, is how to deal with malicious behavior by participants [33, 54, 179] . ...
doi:10.1145/3139256
fatcat:hgq6lcwmofhy3gpq4auqxuhggu
Personalizing Context-Aware Access Control on Mobile Platforms
2017
2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)
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The feedback process used a hierarchical context ontology to represent user-context and gathered contextual-situations in which a policy would be applicable. ...
INTRODUCTION Mobile platforms were predicted to experience an escalation of attacks by a 2014 McAfee Threats Report [1] due to openly available mobile malicious source code. ...
Under the first, we used a default deny policy and under the second we used a curated policy generated using crowd-sourced data. ...
doi:10.1109/cic.2017.00025
dblp:conf/coinco/DasJF17
fatcat:fezyidcobrdr3k2qxugcp73zz4
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