Journal of Information Systems Engineering and Management

Reputation Systems: A framework for attacks and frauds classification
Rui Humberto Pereira 1 * , Maria José Gonçalves 2, Marta Alexandra Guerra Magalhães 3
More Detail
1 CEOS.PP/ University of Maia, 4475-690 Maia, Porto, Portugal
2 CEOS.PP, ISCAP, Polytechnic of Porto, 4465-004 Mamede Infesta, Porto, Portugal
3 ISCAP, Polytechnic of Porto, 4465-004 Mamede Infesta, Porto, Portugal
* Corresponding Author
Literature Review

Journal of Information Systems Engineering and Management, 2023 - Volume 8 Issue 1, Article No: 19218
https://doi.org/10.55267/iadt.07.12830

Published Online: 14 Jan 2023

Views: 972 | Downloads: 688

How to cite this article
APA 6th edition
In-text citation: (Pereira et al., 2023)
Reference: Pereira, R. H., Gonçalves, M. J., & Magalhães, M. A. G. (2023). Reputation Systems: A framework for attacks and frauds classification. Journal of Information Systems Engineering and Management, 8(1), 19218. https://doi.org/10.55267/iadt.07.12830
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Pereira RH, Gonçalves MJ, Magalhães MAG. Reputation Systems: A framework for attacks and frauds classification. J INFORM SYSTEMS ENG. 2023;8(1):19218. https://doi.org/10.55267/iadt.07.12830
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Pereira RH, Gonçalves MJ, Magalhães MAG. Reputation Systems: A framework for attacks and frauds classification. J INFORM SYSTEMS ENG. 2023;8(1), 19218. https://doi.org/10.55267/iadt.07.12830
Chicago
In-text citation: (Pereira et al., 2023)
Reference: Pereira, Rui Humberto, Maria José Gonçalves, and Marta Alexandra Guerra Magalhães. "Reputation Systems: A framework for attacks and frauds classification". Journal of Information Systems Engineering and Management 2023 8 no. 1 (2023): 19218. https://doi.org/10.55267/iadt.07.12830
Harvard
In-text citation: (Pereira et al., 2023)
Reference: Pereira, R. H., Gonçalves, M. J., and Magalhães, M. A. G. (2023). Reputation Systems: A framework for attacks and frauds classification. Journal of Information Systems Engineering and Management, 8(1), 19218. https://doi.org/10.55267/iadt.07.12830
MLA
In-text citation: (Pereira et al., 2023)
Reference: Pereira, Rui Humberto et al. "Reputation Systems: A framework for attacks and frauds classification". Journal of Information Systems Engineering and Management, vol. 8, no. 1, 2023, 19218. https://doi.org/10.55267/iadt.07.12830
ABSTRACT
Reputation and recommending systems have been widely used in e-commerce, as well as online collaborative networks, P2P networks and many other contexts, in order to provide trust to the participants involved in the online interaction. Based on a reputation score, the e-commerce user feels a sense of security, leading the person to trust or not when buying or selling. However, these systems may give the user a false sense of security due to their gaps. This article discusses the limitations of the current reputation systems in terms of models to determine the reputation score of the users. We intend to contribute to the knowledge in this field by providing a systematic overview of the main types of attack and fraud found in those systems, proposing a novel framework of classification based on a matrix of attributes. We believe such a framework could help analyse new types of attacks and fraud. Our work was based on a systematic literature review methodology.
KEYWORDS
REFERENCES
  • Ahn, J., Park, M., & Paek, J. (2018). Reptor: A Model for Deriving Trust and Reputation on Blockchain-based Electronic Payment System. 2018 International Conference on Information and Communication Technology Convergence (ICTC), 1431–1436. https://doi.org/10.1109/ICTC.2018.8539641
  • Ahn, J., Park, M., Shin, H., & Paek, J. (2019). A Model for Deriving Trust and Reputation on Blockchain-Based e-Payment System. Applied Sciences, 9(24), 5362. https://doi.org/10.3390/app9245362
  • Alshammari, S. T., Albeshri, A., & Alsubhi, K. (2021). Building a trust model system to avoid cloud services reputation attacks. Egyptian Informatics Journal, 22(4), 493–503. https://doi.org/10.1016/j.eij.2021.04.001
  • Briner, R. B., Denyer, D., & Rousseau, D. M. (2009). Evidence-Based Management: Concept Cleanup Time? Academy of Management Perspectives, 23(4), 19–32. https://doi.org/10.5465/AMP.2009.45590138
  • Camilo, G. F., Rebello, G. A. F., de Souza, L. A. C., & Duarte, O. C. M. B. (2020). A Secure Personal-Data Trading System Based on Blockchain, Trust, and Reputation. 2020 IEEE International Conference on Blockchain (Blockchain), 379–384. https://doi.org/10.1109/Blockchain50366.2020.00055
  • Damiani, E., di Vimercati, D. C., Paraboschi, S., Samarati, P., & Violante, F. (2002). A reputation-based approach for choosing reliable resources in peer-to-peer networks. Proceedings of the 9th ACM Conference on Computer and Communications Security - CCS ’02, 207. https://doi.org/10.1145/586110.586138
  • Dellarocas, C. (2000). Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior. Proceedings of the 2nd ACM Conference on Electronic Commerce - EC ’00, 150–157. https://doi.org/10.1145/352871.352889
  • Dellarocas., C. (2000). Mechanisms for coping with unfair ratings and discriminatory behavior in online reputation reporting systems. Proceedings of the Twenty First International Conference on Information Systems (ICIS ’00), 520–525.
  • Dellarocas, C. N. (2003). The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.393042
  • Dennis, R., & Owen, G. (2015). Rep on the block: A next generation reputation system based on the blockchain. 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), 131–138. https://doi.org/10.1109/ICITST.2015.7412073
  • Dhakal, Anup, & Cui, Xiaohui. (2019). DTrust: A Decentralized Reputation System for E-commerce Marketplaces.
  • Dixon-Woods, M., & Fitzpatrick, R. (2001). Qualitative research in systematic reviews: Has established a place for itself. British Medical Journal, 323, 765–766.
  • Douceur, J. R. (2002). The Sybil Attack. In: Druschel, P., Kaashoek, F., Rowstron, A. (eds) Peer-to-Peer Systems. Lecture Notes in Computer Science, Vol 2429. Springer, Berlin, Heidelberg, 2429.
  • Feng, Q., Liu, L., & Dai, Y. (2012). Vulnerabilities and countermeasures in context-aware social rating services. ACM Transactions on Internet Technology, 11(3), 1–27. https://doi.org/10.1145/2078316.2078319
  • Fraga, D., Bankovic, Z., & Moya, J. M. (2012). A Taxonomy of Trust and Reputation System Attacks. 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications, 41–50. https://doi.org/10.1109/TrustCom.2012.58
  • Gambetta, D. (1988) Can we Trust Trust? Gambetta, D., Ed., Trust: Making and Breaking Cooperative Relations. Blackwell, New York, 213-237
  • Gong, Y., van Engelenburg, S., & Janssen, M. (2021). A Reference Architecture for Blockchain-Based Crowdsourcing Platforms. Journal of Theoretical and Applied Electronic Commerce Research, 16(4), 937–958. https://doi.org/10.3390/jtaer16040053
  • Hendrikx, F., Bubendorfer, K., & Chard, R. (2015). Reputation systems: A survey and taxonomy. Journal of Parallel and Distributed Computing, 75, 184–197. https://doi.org/10.1016/j.jpdc.2014.08.004
  • Hoffman, K., Zage, D., & Nita-Rotaru, C. (2009). A survey of attack and defense techniques for reputation systems. ACM Computing Surveys, 42(1), 1–31. https://doi.org/10.1145/1592451.1592452
  • Jøsang, A., Ismail, R., & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. Decision Support Systems, 43(2), 618–644. https://doi.org/10.1016/j.dss.2005.05.019
  • Karode, T., Werapun, W., & Arpornthip, T. (2020). Blockchain-based Global Travel Review Framework. International Journal of Advanced Computer Science and Applications, 11(8). https://doi.org/10.14569/IJACSA.2020.0110813
  • Koutrouli, E., & Tsalgatidou, A. (2012). Taxonomy of attacks and defense mechanisms in P2P reputation systems—Lessons for reputation system designers. Computer Science Review, 6(2–3), 47–70. https://doi.org/10.1016/j.cosrev.2012.01.002
  • Koutrouli, E., & Tsalgatidou, A. (2016). Reputation Systems Evaluation Survey. ACM Computing Surveys, 48(3), 1–28. https://doi.org/10.1145/2835373
  • Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Reprint—Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Physical Therapy, 89(9), 873–880. https://doi.org/10.1093/ptj/89.9.873
  • Panagopoulos, A., Koutrouli, E., & Tsalgatidou, A. (2017). Modeling and Evaluating a Robust Feedback-Based Reputation System for E-Commerce Platforms. ACM Transactions on the Web, 11(3), 1–55. https://doi.org/10.1145/3057265
  • Petticrew, M., & Roberts, H. (. (2005). Systematic reviews in the social sciences: A practical guide (1 edition (M. A. Malden, Ed.; 1st ed.). Oxford: Wiley-Blackwell.
  • Sänger, J., Richthammer, C., & Pernul, G. (2015). Reusable components for online reputation systems. Journal of Trust Management, 2(1), 5. https://doi.org/10.1186/s40493-015-0015-3
  • Schaub, A., Bazin, R., Hasan, O., & Brunie, L. (2016). A Trustless Privacy-Preserving Reputation System (pp. 398–411). https://doi.org/10.1007/978-3-319-33630-5_27
  • Swamynathan, G., Almeroth, K. C., Ben, ·, Zhao, Y., Swamynathan, G., Almeroth, · K C, & Zhao, B. Y. (2010). The design of a reliable reputation system. Springer, 10(3), 239–270. https://doi.org/10.1007/s10660-010-9064-y
  • Thomas, J., Gough, D., & Oliver, S. (2017). Introduction to Systematic Reviews (2nd ed.). SAGE Publications, Limited.
  • Wang, J., Jing, X., Yan, Z., Fu, Y., Pedrycz, W., & Yang, L. T. (2020). A Survey on Trust Evaluation Based on Machine Learning. ACM Computing Surveys (CSUR), 53(5). https://doi.org/10.1145/3408292
  • Yao, Y., Ruohomaa, S., & Xu, F. (2012). Addressing Common Vulnerabilities of Reputation Systems for Electronic Commerce. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 3–4. https://doi.org/10.4067/S0718-18762012000100002
  • Zeynalvand, L., Luo, T., Andrejczuk, E., Niyato, D., Teo, S. G., & Zhang, J. (2021). A Blockchain-Enabled Quantitative Approach to Trust and Reputation Management with Sparse Evidence. Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS ’21).
  • Zulfiqar, M., Tariq, F., Janjua, M. U., Mian, A. N., Qayyum, A., Qadir, J., Sher, F., & Hassan, M. (2021). EthReview: An Ethereum-based Product Review System for Mitigating Rating Frauds. Computers & Security, 100, 102094. https://doi.org/10.1016/j.cose.2020.102094
LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.