Outputs (195)

CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images (2023)
Journal Article
Liu, Q., Li, Y., Bilal, M., Liu, X., Zhang, Y., Wang, H., & Xu, X. (2023). CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 2481-2491. https://doi.org/10.1109/jstars.2023.3244336

In recent years, AI and Deep Learning (DL) methods have been widely used for object classification, recognition, and segmentation of high-resolution multispectral remote sensing images. These DL-based solutions perform better compare to traditional s... Read More about CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images.

Explainable AI-Based DDOS Attack Identification Method for IoT Networks (2023)
Journal Article
Kalutharage, C. S., Liu, X., Chrysoulas, C., Pitropakis, N., & Papadopoulos, P. (2023). Explainable AI-Based DDOS Attack Identification Method for IoT Networks. Computers, 12(2), Article 32. https://doi.org/10.3390/computers12020032

The modern digitized world is mainly dependent on online services. The availability of online systems continues to be seriously challenged by distributed denial of service (DDoS) attacks. The challenge in mitigating attacks is not limited to identify... Read More about Explainable AI-Based DDOS Attack Identification Method for IoT Networks.

An Input Sampling Scheme to Radar Echo Extrapolation For RNN-Based Models (2022)
Presentation / Conference Contribution
Wang, Y., Yang, Z., Liu, Q., & Liu, X. (2022, September). An Input Sampling Scheme to Radar Echo Extrapolation For RNN-Based Models. Presented at 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), Falerna, Italy

Short-term heavy rainfall can have a significant impact on people's production, life and travel. Numerical Weather Prediction (NWP) is complex. It can predict weather conditions for the next week or even two weeks, but cannot predict the weather in t... Read More about An Input Sampling Scheme to Radar Echo Extrapolation For RNN-Based Models.

Emerging Simulation Frameworks for Analyzing Smart Grid Cyberattack: A Literature Review (2022)
Presentation / Conference Contribution
Darteh, O. F., Liu, Q., Liu, X., Bah, I., Nakoty, F. M., & Acakpovi, A. (2022, September). Emerging Simulation Frameworks for Analyzing Smart Grid Cyberattack: A Literature Review. Presented at 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), Falerna, Italy

The transition of the conventional power grid into the Smart Grid (SG), a widely distributed energy delivery network characterized by a two-way flow of electricity and information, is key for energy sector stakeholders. Despite the SG’s clear improve... Read More about Emerging Simulation Frameworks for Analyzing Smart Grid Cyberattack: A Literature Review.

Dense-FCN: A Deep Learning Approach for Weather Radar Beam Blockage Correction (2022)
Presentation / Conference Contribution
Sun, J., Wu, H., Liu, Q., Liu, X., & Ma, J. (2022, September). Dense-FCN: A Deep Learning Approach for Weather Radar Beam Blockage Correction. Presented at 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), Falerna, Italy

The weather radar will receive a lot of non-meteorological echo information during the body scan process, such as: object echoes, co-wave interference echoes, airplanes, flocks of birds, etc. These non-meteorological echoes will cause pollution to no... Read More about Dense-FCN: A Deep Learning Approach for Weather Radar Beam Blockage Correction.

Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract) (2022)
Presentation / Conference Contribution
Kalutharage, C. S., Liu, X., & Chrysoulas, C. (2022, September). Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract). Presented at 27th European Symposium on Research in Computer Security (ESORICS) 2022, Copenhagen, Denmark

Over the past few decades, Machine Learning (ML)-based intrusion detection systems (IDS) have become increasingly popular and continue to show remarkable performance in detecting attacks. However, the lack of transparency in their decision-making pro... Read More about Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract).

A survey of intelligent load monitoring in IoT-enabled distributed smart grids (2022)
Journal Article
Gan, J., Zeng, L., Liu, Q., & Liu, X. (2023). A survey of intelligent load monitoring in IoT-enabled distributed smart grids. International Journal of Ad Hoc and Ubiquitous Computing, 42(1), 12. https://doi.org/10.1504/ijahuc.2023.127781

Power load monitoring has been a research hotspot since a few years ago. With development of artificial intelligence, construction of smart grid has become the most important part of power load monitoring. At the same time, task scheduling mechanism... Read More about A survey of intelligent load monitoring in IoT-enabled distributed smart grids.

A Survey on the Integration of Blockchain and IoT: Challenges and Opportunities (2022)
Book Chapter
Abubakar, M., Jaroucheh, Z., Al-Dubai, A., & Liu, X. (2022). A Survey on the Integration of Blockchain and IoT: Challenges and Opportunities. In R. Jiang, A. Bouridane, C.-T. Li, D. Crookes, S. Boussakta, F. Hao, & E. A. Edirisinghe (Eds.), Big Data Privacy and Security in Smart Cities (197-221). Springer. https://doi.org/10.1007/978-3-031-04424-3_11

Since Satoshi Nakamoto first introduced the blockchain as an open-source project for secure financial transactions, it has attracted the scientific community’s interest, paving the way for addressing problems in domains other than cryptocurrencies, o... Read More about A Survey on the Integration of Blockchain and IoT: Challenges and Opportunities.

A Lightweight and User-centric Two-factor Authentication Mechanism for IoT Based on Blockchain and Smart Contract (2022)
Presentation / Conference Contribution
Abubakar, M., Jaroucheh, Z., Al Dubai, A., & Liu, X. (2022, May). A Lightweight and User-centric Two-factor Authentication Mechanism for IoT Based on Blockchain and Smart Contract. Presented at 2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH), Riyadh, Saudi Arabia

Two-factor authentication (2FA) is commonly used in Internet of Things (IoT) authentication to provide multi-layer protection. Tokens, often known as One-Time Passwords (OTP), are used to offer additional information. While this technique provides fl... Read More about A Lightweight and User-centric Two-factor Authentication Mechanism for IoT Based on Blockchain and Smart Contract.

A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars (2022)
Journal Article
Yang, Z., Wu, H., Liu, Q., Liu, X., Zhang, Y., & Cao, X. (2023). A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars. ISA Transactions, 132, 155-166. https://doi.org/10.1016/j.isatra.2022.06.046

In recent years, the number of weather-related disasters significantly increases across the world. As a typical example, short-range extreme precipitation can cause severe flooding and other secondary disasters, which therefore requires accurate pred... Read More about A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars.