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A new thermal integrity method for pile anomaly detection
(
DEStech Publications Inc.
, 2019 , Conference Paper)
Anomaly detection is a hot topic in pile construction which is a complex one due to the intrinsic nature of underground structures, such as limited accessibility, large depth and complex soil profile. Several traditional ...
Anomaly Detection in Blockchain-enabled Supply Chain: An Ontological Approach
(
Qatar University Press
, 2021 , Poster)
In our proposed work, we propose an anomaly detection framework, for detecting anomalous transactions in business processes from transaction event logs. Such a framework will help enhance the accuracy of anomaly detection ...
Automated detection of anomalies in sewer closed circuit television videos using proportional data modeling
(
International Society for Trenchless Technology
, 2016 , Conference Paper)
Sewer pipeline condition information is usually collected using closed circuit television (CCTV). Moreover, in order to evaluate the condition of pipeline, data should be processed by a certified operator, which is time ...
Denial-of-service attack on iec 61850-based substation automation system: A crucial cyber threat towards smart substation pathways
(
MDPI
, 2021 , Article)
The generation of the mix-based expansion of modern power grids has urged the utilization of digital infrastructures. The introduction of Substation Automation Systems (SAS), advanced networks and communication technologies ...
Application of data-driven attack detection framework for secure operation in smart buildings
(
Elsevier Ltd
, 2021 , Article)
With the rapid advancement in the industrial control technologies and the increased deployment of the industrial Internet of Things (IoT) in the buildings sector, this work presents an analysis of the security of the ...
Dynamical observer for continuous linear Roesser systems
(
Elsevier B.V.
, 2020 , Conference Paper)
Monitoring of industrial systems for anomalies such as faults and cyber-attacks as unknown and extremely undesirable inputs in the presence of other inputs (like disturbances) is an important issue for ensuring the safety ...
Iterative per Group Feature Selection for Intrusion Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Network security is an critical subject in any distributed network. Recently, machine learning has proven their efficiency for intrusion detection. By using a comprehensive dataset with multiple attack types, a well-trained ...
Machine Learning Based Cloud Computing Anomalies Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Machine learning techniques are becoming mainstream in intrusion detection systems as they allow real-time response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a ...
Multi-layer security scheme for implantable medical devices
(
Springer
, 2020 , Article)
Internet of Medical Things (IoMTs) is fast emerging, thereby fostering rapid advances in the areas of sensing, actuation and connectivity to significantly improve the quality and accessibility of health care for everyone. ...