Deriving ChaCha20 Key Streams From Targeted Memory Analysis
Journal Article
McLaren, P., Buchanan, W. J., Russell, G., & Tan, Z. (2019)
Deriving ChaCha20 Key Streams From Targeted Memory Analysis. Journal of Information Security and Applications, 48, https://doi.org/10.1016/j.jisa.2019.102372
There can be performance and vulnerability concerns with block ciphers, thus stream ciphers can used as an alternative. Although many symmetric key stream ciphers are fairly r...
Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things
Thesis
Ghaleb, B. Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/Output/2070542
At the heart of the Internet of Things (IoTs) are the Low-power and Lossy networks (LLNs), a collection of interconnected battery-operated and resource-constrained tiny device...
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks
Journal Article
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019)
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371
High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning,...
Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities
Journal Article
Erhan, L., Ndubuaku, M., Ferrara, E., Richardson, M., Sheffield, D., Ferguson, F. J., …Liotta, A. (2019)
Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities. IEEE Access, 7, 19890-19906. https://doi.org/10.1109/access.2019.2897217
The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data ...
A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system
Conference Proceeding
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2018)
A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. In Proceedings of the IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2018)https://doi.org/10.1109/CyberSecPODS.2018.8560683
Industrial Control Systems are part of our daily life in industries such as transportation, water, gas, oil, smart cities, and telecommunications. Technological development ov...
Interference graphs to monitor and control schedules in low-power WPAN
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019)
Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014
Highlights
• This study presents the complete and slotted interference graph model.
• The service uses the complete interference graph to evaluate the network.
• Slotted int...
A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment
Journal Article
Babar, M., Khan, F., Iqbal, . W., Yahya, A., Arif, F., Tan, Z., & Chuma, J. (2018)
A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment. IEEE Access, 6, 43088-43099
Smart societies have an increasing demand for quality-oriented services and infrastructure in an Industrial Internet of Things (IIoT) paradigm. Smart urbanization faces numero...
Reliable and Energy-Efficient Two Levels Unequal Clustering Mechanism for Wireless Sensor Networks
Presentation / Conference
Ali, A. E., Al-Dubai, A., Romdhani, I., & Eshaftri, M. (2018, June)
Reliable and Energy-Efficient Two Levels Unequal Clustering Mechanism for Wireless Sensor Networks. Paper presented at The 16th IEEE International Conference on Smart City (IEEE SmartCity-2018), Exeter, UK
In Wireless Sensor Networks, clustering sensor nodes into disjoint groups is widely used to achieve load balance and increase network lifetime. In particular, traditional uneq...
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018)
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), 1-12. https://doi.org/10.1038/s41467-018-04316-3
Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from ...
An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0
Journal Article
Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019)
An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481-489. https://doi.org/10.1109/tii.2018.2843169
Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and t...