LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the -Barriers for Intrusion Detection Using Wireless Sensor Network.

Abhilash Singh, J Amutha, Jaiprakash Nagar, Sandeep Sharma, Cheng-Chi Lee

January 2022 Sensors (Basel)

Synopsis of Social media discussions

The discussions primarily highlight the availability of the datasets and publication acceptance, with posts like 'LT-FS-ID datasets is a synthetically generated data' and 'Paper accepted! Enjoy reading!' demonstrating mild enthusiasm. The tone is neutral to mildly positive, reflecting moderate engagement and interest without delving into the technical or practical impacts in detail.

A
Agreement
 Neither agree nor disagree

There is a neutral stance with some support for the research, but no strong consensus or disagreement is evident.

I
Interest
 Moderate level of interest

Discussions show moderate interest, especially around the datasets and acceptance of the publication, but lack deep engagement with technical details.

E
Engagement
 Moderate level of engagement

Participants mention the acceptance of the paper and datasets, indicating some level of engagement, but there is little critical analysis or in-depth discussion.

I
Impact
 Moderate level of impact

The focus on datasets and acknowledgment of the publication suggests some recognition of its relevance, but limited discussion of broader implications.

Social Mentions

YouTube

2 Videos

Twitter

7 Posts

Metrics

Video Views

1,164

Total Likes

36

Extended Reach

9,721

Social Features

9

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

Machine Learning for Predicting Barriers in Wireless Sensor Networks

Machine Learning for Predicting Barriers in Wireless Sensor Networks

This video discusses a machine learning model, LTFSSVR, that uses sensor data to accurately predict the number of barriers for quick intrusion detection in wireless sensor networks. It highlights the data processing techniques and model performance.

Abhilash Singh

April 25, 2022

680 views

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This lecture covers the fundamentals of ANN, its differences from biological neurons, how it operates, and the mathematics behind it. It also provides a brief introduction to CNNs, suitable for beginners interested in machine learning and remote sensing.

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April 15, 2022

485 views

  • Sensors MDPI
    @Sensors_MDPI (Twitter)

    #highlycitedpaper LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the k-Barriers for Intrusion Detection Using Wireless Sensor Network https://t.co/ovUI5lEnki #WSN #MachineLearning #IntrusionDetection #FeatureLearning https://t.co/WpkO1vsRdw
    view full post

    August 25, 2023

  • Dr. Jaiprakash Nagar
    @jpnagar91 (Twitter)

    RT @MrIfAndOnlyIf: LT-FS-ID datasets is a synthetically generated data available in the public domain (3/3). Data link:https://t.co/5Cgo6MO…
    view full post

    August 12, 2022

    1

  • Abhilash Singh
    @abhilash_iiserb (Twitter)

    LT-FS-ID datasets is a synthetically generated data available in the public domain (3/3). Data link:https://t.co/5Cgo6MOD53 Publication link: https://t.co/HZY2GSmcQf
    view full post

    July 23, 2022

    2

    1

  • scite Reference Check
    @sciterefcheck (Twitter)

    We've detected a paper from Sensors that cites a retracted paper post-retraction. Citing paper: https://t.co/tAom8ad24g Retracted paper: https://t.co/oaVchuDD02
    view full post

    March 5, 2022

  • Priyanjan Datta
    @priyanjan_datta (Twitter)

    RT @MrIfAndOnlyIf: Paper accepted! Enjoy reading! Data: https://t.co/XeLrbvruRX Paper: https://t.co/VSAijtfaPP #ArtificialInteligence #A…
    view full post

    January 30, 2022

    2

  • Amit Kumar
    @amitkum80458614 (Twitter)

    RT @MrIfAndOnlyIf: Paper accepted! Enjoy reading! Data: https://t.co/XeLrbvruRX Paper: https://t.co/VSAijtfaPP #ArtificialInteligence #A…
    view full post

    January 30, 2022

    2

  • Abhilash Singh
    @abhilash_iiserb (Twitter)

    Paper accepted! Enjoy reading! Data: https://t.co/XeLrbvruRX Paper: https://t.co/VSAijtfaPP #ArtificialInteligence #Algorithms #bioinspired #natureinspired #MachineLearning #wsn #metaheuristic #ML #AI #SVR #LT_FS_ID #openaccess #Intrusion #detection #sensors
    view full post

    January 30, 2022

    7

    2

Abstract Synopsis

  • This study developed a machine learning model, LTFSSVR, that use features like sensor range and number of sensors, extracted via simulations, to accurately predict the number of barriers needed for quick intrusion detection in wireless sensor networks.
  • The researchers applied data processing techniques such as log transformation and feature scaling, and evaluated the importance and sensitivity of each feature to ensure the model's effectiveness.
  • The proposed LTFSSVR model outperformed other benchmark algorithms like GPR, GRNN, ANN, and RF, achieving high accuracy with a correlation coefficient of 0.98 and low error metrics, making it a promising tool for intrusion detection.]