Outputs (274)

Power Consuming Activity Recognition in Home Environment (2017)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2017). Power Consuming Activity Recognition in Home Environment. In X. Sun, H. Chao, X. You, & E. Bertino (Eds.), Cloud Computing and Security. ICCCS 2017 (361-372). https://doi.org/10.1007/978-3-319-68505-2_31

This work proposed an activity recognition model which focus on the power con-suming activity in home environment, to help residents modify their behavior. We set the IoT system with lower number of sensors. The key data for identifying activity come... Read More about Power Consuming Activity Recognition in Home Environment.

An Energy-Efficiency Routing Scheme Based on Clusters with a Mobile Sink for WSNs (2017)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2017). An Energy-Efficiency Routing Scheme Based on Clusters with a Mobile Sink for WSNs. In X. Sun, H. C. Chao, X. You, & E. Bertino (Eds.), Cloud Computing and Security (ICCCS 2017) (450-459). https://doi.org/10.1007/978-3-319-68505-

With the development of microelectronic devices and the radio, the application of WSN is more popular and can be applied in the various areas, which has attracted scholars. However, the requirements of performance for WSNs are becoming great in terms... Read More about An Energy-Efficiency Routing Scheme Based on Clusters with a Mobile Sink for WSNs.

Hiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse (2017)
Presentation / Conference Contribution
Kintis, P., Miramirkhani, N., Lever, C., Chen, Y., Romero-Gómez, R., Pitropakis, N., …Antonakakis, M. (2017). Hiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse. In CCS '17 Proceedings of the 2017 ACM SIGSAC Conference on Computer and

Domain squatting is a common adversarial practice where attackers register domain names that are purposefully similar to popular domains. In this work, we study a specific type of domain squatting called "combosquatting," in which attackers register... Read More about Hiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse.

Load Balancing Objective Function in RPL (Draft 2) (2017)
Report
Qasem, M., Al-Dubai, A., Romdhani, I., Ghaleb, B., Hou, J., & Jadhav, R. A. (2017). Load Balancing Objective Function in RPL (Draft 2). USA: IETF

This document proposes an extended Objective Function(OF) that balances the number of child nodes of the parent nodes to avoid the overloading problem and ensure node lifetime maximization in the IPv6 Routing Protocol for Low-Power and Lossy Ne... Read More about Load Balancing Objective Function in RPL (Draft 2).

Learning from Few Samples with Memory Network (2017)
Journal Article
Zhang, S., Huang, K., Zhang, R., & Hussain, A. (2018). Learning from Few Samples with Memory Network. Cognitive Computation, 10(1), 15-22. https://doi.org/10.1007/s12559-017-9507-z

Neural networks (NN) have achieved great successes in pattern recognition and machine learning. However, the success of a NN usually relies on the provision of a sufficiently large number of data samples as training data. When fed with a limited data... Read More about Learning from Few Samples with Memory Network.

Towards an Accurate Identification of Pyloric Neuron Activity with VSDi (2017)
Presentation / Conference Contribution
dos Santos, F., Andras, P., & Lam, K. (2017). Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. In Artificial Neural Networks and Machine Learning – ICANN 2017 (121-128). https://doi.org/10.1007/978-3-319-68600-4_15

Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important technique to supplement electrophysiological recordings. However, utilising the te... Read More about Towards an Accurate Identification of Pyloric Neuron Activity with VSDi.

Improve deep learning with unsupervised objective (2017)
Presentation / Conference Contribution
Zhang, S., Huang, K., Zhang, R., & Hussain, A. (2017). Improve deep learning with unsupervised objective. . https://doi.org/10.1007/978-3-319-70087-8_74

We propose a novel approach capable of embedding the unsupervised objective into hidden layers of the deep neural network (DNN) for preserving important unsupervised information. To this end, we exploit a very simple yet effective unsupervised method... Read More about Improve deep learning with unsupervised objective.

Building identity in online environments: an Information Science perspective (2017)
Presentation / Conference Contribution
Ryan, F. V. C., Cruickshank, P., Hall, H., & Lawson, A. (2018). Building identity in online environments: an Information Science perspective. Proceedings of the Association for Information Science and Technology, 54(1), 792-793. https://doi.org/10.1002/pr

The research presented in this poster is concerned with the ways in which people use information to build identities for themselves online with reference to the themes of personal reputation management. To date these two themes have been under-explor... Read More about Building identity in online environments: an Information Science perspective.

A multiresolution approach to the extraction of the pyloric rhythm (2017)
Presentation / Conference Contribution
dos Santos, F., Andras, P., & Lam, K. (2017). A multiresolution approach to the extraction of the pyloric rhythm. In 2017 40th International Conference on Telecommunications and Signal Processing (TSP) (403-406). https://doi.org/10.1109/TSP.2017.8076015

This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus using voltage-sensitive dye imaging. The multi-resolution signal decompositi... Read More about A multiresolution approach to the extraction of the pyloric rhythm.

A Machine Learning Approach to Detect Router Advertisement Flooding Attacks in Next-Generation IPv6 Networks (2017)
Journal Article
Anbar, M., Abdullah, R., Al-Tamimi, B. N., & Hussain, A. (2018). A Machine Learning Approach to Detect Router Advertisement Flooding Attacks in Next-Generation IPv6 Networks. Cognitive Computation, 10(2), 201-214. https://doi.org/10.1007/s12559-017-9519-8

Router advertisement (RA) flooding attack aims to exhaust all node resources, such as CPU and memory, attached to routers on the same link. A biologically inspired machine learning-based approach is proposed in this study to detect RA flooding attack... Read More about A Machine Learning Approach to Detect Router Advertisement Flooding Attacks in Next-Generation IPv6 Networks.