Abstract :Transactions Form The Core Of Economic Activities, Representing The Intricate Interplay Between Buyers And Sellers. The Concept Of Exchange Liability Comes Into Focus As These Transactions Unfold Within The Context Of Deceitful Big Data, Where Manipulation And Misinformation Threaten The Trust Upon Which Commerce Relies. The Ramifications Of Misrepresentation Or Falsification Of Information Lead To Adverse Effects, Impacting Both Parties Involved And Potentially Causing Larger Disruptions Across The Market Ecosystem. The Proliferation Of Big Data Has Transformed Consumer-retailer Relationships, Enabling Personalized Experiences And Informed Decisions. However, The Interplay Between Deceitful Actors Within This Data-driven Landscape Necessitates A Comprehensive Exploration Of Liability. This Study Navigates The Nuances Of Liability In Transactions Involving Big Data Consumers And Retailers, Taking Into Account The Challenges Posed By Data Authenticity, Transparency, And Trustworthiness. Through A Synthesis Of Legal Considerations, Ethical Perspectives, And Technological Implications, This Research Delves Into The Multifaceted Nature Of Liability In Transaction Exchange Within The Realm Of Deceitful Big Data. By Elucidating The Responsibilities And Potential Consequences, The Study Aims To Shed Light On Strategies That Can Be Adopted To Mitigate Risks, Foster Transparency, And Promote Fair Interactions Between Consumers And Retailers. Due To The Data Outsourcing, However, This New Paradigm Of Data Hosting Service Also Introduces New Security Challenges. Some Existing Remote Integrity Checking Methods Can Only Serve For Static Archive Data And Thus Cannot Be Applied To The Auditing Service Since The Data In The Cloud Can Be Dynamically Updated. Thus, An Efficient And Secure Dynamic Auditing Protocol Is Desired To Convince Data Owners That The Data Are Correctly Stored In The Cloud. In This Paper, We First Design An Auditing Framework For Cloud Storage Systems And Propo |
Published:09-6-2025 Issue:Vol. 25 No. 6 (2025) Page Nos:329-335 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to Cite |