OOIR: Observatory of International Research

Papers

(The H4-Index of Computers & Security is 49. 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 2020-11-01 to 2024-11-01.)

Article	Citations
Cyber security in the age of COVID-19: A timeline and analysis of cyber-crime and cyber-attacks during the pandemic	333
Cybersecurity for autonomous vehicles: Review of attacks and defense	217
An effective intrusion detection approach using SVM with naïve Bayes feature embedding	184
Privacy preservation in federated learning: An insightful survey from the GDPR perspective	137
A systematic literature review of methods and datasets for anomaly-based network intrusion detection	130
The internet of things security: A survey encompassing unexplored areas and new insights	112
Resource allocation and trust computing for blockchain-enabled edge computing system	108
Deep learning for insider threat detection: Review, challenges and opportunities	107
A fast network intrusion detection system using adaptive synthetic oversampling and LightGBM	106
Integration of blockchain and federated learning for Internet of Things: Recent advances and future challenges	103
Never trust, always verify: A multivocal literature review on current knowledge and research gaps of zero-trust	100
A blockchain-based scheme for privacy-preserving and secure sharing of medical data	100
GDroid: Android malware detection and classification with graph convolutional network	99
A zero-knowledge-proof-based digital identity management scheme in blockchain	92
Ransomware: Recent advances, analysis, challenges and future research directions	91
A survey on wireless body area networks: architecture, security challenges and research opportunities	86
Enhancing employees information security awareness in private and public organisations: A systematic literature review	86
A novel combinatorial optimization based feature selection method for network intrusion detection	84
A survey on security attacks and defense techniques for connected and autonomous vehicles	83
EfficientNet convolutional neural networks-based Android malware detection	83
An effective genetic algorithm-based feature selection method for intrusion detection systems	80
STL-HDL: A new hybrid network intrusion detection system for imbalanced dataset on big data environment	79
A survey of empirical performance evaluation of permissioned blockchain platforms: Challenges and opportunities	76
Developing cybersecurity culture to influence employee behavior: A practice perspective	75
CSE-IDS: Using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems	75

Intrusion detection methods based on integrated deep learning model	74
Catch them alive: A malware detection approach through memory forensics, manifold learning and computer vision	73
Integration of federated machine learning and blockchain for the provision of secure big data analytics for Internet of Things	73
JOWMDroid: Android malware detection based on feature weighting with joint optimization of weight-mapping and classifier parameters	70
A comprehensive study of DDoS attacks over IoT network and their countermeasures	69
How can organizations develop situation awareness for incident response: A case study of management practice	66
Applying machine learning and natural language processing to detect phishing email	66
Towards an interpretable deep learning model for mobile malware detection and family identification	64
A novel architecture for web-based attack detection using convolutional neural network	63
Developing a cyber security culture: Current practices and future needs	61
A systematic threat analysis and defense strategies for the metaverse and extended reality systems	60
Recurrent neural network for detecting malware	60
Machine learning for encrypted malicious traffic detection: Approaches, datasets and comparative study	59
Optimized extreme learning machine for detecting DDoS attacks in cloud computing	59
Authentication and Identity Management of IoHT Devices: Achievements, Challenges, and Future Directions	59
A survey of machine learning techniques in adversarial image forensics	57
Hardening machine learning denial of service (DoS) defences against adversarial attacks in IoT smart home networks	57
Cloud computing security: A survey of service-based models	56
Latest trends of security and privacy in recommender systems: A comprehensive review and future perspectives	56
A new DDoS attacks intrusion detection model based on deep learning for cybersecurity	55
KronoDroid: Time-based Hybrid-featured Dataset for Effective Android Malware Detection and Characterization	51
Characterizing cryptocurrency exchange scams	51
RNNIDS: Enhancing network intrusion detection systems through deep learning	50
Cybercrime threat intelligence: A systematic multi-vocal literature review	50
Information security governance challenges and critical success factors: Systematic review	49
Assessing IoT enabled cyber-physical attack paths against critical systems	49
Survey on smart homes: Vulnerabilities, risks, and countermeasures	49