Deception detection with machine learning: A systematic review and statistical analysis
Several studies applying Machine Learning to deception detection have been published in
the last decade. A rich and complex set of settings, approaches, theories, and results is now …
the last decade. A rich and complex set of settings, approaches, theories, and results is now …
Evaluation of the critical success factors of dynamic enterprise risk management in manufacturing SMEs using an integrated fuzzy decision-making model
D Zhu, Z Li, AR Mishra - Technological Forecasting and Social Change, 2023 - Elsevier
To succeed, a firm essentially needs to take the right amount of risk. Thus, the great
significance of risk management has attracted many researchers to focus on how to …
significance of risk management has attracted many researchers to focus on how to …
Optimized machine learning-based intrusion detection system for fog and edge computing environment
As a new paradigm, fog computing (FC) has several characteristics that set it apart from the
cloud computing (CC) environment. Fog nodes and edge computing (EC) hosts have limited …
cloud computing (CC) environment. Fog nodes and edge computing (EC) hosts have limited …
Fusion of deep learning based cyberattack detection and classification model for intelligent systems
In recent years, the exponential growth of malware has posed a significant security threat to
intelligent systems. Earlier static and dynamic analysis methods fail to achieve effective …
intelligent systems. Earlier static and dynamic analysis methods fail to achieve effective …
[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …
the threat of malware to computer system, android-based smart phones, Internet of Things …
[HTML][HTML] Comparison of multiclass classification techniques using dry bean dataset
Background The application of classsification methods through multivariate and machine
learning techniques has enormous significance in agricultural sector. It is vital to classify …
learning techniques has enormous significance in agricultural sector. It is vital to classify …
SG-PBFS: Shortest gap-priority based fair scheduling technique for job scheduling in cloud environment
Job scheduling in cloud computing plays a crucial role in optimizing resource utilization and
ensuring efficient job allocation. But cloud resources may be wasted, or service performance …
ensuring efficient job allocation. But cloud resources may be wasted, or service performance …
[HTML][HTML] COVID-19 detection and classification for machine learning methods using human genomic data
MT Ahemad, MA Hameed, R Vankdothu - Measurement: Sensors, 2022 - Elsevier
Coronavirus is a disease connected to coronavirus. World Health Organization has declared
COVID-19 a pandemic. It has an impact on 212 nations and territories worldwide. Examining …
COVID-19 a pandemic. It has an impact on 212 nations and territories worldwide. Examining …
Quantum Mayfly optimization with encoder-decoder driven LSTM networks for malware detection and classification model
Malware refers to malicious software developed to penetrate or damage a computer system
without any owner's informed consent. It uses target system susceptibilities, like bugs in …
without any owner's informed consent. It uses target system susceptibilities, like bugs in …
Metaheuristics with deep learning model for cybersecurity and Android malware detection and classification
Since the development of information systems during the last decade, cybersecurity has
become a critical concern for many groups, organizations, and institutions. Malware …
become a critical concern for many groups, organizations, and institutions. Malware …