A Privacy-Preserving Method Based on Artificial Immune Computing in MCS
Due to the widespread use of mobile intelligent terminal devices, Mobile Crowd Sensing (MCS) applications have gained significant research attention. However, ensuring users privacy remains a critical challenge, as it can hinder users’ willingness to participate actively in tasks. To addr...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10328773/ |
| _version_ | 1797357922066366464 |
|---|---|
| author | Hao Long Jiawei Hao Shukui Zhang Yang Zhang Li Zhang |
| author_facet | Hao Long Jiawei Hao Shukui Zhang Yang Zhang Li Zhang |
| author_sort | Hao Long |
| collection | DOAJ |
| description | Due to the widespread use of mobile intelligent terminal devices, Mobile Crowd Sensing (MCS) applications have gained significant research attention. However, ensuring users privacy remains a critical challenge, as it can hinder users’ willingness to participate actively in tasks. To address the limitations of existing differential privacy protection methods, this paper proposes a novel privacy protection approach based on Artificial Immune Computing (AICppm). Specifically, private information is concealed within a masking carrier, and data scrambling is avoided. The proposed method involves two main steps: first, a carrier preprocessing approach based on a high-pass filter bank is designed to identify candidate positions for perturbation. Then, a carrier steganography algorithm based on multi-objective optimization is used, transforming the perturbation position into an antibody using the artificial immune algorithm. By iteratively searching for antibodies with higher fitness, the optimal perturbation of the offspring population is identified using the improved Strength Pareto Evolution Algorithm (SPEA2). The experimental results demonstrate that the proposed algorithm can withstand the attacks of malicious steganalysis tools, preserving the integrity of the sensing data and enabling real-time processing of private information. |
| first_indexed | 2024-03-08T14:52:29Z |
| format | Article |
| id | doaj.art-7309f8f4bcbd40588b95333f17975921 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T14:52:29Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7309f8f4bcbd40588b95333f179759212024-01-11T00:02:13ZengIEEEIEEE Access2169-35362023-01-011113407413408610.1109/ACCESS.2023.333670110328773A Privacy-Preserving Method Based on Artificial Immune Computing in MCSHao Long0https://orcid.org/0000-0003-3943-3244Jiawei Hao1Shukui Zhang2https://orcid.org/0000-0001-6191-5827Yang Zhang3https://orcid.org/0000-0002-8781-4722Li Zhang4https://orcid.org/0000-0001-8966-1451School of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou, ChinaSchool of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou, ChinaSchool of Computer Science and Technology, Soochow University, Suzhou, ChinaSchool of Computer Science and Technology, Soochow University, Suzhou, ChinaSchool of Computer Science and Technology, Soochow University, Suzhou, ChinaDue to the widespread use of mobile intelligent terminal devices, Mobile Crowd Sensing (MCS) applications have gained significant research attention. However, ensuring users privacy remains a critical challenge, as it can hinder users’ willingness to participate actively in tasks. To address the limitations of existing differential privacy protection methods, this paper proposes a novel privacy protection approach based on Artificial Immune Computing (AICppm). Specifically, private information is concealed within a masking carrier, and data scrambling is avoided. The proposed method involves two main steps: first, a carrier preprocessing approach based on a high-pass filter bank is designed to identify candidate positions for perturbation. Then, a carrier steganography algorithm based on multi-objective optimization is used, transforming the perturbation position into an antibody using the artificial immune algorithm. By iteratively searching for antibodies with higher fitness, the optimal perturbation of the offspring population is identified using the improved Strength Pareto Evolution Algorithm (SPEA2). The experimental results demonstrate that the proposed algorithm can withstand the attacks of malicious steganalysis tools, preserving the integrity of the sensing data and enabling real-time processing of private information.https://ieeexplore.ieee.org/document/10328773/Mobile crowd sensingprivacy-preservingedge computingartificial immune computingsensing data |
| spellingShingle | Hao Long Jiawei Hao Shukui Zhang Yang Zhang Li Zhang A Privacy-Preserving Method Based on Artificial Immune Computing in MCS IEEE Access Mobile crowd sensing privacy-preserving edge computing artificial immune computing sensing data |
| title | A Privacy-Preserving Method Based on Artificial Immune Computing in MCS |
| title_full | A Privacy-Preserving Method Based on Artificial Immune Computing in MCS |
| title_fullStr | A Privacy-Preserving Method Based on Artificial Immune Computing in MCS |
| title_full_unstemmed | A Privacy-Preserving Method Based on Artificial Immune Computing in MCS |
| title_short | A Privacy-Preserving Method Based on Artificial Immune Computing in MCS |
| title_sort | privacy preserving method based on artificial immune computing in mcs |
| topic | Mobile crowd sensing privacy-preserving edge computing artificial immune computing sensing data |
| url | https://ieeexplore.ieee.org/document/10328773/ |
| work_keys_str_mv | AT haolong aprivacypreservingmethodbasedonartificialimmunecomputinginmcs AT jiaweihao aprivacypreservingmethodbasedonartificialimmunecomputinginmcs AT shukuizhang aprivacypreservingmethodbasedonartificialimmunecomputinginmcs AT yangzhang aprivacypreservingmethodbasedonartificialimmunecomputinginmcs AT lizhang aprivacypreservingmethodbasedonartificialimmunecomputinginmcs AT haolong privacypreservingmethodbasedonartificialimmunecomputinginmcs AT jiaweihao privacypreservingmethodbasedonartificialimmunecomputinginmcs AT shukuizhang privacypreservingmethodbasedonartificialimmunecomputinginmcs AT yangzhang privacypreservingmethodbasedonartificialimmunecomputinginmcs AT lizhang privacypreservingmethodbasedonartificialimmunecomputinginmcs |