[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

An Implementation of Fake News Prevention by Blockchain and Entropy-based Incentive Mechanism

  • Original Article
  • Published:
Social Network Analysis and Mining Aims and scope Submit manuscript

Abstract

Fake news is undoubtedly a significant threat to democratic countries nowadays because existing technologies can quickly and massively produce fake videos, articles, or social media messages based on the rapid development of artificial intelligence and deep learning. Therefore, human assistance is critical if current fake news prevention systems desire to improve accuracy. Given this situation, prior research has proposed to add a quorum, a group of appraisers trusted by users to verify the authenticity of digital content, to the fake news prevention systems. This paper proposes an entropy-based incentive mechanism to diminish the negative effect of malicious behaviors on a quorum-based fake news prevention system. In order to maintain the Safety and Liveness of our system, we employed entropy to measure the degree of voting disagreement to determine appropriate rewards and penalties. To the best of our knowledge, we believe this is the first proposed work to leverage entropy in a fake news prevention system. Moreover, we use Hyperledger Fabric, Schnorr signatures, and human appraisers to implement a practical prototype of a quorum-based fake news prevention system. Then we conduct necessary case analyses and experiments to realize how dishonest participants, crash failures, and scale impact our system. The outcomes of the case analyses and experiments show that our mechanisms are feasible and provide an analytical basis for developing fake news prevention systems. Furthermore, we have added six innovative contributions in this extension work compared to our previous workshop paper in DEVIANCE 2021.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article.

References

  • Zhou X, Zafarani R (2020) A survey of fake news: fundamental theories, detection methods, and opportunities. ACM Comput Surv. https://doi.org/10.1145/3395046

    Article  Google Scholar 

  • Haciyakupoglu G, Hui JY, Suguna VS, Leong D, Rahman MFBA (2018) Countering fake news: A survey of recent global initiatives. S. Rajaratnam School of International Studies, Nanyang Technological University, Jurong West, Singapore, Accessed: August 16. 2021, [Online]. Available:https://think-asia.org/bitstream/handle/11540/8063/PR180307_Countering-Fake-News.pdf?sequence=1

  • Guess A, Nagler J, Tucker J (2019) Less than you think: prevalence and predictors of fake news dissemination on Facebook. Sci Adv 5(1):4586

    Article  Google Scholar 

  • Google Inc. (2019) How google fights disinformation. [White paper]. Accessed: August 15, 2021. [Online]. Available: https://blog.google/documents/37/How_Google_Fights_Disinformation

  • Chatila R, Havens JC (2019) The IEEE global initiative on ethics of autonomous and intelligent systems. In: Aldinhas Ferreira M, Silva Sequeira J, Singh Virk G, Tokhi ME, Kadar E (eds) Robotics and Well-Being. Intelligent Systems, Control and Automation: Science and Engineering, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-030-12524-0_2

  • Isaak J, Hanna MJ (2018) User data privacy: Facebook, cambridge analytica, and privacy protection. Computer 51(8):56–59. https://doi.org/10.1109/MC.2018.3191268

    Article  Google Scholar 

  • Nakamoto S (2008) Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, 21260

  • Zheng Z, Xie S, Dai H-N, Chen X, Wang H (2018) Blockchain challenges and opportunities: a survey. Int J Web Grid Serv 14(4):352–375. https://doi.org/10.1504/IJWGS.2018.10016848

    Article  Google Scholar 

  • DiCicco KW, Agarwal N (2020) Blockchain technology-based solutions to fight misinformation: A survey. Disinformation, Misinformation, and Fake News in Social Media. Springer, New York, pp 267–281

    Chapter  Google Scholar 

  • Jing TW, Murugesan RK (2018) A theoretical framework to build trust and prevent fake news in social media using blockchain. International Conference of Reliable Information and Communication Technology. Springer, New York, pp 955–962

    Google Scholar 

  • Torky M, Nabil E, Said W (2019) Proof of credibility: a blockchain approach for detecting and blocking fake news in social networks. Int J Adv Comput Sci Appl. https://doi.org/10.14569/IJACSA.2019.0101243

    Article  Google Scholar 

  • Dhall S, Dwivedi AD, Pal SK, Srivastava G (2021) Blockchain-based framework for reducing fake or vicious news spread on social media/messaging platforms. Trans Asian Low-Res Language Inform Process 21(1):1–33. https://doi.org/10.1145/3467019

    Article  Google Scholar 

  • Huckle S, White M (2017) Fake news: A technological approach to proving the origins of content, using blockchains. Big Data 5(4):356–371. https://doi.org/10.1089/big.2017.0071

    Article  Google Scholar 

  • Ansari JAN, Azhar M, Akhtar MJ (2022) The spread of misinformation on social media: An insightful countermeasure to restrict. Studies in Economics and Business Relations 3(1)

  • Jaroucheh Z, Alissa M, Buchanan WJ, Liu X (2020) TRUSTD: Combat fake content using blockchain and collective signature technologies, pp. 1235–1240. https://doi.org/10.1109/COMPSAC48688.2020.00-87

  • Chen C-C, Du Y, Peter R, Golab W (2021) An implementation of fake news prevention by blockchain and entropy-based incentive mechanism. In: 2021 IEEE International Conference on Big Data (Big Data), pp. 2476–2486. https://doi.org/10.1109/BigData52589.2021.9671778

  • King S, Nadal S (2012) Ppcoin: Peer-to-peer crypto-currency with proof-of-stake. self-published paper, August 19(1)

  • Shannon CE (2001) A mathematical theory of communication. ACM SIGMOBILE Mobile Comput Commun Rev 5(1):3–55

    Article  MathSciNet  Google Scholar 

  • Androulaki E, Barger A, Bortnikov V, Cachin C, Christidis K, De Caro A, Enyeart D, Ferris C, Laventman G, Manevich Y, Muralidharan S, Murthy C, Nguyen B, Sethi M, Singh G, Smith K, Sorniotti A, Stathakopoulou C, Vukolić M, Cocco SW, Yellick J (2018) Hyperledger fabric: A distributed operating system for permissioned blockchains. In: Proceedings of the Thirteenth EuroSys Conference. EuroSys ’18. Association for Computing Machinery, New York, NY, USA . https://doi.org/10.1145/3190508.3190538

  • Schnorr CP (1990) Efficient identification and signatures for smart cards. In: Brassard G (ed) Advances in Cryptology – CRYPTO’ 89 Proceedings. Springer, New York, NY, pp 239–252

    Chapter  Google Scholar 

  • Ross B, Jung A, Heisel J, Stieglitz S (2018) Fake news on social media: The (in) effectiveness of warning messages. In: 39th International Conference on Information Systems, p. 16. Association for Information Systems

  • Sirajudeen SM, Azmi NFA, Abubakar AI (2017) Online fake news detection algorithm. J Theor Appl Inform Technol 95:4114–4122

    Google Scholar 

  • Reality Defender (2020) Reality Defender, https://rd2020.org/index.html (accessed August 16, 2021)

  • Lauslahti K, Mattila J, Seppala T (2017) Smart contracts–How will blockchain technology affect contractual practices? Etla Reports (68). https://doi.org/10.2139/ssrn.3154043

  • Wahane A, Patil B (2022) Blockchains to curb fake news in an online world. In: 2022 International Conference for Advancement in Technology (ICONAT), pp. 1–6. https://doi.org/10.1109/ICONAT53423.2022.9725933.IEEE

  • Fraga-Lamas P, Fernández-Caramés TM (2020) Fake news, disinformation, and deepfakes: Leveraging distributed ledger technologies and blockchain to combat digital deception and counterfeit reality. IT Professional 22(2):53–59. https://doi.org/10.1109/MITP.2020.2977589

    Article  Google Scholar 

  • Pawlicki M, Jahankhani H (2022) Advancing governance of news provenance posted on social media platforms with the use of blockchain technology. Social Media Analytics. Strategies and Governance. CRC Press, Boca Raton, Florida, USA, pp 1–30

    Google Scholar 

  • Paul S, Joy JI, Sarker S, Ahmed S, Das AK (2019) Fake news detection in social media using blockchain. In: 2019 7th International Conference on Smart Computing & Communications (ICSCC), pp. 1–5. https://doi.org/10.1109/ICSCC.2019.8843597.IEEE

  • Saad M, Ahmad A, Mohaisen A (2019) Fighting fake news propagation with blockchains. In: 2019 IEEE Conference on Communications and Network Security (CNS), pp. 1–4. https://doi.org/10.1109/CNS.2019.8802670.IEEE

  • Qayyum A, Qadir J, Janjua MU, Sher F (2019) Using blockchain to rein in the new post-truth world and check the spread of fake news. IT Professional 21(4):16–24. https://doi.org/10.1109/MITP.2019.2910503

    Article  Google Scholar 

  • Christodoulou P, Christodoulou K (2020) Developing more reliable news sources by utilizing the blockchain technology to combat fake news. In: 2020 Second International Conference on Blockchain Computing and Applications (BCCA), pp. 135–13 . https://doi.org/10.1109/BCCA50787.2020.9274460.IEEE

  • Ush Shahid I, Anjum MT, Hossain Miah Shohan MS, Tasnim R, Al-Amin M (2021) Authentic facts: A blockchain based solution for reducing fake news in social media. In: 2021 4th International Conference on Blockchain Technology and Applications, pp. 121–127. https://doi.org/10.1145/3510487.3510505

  • Koly WS, Jamil AK, Rahman MS, Bhuiyan H, Bhuiyan MZA, Al Omar A (2021). Towards a location-aware blockchain-based solution to distinguish fake news in social media. In: Inernational Conference on Ubiquitous Security, pp. 116–130 https://doi.org/10.1007/978-981-19-0468-4_9.Springer

  • Singh RR, Thakral M, Kaushik S, Jain A, Chhabra G (2022) A blockchain-based expectation solution for the internet of bogus media. Intelligent Data Communication Technologies and Internet of Things. Springer, New York, pp 385–397

    Chapter  Google Scholar 

  • Poynter Institute (2018) PolitiFact, https://www.politifact.com/ (accessed August 17, 2021)

  • Adair B, Stencel M, Guess C, Ryan E, Luther J, Royal A (2021) Global fact-checking sites. Duke Reports’ LAB, https://reporterslab.org/fact-checking/# (accessed August 17, 2021)

  • Han R, Yan Z, Liang X, Yang LT (2022) How can incentive mechanisms and blockchain benefit with each other? a survey. ACM Computing Surveys (CSUR). https://doi.org/10.1145/3539604

  • Chen Q, Srivastava G, Parizi RM, Aloqaily M, Al Ridhawi I (2020) An incentive-aware blockchain-based solution for internet of fake media things. Inform Process Manage 57(6):102370. https://doi.org/10.1016/j.ipm.2020.102370

    Article  Google Scholar 

  • Zen THY, Hong CB, Mohan PM, Balachandran V (2021) ABC-Verify: AI-Blockchain integrated framework for tweet misinformation detection. In: 2021 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), pp. 1–5 . https://doi.org/10.1109/SOLI54607.2021.9672392.IEEE

  • Farooq M, Ashraf Makhdomi A, Altaf Gillani I (2022) Crowd sourcing and blockchain-based incentive mechanism to combat fake news. Combating Fake News with Computational Intelligence Techniques. Springer, New York, pp 299–325

    Chapter  Google Scholar 

  • Silberschatz A, Korth HF, Sudarshan S (2010) In: Database System Concepts (6th Ed.), pp. 897–898. McGraw-Hil, New York, USA

  • Lesne A (2014) Shannon entropy: a rigorous notion at the crossroads between probability, information theory, dynamical systems and statistical physics. Mathe Struct Comput Sci. https://doi.org/10.1017/S0960129512000783

    Article  MathSciNet  MATH  Google Scholar 

  • Wood G (2014) Ethereum: a secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper 151(2014):1–32

    Google Scholar 

  • Wang W, Hoang DT, Hu P, Xiong Z, Niyato D, Wang P, Wen Y, Kim DI (2019) A survey on consensus mechanisms and mining strategy management in blockchain networks. IEEE Access 7:22328–22370. https://doi.org/10.1109/ACCESS.2019.2896108

    Article  Google Scholar 

  • Hunt P, Konar M, Junqueira FP, Reed B (2010) Zookeeper: Wait-free coordination for internet-scale systems. In: 2010 USENIX Annual Technical Conference, June 23-25. USENIX Association

  • Kernighan BW, Ritchie DM (eds) (1988) The C Programming Language. Prentice Hall Professional Technical Reference, Oboken, New Jersey, USA

  • Thakkar P, Nathan S, Viswanathan B (2018) Performance benchmarking and optimizing hyperledger fabric blockchain platform. In: 2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), pp. 264–276. https://doi.org/10.1109/MASCOTS.2018.00034

Download references

Funding

This study was funded by Ripple and the Natural Sciences and Engineering Research Council of Canada (NSERC).

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering, University of Waterloo, University Avenue West, Waterloo, N2L 3G1, Ontario, Canada

    Chien-Chih Chen, Yuxuan Du, Richards Peter & Wojciech Golab

Authors
  1. Chien-Chih Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuxuan Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richards Peter
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wojciech Golab
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chien-Chih Chen.

Ethics declarations

Conflict of Interest

Chien-Chih Chen and Dr. Wojciech Golab have received research grants from Ripple and the Natural Sciences and Engineering Research Council of Canada (NSERC).

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, CC., Du, Y., Peter, R. et al. An Implementation of Fake News Prevention by Blockchain and Entropy-based Incentive Mechanism. Soc. Netw. Anal. Min. 12, 114 (2022). https://doi.org/10.1007/s13278-022-00941-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13278-022-00941-5

Keywords

Search

Navigation