Research Article

Behavioral Steganography in Social Networks

Volume: 11 Number: 4 December 28, 2022
EN

Behavioral Steganography in Social Networks

Abstract

Recently, using human behavior to hide the existence of information has been at the center of steganography research. In this study, a behavioral steganography algorithm using CMI (Coded Signal Inversion) coding is proposed to minimize the high bit error rate that occurs when transmitting a large number of continuous and identical confidential information in the knapsack algorithm, which is used to improve information transmission efficiency and flexibility of transmission mode in social networks. In the proposed algorithm; Data redundancy is reduced by reducing the number of mutual friends of the sender and each receiver. Then, the proposed algorithm was applied and the results were analyzed. Experimental analysis shows that this scheme improves the practical value of behavioral steganography in social networks and has high security.

Keywords

References

  1. Çıtlak O, Dörtler M. and Doğru, İ. A. A survey on detecting spam accounts on Twitter network. Soc.Netw. Anal. Min. 2019, 9:35.
  2. Dutta H, Das R K, Nandi S, An overview of digital audio steganography. IETE Technical Review, 2020, 37(6): 632 - 650.
  3. Evsutin O, Melman S, Meshcheryakov R, V. Digital steganography and watermarking for digital images: a review of current research directions. IEEE Access, 2020, 8: 166589 - 166611.
  4. Han X, Li G. Dynamic cat transformation and chaotic mapping image encryption algorithm. Computer Engineering and Design, 2020, 41(08): 2381 - 2387.
  5. Hu F. A probabilistic solution discovery algorithm for solving 0-1 knapsack problem. International Journal of Parallel, Emergent, and Distributed Systems, 2018, 33(6): 618 - 626.
  6. Hu Y, Wang Z, Zhang X. Steganography in social networks based on behavioral correlation. IETE Technical Review, 2020, 38(1): 93 - 99.
  7. Kantartopoulos P, Pitropakis N, Mylonas, A. Exploring adversarial attacks and defenses for fake Twitter account detection. Technologies, 2020, 8 (4): 64.
  8. Li S, Zhang X. Towards construction based data hiding: from secrets to fingerprint images. IEEE Transactions on Image Processing, 2019, 28(3): 1482 - 1497.

Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Publication Date

December 28, 2022

Submission Date

November 21, 2022

Acceptance Date

December 13, 2022

Published in Issue

Year 2022 Volume: 11 Number: 4

APA
Gençoğlu, M. T. (2022). Behavioral Steganography in Social Networks. Türk Doğa Ve Fen Dergisi, 11(4), 135-141. https://doi.org/10.46810/tdfd.1208075
AMA
1.Gençoğlu MT. Behavioral Steganography in Social Networks. TJNS. 2022;11(4):135-141. doi:10.46810/tdfd.1208075
Chicago
Gençoğlu, Muharrem Tuncay. 2022. “Behavioral Steganography in Social Networks”. Türk Doğa Ve Fen Dergisi 11 (4): 135-41. https://doi.org/10.46810/tdfd.1208075.
EndNote
Gençoğlu MT (December 1, 2022) Behavioral Steganography in Social Networks. Türk Doğa ve Fen Dergisi 11 4 135–141.
IEEE
[1]M. T. Gençoğlu, “Behavioral Steganography in Social Networks”, TJNS, vol. 11, no. 4, pp. 135–141, Dec. 2022, doi: 10.46810/tdfd.1208075.
ISNAD
Gençoğlu, Muharrem Tuncay. “Behavioral Steganography in Social Networks”. Türk Doğa ve Fen Dergisi 11/4 (December 1, 2022): 135-141. https://doi.org/10.46810/tdfd.1208075.
JAMA
1.Gençoğlu MT. Behavioral Steganography in Social Networks. TJNS. 2022;11:135–141.
MLA
Gençoğlu, Muharrem Tuncay. “Behavioral Steganography in Social Networks”. Türk Doğa Ve Fen Dergisi, vol. 11, no. 4, Dec. 2022, pp. 135-41, doi:10.46810/tdfd.1208075.
Vancouver
1.Muharrem Tuncay Gençoğlu. Behavioral Steganography in Social Networks. TJNS. 2022 Dec. 1;11(4):135-41. doi:10.46810/tdfd.1208075

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