Computer Journal

Papers
(The H4-Index of Computer Journal is 18. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-08-01 to 2026-08-01.)
ArticleCitations
Towards Accurate Smartphone Localization Using CSI Measurements126
Analysis and Construction of Zero-Knowledge Proofs for the MinRank Problem105
Special Issue on Failed Approaches and Insightful Losses in Cryptology — Foreword43
Thematic Editorial: Mostly Artificial Intelligence (AI) or Machine Learning (ML) Now in the Engine Room, in Pursuit of a Green Agenda38
A hybrid architecture for secure data sharing in multi-clouds system34
Developing an intelligent framework with Blockchain capabilities for environmental monitoring using a CubeSat32
Menger-Type Connectivity of Line Graphs of Generalized Hypercubes With Faulty Edges31
2L-LSH: A Locality-Sensitive Hash Function-Based Method For Rapid Point Cloud Indexing27
Enhancing conversational agent responses with EXLNetT using learnable enhanced Laplacian kernel attention mechanism, deep bi-affine network, and hybrid positional encoding23
A New Approach of Evaluating the Security Against Differential and Linear Cryptanalysis and Its Applications to Serpent, NOEKEON and ASCON23
Authentication safety: safe on-demand concurrent authentication under transient faults and arbitrary initialization22
Singular value decomposition-based graph densification for link prediction in sparse graphs22
Time-Aware Data Partition Optimization and Heterogeneous Task Scheduling Strategies in Spark Clusters20
A study of improved k-anonymity privacy-preserving algorithms for data sharing20
Minority sample selection in fraud detection with classifier-based reinforcement learning19
Gaussian process regression based on random projections and dynamic pseudo-input selection18
RPKClust: region-partitioned keywords inference for binary protocol reverse18
Online Optimization Method of Learning Process for Meta-Learning18
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