Machine-learning-based darknet traffic detection system for IoT applications

Q Abu Al-Haija, M Krichen, W Abu Elhaija - Electronics, 2022 - mdpi.com
The massive modern technical revolution in electronics, cognitive computing, and sensing
has provided critical infrastructure for the development of today's Internet of Things (IoT) for a …

Anomaly detection in Internet of medical Things with Blockchain from the perspective of deep neural network

J Wang, H Jin, J Chen, J Tan, K Zhong - Information Sciences, 2022 - Elsevier
IoMT technology has many advantages in healthcare system, such as optimizing the
medical service model, improving the efficiency of hospital operation and management, and …

[HTML][HTML] Identifying the latent relationships between factors associated with traffic crashes through graphical models

MB Ulak, EE Ozguven - Accident Analysis & Prevention, 2024 - Elsevier
Traffic safety field has been oriented toward finding the relationships between crash
outcomes and predictor variables to understand crash phenomena and/or predict future …

Designing comprehensive cyber threat analysis platform: Can we orchestrate analysis engines?

T Takahashi, Y Umemura, C Han, T Ban… - … and other Affiliated …, 2021 - ieeexplore.ieee.org
To cope with growing cyber threats on the Internet, various techniques have been proposed
and implemented. Each of these techniques automates specific tasks of cybersecurity …

Dark-TRACER: Early Detection Framework for Malware Activity Based on Anomalous Spatiotemporal Patterns

C Han, J Takeuchi, T Takahashi, D Inoue - IEEE Access, 2022 - ieeexplore.ieee.org
As cyberattacks become increasingly prevalent globally, there is a need to identify trends in
these cyberattacks and take suitable countermeasures quickly. The darknet, an unused IP …

Automated detection of malware activities using nonnegative matrix factorization

C Han, J Takeuchi, T Takahashi… - 2021 IEEE 20th …, 2021 - ieeexplore.ieee.org
Malware is increasingly diversified and sophisti-cated. It is essential to rapidly and
accurately detect malware activities when malware infection spreads. However, accurately …

FINISH: Efficient and Scalable NMF-Based Federated Learning for Detecting Malware Activities

YW Chang, HY Chen, C Han… - … on Emerging Topics …, 2023 - ieeexplore.ieee.org
5G networks with the vast number of devices pose security threats. Manual analysis of such
extensive security data is complex. Dark-NMF can detect malware activities by monitoring …

Internet-wide scanner fingerprint identifier based on TCP/IP header

A Tanaka, C Han, T Takahashi… - 2021 Sixth International …, 2021 - ieeexplore.ieee.org
Identifying individual scan activities is a crucial and challenging activity for mitigating
emerging cyber threats or gaining insights into security scans. Sophisticated adversaries …

Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data

X Tan, Y Shen, M Wang, B Wang - Proceedings of the 32nd ACM …, 2023 - dl.acm.org
Graph knowledge discovery from graph-structured data is a fascinating data mining topic in
various domains, especially in the Internet of Things, where inferring the graph structure …

Darknet Analysis-Based Early Detection Framework for Malware Activity: Issue and Potential Extension

C Han, A Tanaka, T Takahashi - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Most packets arriving in the darknet (or network telescope), which is unused IP address
space on the Internet, are related to indiscriminate scanning and attack activities. In recent …