All Outputs (119)

Experimental Review of Neural-Based Approaches for Network Intrusion Management (2020)
Journal Article
Mauro, M. D., Galatro, G., & Liotta, A. (2020). Experimental Review of Neural-Based Approaches for Network Intrusion Management. IEEE Transactions on Network and Service Management, 17(4), 2480-2495. https://doi.org/10.1109/tnsm.2020.3024225

The use of Machine Learning (ML) techniques in Intrusion Detection Systems (IDS) has taken a prominent role in the network security management field, due to the substantial number of sophisticated attacks that often pass undetected through classic ID... Read More about Experimental Review of Neural-Based Approaches for Network Intrusion Management.

Artificial neural networks training acceleration through network science strategies (2020)
Journal Article
Cavallaro, L., Bagdasar, O., De Meo, P., Fiumara, G., & Liotta, A. (2020). Artificial neural networks training acceleration through network science strategies. Soft Computing, 24, https://doi.org/10.1007/s00500-020-05302-y

The development of deep learning has led to a dramatic increase in the number of applications of artificial intelligence. However, the training of deeper neural networks for stable and accurate models translates into artificial neural networks (ANNs)... Read More about Artificial neural networks training acceleration through network science strategies.

Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia (2020)
Journal Article
Cavallaro, L., Ficara, A., De Meo, P., Fiumara, G., Catanese, S., Bagdasar, O., …Liotta, A. (2020). Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia. PLOS ONE, 15(8), Article e0236476. https://doi.org/10.1371/jour

Compared to other types of social networks, criminal networks present particularly hard challenges, due to their strong resilience to disruption, which poses severe hurdles to Law-Enforcement Agencies (LEAs). Herein, we borrow methods and tools from... Read More about Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia.

Evaluating group formation in virtual communities (2020)
Journal Article
Fortino, G., Liotta, A., Messina, F., Rosaci, D., & Sarne, G. M. L. (2020). Evaluating group formation in virtual communities. IEEE/CAA Journal of Automatica Sinica, 7(4), 1003-1015. https://doi.org/10.1109/jas.2020.1003237

In this paper, we are interested in answering the following research question: “ Is it possible to form effective groups in virtual communities by exploiting trust information without significant overhead, similarly to real user communities? ” In ord... Read More about Evaluating group formation in virtual communities.

PmA: A real-world system for people mobility monitoring and analysis based on Wi-Fi probes (2020)
Journal Article
Uras, M., Cossu, R., Ferrara, E., Liotta, A., & Atzori, L. (2020). PmA: A real-world system for people mobility monitoring and analysis based on Wi-Fi probes. Journal of Cleaner Production, 270, Article 122084. https://doi.org/10.1016/j.jclepro.2020.12208

A UN report states that in 2050, about 70% of the total world population will live in cities. This increases the complexity of the services that the local public administrations have to provide the citizens with to keep an acceptable level of quality... Read More about PmA: A real-world system for people mobility monitoring and analysis based on Wi-Fi probes.

An Experimental Evaluation and Characterization of VoIP Over an LTE-A Network (2020)
Journal Article
Di Mauro, M., & Liotta, A. (2020). An Experimental Evaluation and Characterization of VoIP Over an LTE-A Network. IEEE Transactions on Network and Service Management, 17(3), 1626-1639. https://doi.org/10.1109/tnsm.2020.2995505

Mobile telecommunications are converging towards all-IP solutions. This is the case of the Long Term Evolution (LTE) technology that, having no circuit-switched bearer to support voice traffic, needs a dedicated VoIP infrastructure, which often relie... Read More about An Experimental Evaluation and Characterization of VoIP Over an LTE-A Network.

Improved Particle Swarm Optimization for Sea Surface Temperature Prediction (2020)
Journal Article
He, Q., Zha, C., Song, W., Hao, Z., Du, Y., Liotta, A., & Perra, C. (2020). Improved Particle Swarm Optimization for Sea Surface Temperature Prediction. Energies, 13(6), Article 1369. https://doi.org/10.3390/en13061369

The Sea Surface Temperature (SST) is one of the key factors affecting ocean climate change. Hence, Sea Surface Temperature Prediction (SSTP) is of great significance to the study of navigation and meteorology. However, SST data is well-known to suffe... Read More about Improved Particle Swarm Optimization for Sea Surface Temperature Prediction.

An Online Learning Approach to a Multi-player N-armed Functional Bandit (2020)
Presentation / Conference Contribution
O’Neill, S., Bagdasar, O., & Liotta, A. (2020). An Online Learning Approach to a Multi-player N-armed Functional Bandit. In Numerical Computations: Theory and Algorithms (438-445). https://doi.org/10.1007/978-3-030-40616-5_41

Congestion games possess the property of emitting at least one pure Nash equilibrium and have a rich history of practical use in transport modelling. In this paper we approach the problem of modelling equilibrium within congestion games using a decen... Read More about An Online Learning Approach to a Multi-player N-armed Functional Bandit.

Artificial Neural Networks Training Acceleration Through Network Science Strategies (2020)
Presentation / Conference Contribution
Cavallaro, L., Bagdasar, O., De Meo, P., Fiumara, G., & Liotta, A. (2020). Artificial Neural Networks Training Acceleration Through Network Science Strategies. In Numerical Computations: Theory and Algorithms (330-336). https://doi.org/10.1007/978-3-030-

Deep Learning opened artificial intelligence to an unprecedented number of new applications. A critical success factor is the ability to train deeper neural networks, striving for stable and accurate models. This translates into Artificial Neural Net... Read More about Artificial Neural Networks Training Acceleration Through Network Science Strategies.

Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map (2020)
Journal Article
Song, W., Wang, Y., Huang, D., Liotta, A., & Perra, C. (2020). Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map. IEEE Transactions on Broadcasting, 66(1), 153-169. https://doi.org/10.1109/tbc

Underwater images often have severe quality degradation and distortion due to light absorption and scattering in the water medium. A hazy image formation model is widely used to restore the image quality. It depends on two optical parameters: the bac... Read More about Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map.

Cloud-assisted Adaptive Stream Processing from Discriminative Representations (2019)
Presentation / Conference Contribution
Ndubuaku, M., Anjum, A., & Liotta, A. Cloud-assisted Adaptive Stream Processing from Discriminative Representations. . https://doi.org/10.1109/smc.2019.8914227

As the streaming data generated by Internet of Things (IoT) ubiquitous sensors grow in massive scale, extracting interesting information (anomalies) in real-time becomes more challenging. Traditional systems which retrospectively perform all the proc... Read More about Cloud-assisted Adaptive Stream Processing from Discriminative Representations.

Unsupervised Anomaly Thresholding from Reconstruction Errors (2019)
Presentation / Conference Contribution
Ndubuaku, M. U., Anjum, A., & Liotta, A. (2019). Unsupervised Anomaly Thresholding from Reconstruction Errors. In Unsupervised Anomaly Thresholding from Reconstruction Errors (123-129). https://doi.org/10.1007/978-3-030-34914-1_12

Internet of Things (IoT) sensors generate massive streaming data which needs to be processed in real-time for many applications. Anomaly detection is one popular way to process such data and discover nuggets of information. Various machine learning t... Read More about Unsupervised Anomaly Thresholding from Reconstruction Errors.

An AI approach to Collecting and Analyzing Human Interactions with Urban Environments (2019)
Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019). An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.294384

Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, in turn, improve human well-being in urban environments. This is a scientifi... Read More about An AI approach to Collecting and Analyzing Human Interactions with Urban Environments.

Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach (2019)
Journal Article
Di Mauro, M., & Liotta, A. (2019). Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.29437

The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provisioning platforms such as the IP Multimedia Subsystem (IMS). The NFV concept is... Read More about Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach.

RSS Indoor Localization Based on a Single Access Point (2019)
Journal Article
Kokkinis, A., Kanaris, L., Liotta, A., & Stavrou, S. (2019). RSS Indoor Localization Based on a Single Access Point. Sensors, 19(17), Article 3711. https://doi.org/10.3390/s19173711

This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS value... Read More about RSS Indoor Localization Based on a Single Access Point.

An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging (2019)
Journal Article
Wang, Y., Song, W., Fortino, G., Qi, L., Zhang, W., & Liotta, A. (2019). An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging. IEEE Access, 7, 140233-140251. https://doi.org/10.1109/ACCESS.2019.2932130

Underwater images play a key role in ocean exploration, but often suffer from severe quality degradation due to light absorption and scattering in water medium. Although major breakthroughs have been made recently in the general area of image enhance... Read More about An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging.

Intelligence at the Edge of Complex Networks: The Case of Cognitive Transmission Power Control (2019)
Journal Article
Pace, P., Fortino, G., Zhang, Y., & Liotta, A. (2019). Intelligence at the Edge of Complex Networks: The Case of Cognitive Transmission Power Control. IEEE Wireless Communications, 26(3), 97-103. https://doi.org/10.1109/mwc.2019.1800354

The rapid proliferation of new devices has led to the Internet of Things (IoT), a network where virtually any object equipped with a radio interface can be connected. Accordingly, networks are exploding in terms of the number of devices but also in c... Read More about Intelligence at the Edge of Complex Networks: The Case of Cognitive Transmission Power Control.

Runtime evaluation of cognitive systems for non-deterministic multiple output classification problems (2019)
Journal Article
Gopalakrishna, A. K., Ozcelebi, T., Lukkien, J. J., & Liotta, A. (2019). Runtime evaluation of cognitive systems for non-deterministic multiple output classification problems. Future Generation Computer Systems, 100, 1005-1016. https://doi.org/10.1016/j.f

Cognitive applications that involve complex decision making such as smart lighting have non-deterministic input-output relationships, i.e., more than one output may be acceptable for a given input. We refer them as non-deterministic multiple output c... Read More about Runtime evaluation of cognitive systems for non-deterministic multiple output classification problems.

Recent Advances in the Processing and Rendering Algorithms for Computer-Generated Holography (2019)
Journal Article
Corda, R., Giusto, D., Liotta, A., Song, W., & Perra, C. (2019). Recent Advances in the Processing and Rendering Algorithms for Computer-Generated Holography. Electronics, 8(5), https://doi.org/10.3390/electronics8050556

Digital holography represents a novel media which promises to revolutionize the way the users interacts with content. This paper presents an in-depth review of the state-of-the-art algorithms for advanced processing and rendering of computer-generate... Read More about Recent Advances in the Processing and Rendering Algorithms for Computer-Generated Holography.

Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks (2019)
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, a prominent method in artificial intelligence, to design an energy-preserv... Read More about Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks.