ITC Infotech > Resources > Whitepapers > Unsupervised Network Traffic Anomaly Detection Using Parameterized Entropy and LSTM AutoEncoders

Unsupervised Network Traffic Anomaly Detection Using Parameterized Entropy and LSTM AutoEncoders

September 3, 2019

Summary

Detecting anomalous traffic provides one approach to network security threat detection. In this white paper we propose a behavior-based anomaly detection method that detects anomalous traffic by applying a threshold to a reconstruction error given by the LSTM AutoEncoder model on the Bro conn log data collected as time series data.

What is in it for you?

The experimental results in the white paper show that the use of Bro connection logs and extracting only features that significantly contribute to intrusion detection gives promising results.

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Beware of fraudulent and fake job offers

It has come to our attention that certain employment agencies and individuals are asking people for money in exchange for a job at ITC Infotech.

Such Agencies/individuals could impersonate ITC Infotech’s officers, use the company name/logo, brand names and images illegally, without authorization, and/or try to extract money towards security deposit, documentation processing fees, training fees, and so on.

Please note that ITC Infotech never asks job applicants or members of the public to pay money in any form while recruiting.

Feel free to reach out to us at contact.us@itcinfotech.com to report any such incidents that you may have experienced, please use the subject line “Recruitment Fraud Alert” in your message.

Always exercise caution and stay protected against fraud:

  • Do not pay money or transfer funds to anyone toward securing an ITC Infotech job. ITC Infotech will not accept liability for any losses that may have been suffered by the victims of such fraudulent activities.
  • Be careful when sharing your personal information and protect yourself from potential damage. Do not engage with people who fraudulently misrepresent ITC Infotech or its employees/officers and try to solicit payments under the pretext of offering jobs.

View Current Openings

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