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Crowdsourcing Under Data Poisoning Attacks: A Comparative Study [chapter]

Farnaz Tahmasebian, Li Xiong, Mani Sotoodeh, Vaidy Sunderam
2020 Lecture Notes in Computer Science  
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

Akshay Dua, Nirupama Bulusu, Wu-Chang Feng, Wen Hu
2014 ACM Transactions on Embedded Computing Systems  
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

Marcin Waniek, Gururaghav Raman, Bedoor AlShebli, Jimmy Chih-Hsien Peng, Talal Rahwan
2021 Scientific Reports  
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]

Marcin Waniek, Gururaghav Raman, Bedoor AlShebli, Jimmy Chih-Hsien Peng, Talal Rahwan
2020 arXiv   pre-print
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

Jiyuan Zhou, Xing Jin, Lanping Yu, Limin Xue, Yizhi Ren
2021 Sensors  
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

Michael C. Lucic, Xiangpeng Wan, Hakim Ghazzai, Yehia Massoud
2020 Smart Cities  
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

Francesco Restuccia, Sajal K. Das, Jamie Payton
2016 ACM transactions on sensor networks  
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]

Simone Raponi, Savio Sciancalepore, Gabriele Oligeri, Roberto Di Pietro
2021 arXiv   pre-print
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]

Joshua Brown, Olga Ohrimenko, Roberto Tamassia
2013 arXiv   pre-print
., 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]

Francesco Restuccia and Sajal K. Das and Jamie Payton
2015 arXiv   pre-print
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]

Francesco Restuccia and Pierluca Ferraro and Timothy S. Sanders and Simone Silvestri and Sajal K. Das and Giuseppe Lo Re
2018 arXiv   pre-print
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

Zhihong Wang, Yongbiao Li, Dingcheng Li, Ming Li, Bincheng Zhang, Shishi Huang, Wen He, Leo Y. Zhang
2021 Security and Communication Networks  
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

Francesco Restuccia, Salvatore DrOro, Tommaso Melodia
2018 IEEE Internet of Things Journal  
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

Francesco Restuccia, Nirnay Ghosh, Shameek Bhattacharjee, Sajal K. Das, Tommaso Melodia
2017 ACM transactions on sensor networks  
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

Prajit Kumar Das, Anupam Joshi, Tim Finin
2017 2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)  
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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