IoT
Power system state estimation (PSSE) plays a vital role in stable operation of modern smart grids, while it is vulnerable to cyber attacks. False data injection attacks (FDIA), one of the most common cyber attacks, can tamper with measurement data and bypass the bad data detection (BDD) mechanism, leading to incorrect PSSE results.
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This dataset contains 22 blocks which are designed based on Scratch programming tool for children. These blocks are flagged by HCI experts and primary schooll teachers as "Usefule" and "Understandable".
The usefulness of the blocks are measured based on a task list provided in a brainstorming session with children of age 8-12.
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This dataset contains usability evaluation raw data of the "Child-Home Interaction: Design and Usability Evaluation of Game-based End-user Development for Children" paper.
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This is the source code and dataset of the paper "Double QoS Guarantee for NOMA-Enabled
Massive MTC Networks".
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The dataset originally was taken from DAIAD, which has the mechanism to monitor the water consumption in real time using a validated platform for different cities. These datasets had the record of different water consumption values taken from the smart water meters that indicates, total water consumption by different users in Litres with the time interval of one hour for a year.
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It is now widely known fact that the Cloud computing and Software defined network paradigms have received a wide acceptance from researchers, academia and the industry. But the wider acceptance of cloud computing and SDN paradigms are hampered by increasing security threats. One of the several facts is that the advancements in processing facilities currently available are implicitly helping the attackers to attack in various directions. For example, it is visible that the conventional DoS attacks are now extended to cloud environments as DDoS attacks.
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With the modern day technological advancements and the evolution of Industry 4.0, it is very important to make sure that the problem of Intrusion detection in Cloud , IoT and other modern networking environments is addressed as an immediate concern. It is a fact that Cloud and Cyber Physical Systems are the basis for Industry 4.0. Thus, intrusion detection in cyber physical systems plays a crucial role in Industry 4.0. Here, we provide the an intrusion detection dataset for performance evaluation of machine learning and deep learning based intrusion detection systems.
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data of fishing operations from beidou, AIS and policy.
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301 Views
Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).
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1840 Views
README.txt for simulation files IEEE_Collaboration_N_entities_2021.mdl and IEEE_2_Platforms_federation_SF_2021.mdl
This is a README.txt for the model published on the paper titled:
Improving IoT Federation Resiliency with Distributed Ledger Technology, 2021, Elo T, et al.
This readme describes how to replicate the main simulation results from the paper using a Vensim
model file. The model file has been generated using the Vensim DSS Macintosh Version
8.0.7 Double Precision x64.
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