AIMC Topic: Computer Security

Clear Filters Showing 271 to 280 of 455 articles

Temporal Weighted Averaging for Asynchronous Federated Intrusion Detection Systems.

Computational intelligence and neuroscience
Federated learning (FL) is an emerging subdomain of machine learning (ML) in a distributed and heterogeneous setup. It provides efficient training architecture, sufficient data, and privacy-preserving communication for boosting the performance and fe...

Byzantine-robust federated learning via credibility assessment on non-IID data.

Mathematical biosciences and engineering : MBE
Federated learning is a novel framework that enables resource-constrained edge devices to jointly learn a model, which solves the problem of data protection and data islands. However, standard federated learning is vulnerable to Byzantine attacks, wh...

A machine and human reader study on AI diagnosis model safety under attacks of adversarial images.

Nature communications
While active efforts are advancing medical artificial intelligence (AI) model development and clinical translation, safety issues of the AI models emerge, but little research has been done. We perform a study to investigate the behaviors of an AI dia...

Is Homomorphic Encryption-Based Deep Learning Secure Enough?

Sensors (Basel, Switzerland)
As the amount of data collected and analyzed by machine learning technology increases, data that can identify individuals is also being collected in large quantities. In particular, as deep learning technology-which requires a large amount of analysi...

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions.

Sensors (Basel, Switzerland)
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices...

Intelligent Techniques for Detecting Network Attacks: Review and Research Directions.

Sensors (Basel, Switzerland)
The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempt...

The Impact of Artificial Intelligence on Data System Security: A Literature Review.

Sensors (Basel, Switzerland)
Diverse forms of artificial intelligence (AI) are at the forefront of triggering digital security innovations based on the threats that are arising in this post-COVID world. On the one hand, companies are experiencing difficulty in dealing with secur...

Enabling Security Services in Socially Assistive Robot Scenarios for Healthcare Applications.

Sensors (Basel, Switzerland)
Today's IoT deployments are highly complex, heterogeneous and constantly changing. This poses severe security challenges such as limited end-to-end security support, lack of cross-platform cross-vertical security interoperability as well as the lack ...

Detecting phishing websites using machine learning technique.

PloS one
In recent years, advancements in Internet and cloud technologies have led to a significant increase in electronic trading in which consumers make online purchases and transactions. This growth leads to unauthorized access to users' sensitive informat...

A static analysis approach for Android permission-based malware detection systems.

PloS one
The evolution of malware is causing mobile devices to crash with increasing frequency. Therefore, adequate security evaluations that detect Android malware are crucial. Two techniques can be used in this regard: Static analysis, which meticulously ex...