Evidence map›Paper›PMID 42071035›Full record

ArticleScientific reports2026

Advanced security in fog environments using encryption and adaptive user activity tracking.

Hari Mohan Rai, Abdul Razaque, Neha Agarwal, Saurabh Agarwal, Hanaa A Abdallah, Shashi Kant

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hari Mohan Rai *Department of Computer Science, School of Engineering and Digital Sciences, Nazarbayev University, Astana, 010000, Kazakhstan.
Abdul Razaque *Department of Cybersecurity, International Information Technology University, Almaty, Kazakhstan.
Neha Agarwal *School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.
Saurabh AgarwalSchool of Computer Science and Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea. saurabh@yu.ac.kr.
Hanaa A AbdallahDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Shashi KantDepartment of Management, College of Business and Economics, Bule Hora University, Bule Hora, Ethiopia. shashi.kant@bhu.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of fog computing is on the rise, adding new dimensions to security and, more specifically, to data protection in fog cloud environments. Storing fog-computing data increases the likelihood of data exploitation when it is uploaded to fog-computing storage. In this paper, Adaptable User Activity Tracking (ASUT) is introduced, integrating AES-256, SHA-512, and user activity tracking (UAT). The need to integrate activity monitoring into the ASUT to collect statistical information on user actions has been stated. The file uploaded to the fog computing storage is encrypted using a 256-bit AES key. Then, this key is hashed with SHA-512 and stored in the fog cloud. The AES expansion is used to decrypt the data, while the SHA-512 hash of the AES key is used to verify that the user-provided key matches the original before decryption proceeds-the hash is irreversible, and the original key is never stored in plaintext. The user must know the initial key to access the file further. When the client re-enters the fog, the algorithm compares the hashes of the two: the initial and the second entry keys. In parallel, the fog cloud broadcasts the user's actions to track any abnormal activity on the account. This mechanism helps mitigate risks of unauthorized data access and suggests ways to improve user protection. The proposed ASUT is designed using Python and PHP. Experimental results show that ASUT achieves 43.39% faster encryption, 66% faster decryption, and 19.86% higher throughput compared to the best-performing competing method, indicating improved computational efficiency and practical feasibility under the evaluated conditions.

Indexed as

Confidential data securityCybersecurityEncrypting algorithmFog computingUser activity tracking

Identifiers

PMID42071035
PMCPMC13226734

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.