AIMC Topic: Computer Security

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An efficient detection of Sinkhole attacks using machine learning: Impact on energy and security.

PloS one
In the realm of Wireless Sensor Networks (WSNs), the detection and mitigation of sinkhole attacks remain pivotal for ensuring network integrity and efficiency. This paper introduces SFlexCrypt, an innovative approach tailored to address these securit...

A malware classification method based on directed API call relationships.

PloS one
In response to the growing complexity of network threats, researchers are increasingly turning to machine learning and deep learning techniques to develop advanced models for malware detection. Many existing methods that utilize Application Programmi...

[Focus: artificial intelligence in medicine-Legal aspects of using large language models in clinical practice].

Innere Medizin (Heidelberg, Germany)
BACKGROUND: The use of artificial intelligence (AI) and natural language processing (NLP) methods in medicine, particularly large language models (LLMs), offers opportunities to advance the healthcare system and patient care in Germany. LLMs have rec...

Patient consent for the secondary use of health data in artificial intelligence (AI) models: A scoping review.

International journal of medical informatics
BACKGROUND: The secondary use of health data for training Artificial Intelligence (AI) models holds immense potential for advancing medical research and healthcare delivery. However, ensuring patient consent for such utilization is paramount to uphol...

Opportunistic access control scheme for enhancing IoT-enabled healthcare security using blockchain and machine learning.

Scientific reports
The healthcare industry, aided by technology, leverages the Internet of Things (IoT) paradigm to offer patient/user-related services that are ubiquitous and personalized. The authorized repository stores ubiquitous data for which access-level securit...

Neural-network-based practical specified-time resilient formation maneuver control for second-order nonlinear multi-robot systems under FDI attacks.

Neural networks : the official journal of the International Neural Network Society
This paper presents a specified-time resilient formation maneuver control approach for second-order nonlinear multi-robot systems under false data injection (FDI) attacks, incorporating an offline neural network. Building on existing works in integra...

Reconfigurable security solution based on hopfield neural network for e-healthcare applications.

Scientific reports
In the healthcare sector, e-diagnosis through medical images is essential in a multi-speciality hospital; securing the medical images becomes crucial for preserving an individual's privacy in e-healthcare applications. So, this paper has proposed a n...

From challenges and pitfalls to recommendations and opportunities: Implementing federated learning in healthcare.

Medical image analysis
Federated learning holds great potential for enabling large-scale healthcare research and collaboration across multiple centers while ensuring data privacy and security are not compromised. Although numerous recent studies suggest or utilize federate...

A novel deep learning-based framework with particle swarm optimisation for intrusion detection in computer networks.

PloS one
Intrusion detection plays a significant role in the provision of information security. The most critical element is the ability to precisely identify different types of intrusions into the network. However, the detection of intrusions poses a importa...

Fast finite-time quantized control of multi-layer networks and its applications in secure communication.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a quantized controller to address the challenge of fast finite-time synchronization of multi-layer networks, where each layer represents a distinct type of interaction within complex systems. Firstly, based on the stability theo...