Skip to main content

Advertisement

SpringerLink
Log in

Fuzzy with black widow and spider monkey optimization for privacy-preserving-based crowdsourcing system

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Crowdsourcing is a procedure for demonstrating data outsourcing to a wide range of individual workers rather than considering a unique entity or a company. Crowdsourcing has made different kinds of chances for some trying issues by utilizing human knowledge. In order to attain an optimal global assignment technique, it is necessary to gather information regarding the location of the entire workers. There occur few security issues during information gathering that causes severe threat to all workers. To overcome the concerns based on privacy-preserving, this paper proposes a privacy-preserving model based on Fuzzy with the Black widow and Spider Monkey Optimization (BW–SMO). The fuzzy can be used to cluster the query solution. To optimize the query selection, we exploited the Black widow optimization algorithm incorporated with the Spider Monkey optimization algorithm. The parameters of both algorithms are controlled by the Fuzzy logic controller. Thus, our proposed frameworks of Fuzzy with BW–SMO effectively solve optimizing selection and join queries with low cost, latency, and securing data. The proposed model will be compared with the existing models to show the system's effectiveness.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Agrawal D, Aggarwal CC (2001) On the design and quantification of privacy preserving data mining algorithms. In: PODS

  • Ali SH (2012) Miner for OACCR: case of medical data analysis in knowledge discovery. In: IEEE, 2012 6th international conference on sciences of electronics, technologies of information and telecommunications (SETIT), Sousse, 2012, pp 962–975. doi: https://doi.org/10.1109/SETIT.2012.6482043

  • Ali SH (2013) Novel approach for generating the key of stream cipher system using random forest data mining algorithm. In: IEEE, 2013 Sixth international conference on developments in eSystems engineering, Abu Dhabi, 2013, pp 259–269. doi: https://doi.org/10.1109/DeSE.2013.54

  • Al-Janabi S, Alkaim AF (2020) A nifty collaborative analysis to predicting a novel tool (DRFLLS) for missing values estimation. Soft Comput 24(1):555–569

    Article  Google Scholar 

  • S Al-Janabi, E Alwan (2017) Soft mathematical system to solve black box problem through development the FARB based on hyperbolic and polynomial functions. In: IEEE, 2017 10th international conference on developments in eSystems engineering (DeSE), Paris, pp 37–42. doi: https://doi.org/10.1109/DeSE.2017.23

  • Al-Janabi S, Rawat S, Patel A, Al-Shourbaji I (2015) Design and evaluation of a hybrid system for detection and prediction of faults in electrical transformers. Int J Electr Power Energy Syst 67:324–335. https://doi.org/10.1016/j.ijepes.2014.12.005

    Article  Google Scholar 

  • Al-Janabi S, Alkaim AF, Adel Z (2020a) An innovative synthesis of deep learning techniques (DCapsNet and DCOM) for generation electrical renewable energy from wind energy. Soft Comput 24:10943–10962

    Article  Google Scholar 

  • Al-Janabi S, Mohammad M, Al-Sultan A (2020b) A new method for prediction of air pollution based on intelligent computation. Soft Comput 24(1):661–680

    Article  Google Scholar 

  • Alkaim AF, Al-Janabi S (2019) Multi objectives optimization to gas flaring reduction from oil production. In: Farhaoui Y (ed) Big data and networks technologies BDNT 2019. Lecture notes in networks and systems, vol 81. Springer, Cham

    Google Scholar 

  • Bhaskar N, Kumar PM (2020) Optimal processing of nearest-neighbor user queries in crowdsourcing based on the whale optimization algorithm. Soft Comput 24:13037–13050

    Article  Google Scholar 

  • Bhaskar N, Kumar PM, Renjit JA (2020) Evolutionary Fuzzy-based gravitational search algorithm for query optimization in crowdsourcing system to minimize cost and latency. Comput Intel. https://doi.org/10.1111/coin.12382

    Article  Google Scholar 

  • Even S, Goldreich O, Lempel A (1983) A randomized protocol for signing contracts. Springer, Berlin

    Book  Google Scholar 

  • Foursquare (2016) https://foursquare.com/

  • Garmin Connect (2016) https://connect.garmin.com/

  • Guan Z, Zhang Y, Wu L, Wu J, Li J, Ma Y, Hu J (2019) APPA: an anonymous and privacy preserving data aggregation scheme for fog-enhanced IoT. J Netw Comput Appl 125:82–92

    Article  Google Scholar 

  • Guo Y, H Xie, Y Miao, C Wang, X Jia (2020) FedCrowd: a federated and privacy-preserving crowdsourcing platform on blockchain. IEEE Trans Serv Comput

  • Hayyolalam V, Kazem AAP (2020) Black widow optimization algorithm: a novel meta-heuristic approach for solving engineering optimization problems. Eng Appl Artif Intell 87:103249

    Article  Google Scholar 

  • Jose J, Gautam N, Tiwari M, Tiwari T, Suresh A, Sundararaj V, Rejeesh MR (2021) An image quality enhancement scheme employing adolescent identity search algorithm in the NSST domain for multimodal medical image fusion. Biomed Sig Process Control 66:102480

    Article  Google Scholar 

  • Lin Y, Cunningham IIIGA, Coggeshall SV (1997) Using fuzzy partitions to create fuzzy systems from input-output data and set the initial weights in a fuzzy neural network. IEEE Trans Fuzzy Syst 5(4):614–621

    Article  Google Scholar 

  • Lin C, He D, Zeadally S, Kumar N, Choo K-KR (2020) SecBCS: a secure and privacy-preserving blockchain-based crowdsourcing system. Sci China Inf Sci 63(3):1–14

    Article  MathSciNet  Google Scholar 

  • Louise B (2012). The mismeasurement of privacy: using contextual integrity to reconsider privacy in HCI. In: SIGCHI. ACM, pp 367–376

  • Naor M, Pinkas B (2001) Efficient oblivious transfer protocols. SODA 1:448–457

    MathSciNet  MATH  Google Scholar 

  • Naor M, Pinkas B (2005) Computationally secure oblivious transfer. J Cryptol 18(1):1–35

    Article  MathSciNet  Google Scholar 

  • Prabakeran S, Sethukarasi T (2020) Optimal solution for malicious node detection and prevention using hybrid chaotic particle dragonfly swarm algorithm in VANETs. Wirel Netw 26(8):5897–5917

    Article  Google Scholar 

  • Raja S, Ramaiah S (2017) An efficient fuzzy-based hybrid system to cloud intrusion detection. Int J Fuzzy Syst 19(1):62–77

    Article  Google Scholar 

  • Rejeesh MR (2019) Interest point based face recognition using adaptive neuro fuzzy inference system. Multimed Tools Appl 78(16):22691–22710

    Article  Google Scholar 

  • Saravanan P, Sethukarasi T, Indumathi V (2018a) An efficient software defined network based cooperative scheme for mitigation of distributed denial of service (DDoS) attacks. J Comput Theor Nanosci 15(6–7):2221–2226

    Article  Google Scholar 

  • Saravanan P, Sethukarasi T, Indumathi V (2018b) Authentic novel trust propagation model with deceptive recommendation penalty scheme for distributed denial of service attacks. J Comput Theor Nanosci 15(6–7):2383–2389

    Article  Google Scholar 

  • Saravanan P, Kumar RH, Arvind T, Narayanan B (2019) Hybrid Crypto System Using Homomorphic Encryption and Elliptic Curve Cryptography. i-Manager’s J Comput Sci 7(1):36

    Google Scholar 

  • Sharma H, G Hazrati, JC Bansal (2019) Spider monkey optimization algorithm. In: Evolutionary and swarm intelligence algorithms. Springer, Cham, pp 43–59

  • Shi K, Zhu L, Zhang C, Xu L, Gao F (2020) Blockchain-based multimedia sharing in vehicular social networks with privacy protection. Multimed Tools Appl 79:8085–8105

    Article  Google Scholar 

  • Sundararaj V (2016) An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. Int J Intell Eng Syst 9(3):117–126

    Google Scholar 

  • Sundararaj V (2019) Optimal task assignment in mobile cloud computing by queue based ant-bee algorithm. Wirel Pers Commun 104(1):173–197

    Article  Google Scholar 

  • Tang W, Zhang K, Ren J, Zhang Y, Shen XS (2020) Privacy-preserving task recommendation with win-win incentives for mobile crowdsourcing. Inf Sci 527:477–492

    Article  Google Scholar 

  • Tatiana P, Vasconcelos M, Almeida J, Kumaraguru P, Almeida V (2012) We know where you live: privacy characterization of foursquare behavior. In: UbiComp. Pittsburgh, Pennsylvania, pp 898–905

  • Vinu S (2019) Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction. Int J Biomed Eng Technol 31(4):325

    Article  Google Scholar 

  • Vinu S, Muthukumar S, Kumar RS (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Comput Secur 77:277–288

    Article  Google Scholar 

  • Vinu S, Anoop V, Dixit P, Arjaria A, Chourasia U, Bhambri P, Rajeesh MR, Sundararaj R (2020) CCGPA-MPPT: cauchy preferential crossover-based global pollination algorithm for MPPT in photovoltaic system. Prog Photovolt Res Appl 28(11):1128–1145

    Article  Google Scholar 

  • Wang S, Jia X, Sang Q (2020) A dual privacy preserving algorithm in spatial crowdsourcing. Mob Inf Syst

  • Yi X, Paulet R, Bertino E (2014) Homomorphic encryption and applications, vol 3. Springer, Heidelberg

    MATH  Google Scholar 

  • Zhang J, Zhang Q, Ji S (2020) A fog-assisted privacy-preserving task allocation in crowdsourcing. IEEE Internet Things J 7:8331–8342

    Article  Google Scholar 

  • Zhang J, Wan C, Zhang C, Guo X, Chen Y (2020) Noninteractive lightweight privacy-preserving auditing on images in mobile crowdsourcing networks. Secur Commun Netw

  • Zhang X, Chen X, Yan H, Xiang Y (2021) Privacy-preserving and verifiable online crowdsourcing with worker updates. Inf Sci 548:212–232

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Velammal Engineering College, Chennai, India

    J. Sathya Priya

  2. Department of Information Technology, KCG College of Technology, Chennai, India

    N. Bhaskar

  3. Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Chennai, India

    S. Prabakeran

Authors
  1. J. Sathya Priya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Bhaskar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Prabakeran
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to J. Sathya Priya or N. Bhaskar.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

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

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Priya, J.S., Bhaskar, N. & Prabakeran, S. Fuzzy with black widow and spider monkey optimization for privacy-preserving-based crowdsourcing system. Soft Comput 25, 5831–5846 (2021). https://doi.org/10.1007/s00500-021-05657-w

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-021-05657-w

Keywords

Search

Navigation