AIMC Topic: Computer Security

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Multilayered SDN security with MAC authentication and GAN-based intrusion detection.

PloS one
Computer networks are highly vulnerable to cybersecurity intrusions. Likewise, software-defined networks (SDN), which enable 5G users to broadcast sensitive data, have become a primary target for vulnerability. To protect the network security against...

Improving the accuracy of cybersecurity spam email detection using ensemble techniques: A stacking approach Machine learning for spam email detection.

PloS one
With the widespread adoption of internet technologies and email communication systems, the exponential growth in email usage has precipitated a corresponding surge in spam proliferation. These unsolicited messages not only consume users' valuable tim...

A machine learning approach for detecting WPA3 downgrade attacks in next-generation Wi-Fi systems.

PloS one
This paper presents a hybrid adaptive approach based on machine learning (ML) for classifying incoming traffic, feature selection and thresholding, aimed at enhancing downgrade attack detection in Wi-Fi Protected Access 3 (WPA3) networks. The fast pr...

MACML: Marrying attention and convolution-based meta-learning method for few-shot IoT intrusion detection.

PloS one
The widespread deployment of Internet of Things (IoT) devices has made them prime targets for cyberattacks. Existing intrusion detection systems (IDSs) heavily rely on large-scale labeled datasets, which limits their effectiveness in detecting novel ...

Mapping interconnectivity of digital twin healthcare research themes through structural topic modeling.

Scientific reports
Digital twin (DT) technology is revolutionizing healthcare systems by leveraging real-time data integration and advanced analytics to enhance patient care, optimize clinical operations, and facilitate simulation. This study aimed to identify key rese...

Identifying significant features in adversarial attack detection framework using federated learning empowered medical IoT network security.

Scientific reports
The expansion of the Internet of Medical Things (IoHT) presents significant advantages for healthcare over improved data-driven insights and connectivity and offers critical cybersecurity challenges. Attacks are a serious risk for neural network secu...

Hybrid deep learning-enabled framework for enhancing security, data integrity, and operational performance in Healthcare Internet of Things (H-IoT) environments.

Scientific reports
The increasing reliance on Human-centric Internet of Things (H-IoT) systems in healthcare and smart environments has raised critical concerns regarding data integrity, real-time anomaly detection, and adaptive access control. Traditional security mec...

A comprehensive survey of deep face verification systems adversarial attacks and defense strategies.

Scientific reports
Face Verification (FV) systems have exhibited remarkable performance in verification tasks and have consequently garnered extensive adoption across various applications, from identity duplication to authentication in mobile payments. However, the sur...

A hybrid ECC-AES encryption framework for secure and efficient cloud-based data protection.

Scientific reports
In digital healthcare, ensuring the privacy and security of sensitive mental health data remains a critical challenge. This paper introduces SymECCipher, a novel hybrid encryption framework that integrates Elliptic Curve Cryptography (ECC) for key ex...

DSTF-GKAN: A lightweight spatiotemporal fusion framework for real-time eavesdropping detection in dynamic smart grid networks.

PloS one
With the rapid development of smart grids and the Power Internet of Things (PIoT), wireless communication networks are facing the severe threat of dynamic eavesdropping attacks. Traditional detection methods rely on static assumptions or shallow mode...