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The domain of Mobile Edge Computing (MEC) has seen rapid growth, making consumer behavior research an essential element in many applications. Nevertheless, in MEC systems that are decentralized and have limited resources, challenges arise in ensuring both data integrity and access control. This paper introduces a new technique called Quantum Hash-Based Attribute-Based Encryption (QH-ABE) to address these issues. Previously, there were several methods available to guarantee data integrity and access control in MEC. However, these systems had limits in managing large and intricate datasets, lacked a standardized protocol for revocation, and incurred significant computational cost. We were prompted by these restrictions to suggest a more efficient technique, which included the use of the QH-ABE method in our study. The suggested solution integrates hash functions with quantum computing concepts to enhance security and control access in MEC-enabled consumer behavior research. The suggested technique provides several benefits compared to traditional hash algorithms by using hash functions. In this technique, we introduce a Recursive Non-Linear Polynomial graph-centered Integrity Algorithm (RNLPIA). RNLPIA enhances security by thwarting covert alterations to data and guaranteeing tamper-evident measures via the generation of unique hash values derived from the content of the data. The suggested method&#x2019;s efficacy and efficiency are proved by a comprehensive experimental assessment, highlighting its capability to fulfill the data integrity and access control needs of MEC situations. The performance of our technology showcases its potential and paves the way for using quantum computing technologies for accessing control and data security. This work contributes to the progress of privacy-preserving, secure analysis of consumer behavior in the dynamic MEC environment.

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A Novel Quantum Hash-Based Attribute-Based Encryption Approach for Secure Data Integrity and Access Control in Mobile Edge Computing-Enabled Customer Behavior Analysis