strelka VS DeepMalwareDetector

Compare strelka vs DeepMalwareDetector and see what are their differences.

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strelka DeepMalwareDetector
1 1
803 65
1.7% -
9.3 0.0
11 days ago about 1 year ago
Python Python
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

strelka

Posts with mentions or reviews of strelka. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-24.

DeepMalwareDetector

Posts with mentions or reviews of DeepMalwareDetector. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-26.
  • Looking for insight on labelling portable executable (PE) malware files using a VirusTotal API response report.
    3 projects | /r/Malware | 26 Aug 2022
    What brought me to this research was these studies [1] [2], which demonstrates how image-based malware classification can be done using a CNN (convolutional neural network). Since I had a bit of a background with malware, and I recently completed a CNN model, I figured I would try to do something similar. It was only after investigating different materials I hit a bit of a roadblock. I found this one dataset, malimg [3], which is made up of PE files that have been converted into images already. I didn't want to just use the images, I wanted to demonstrate how to get them, only the method used to classify them turned out to be a bit out of my depth, kind of like this whole project, it's discussed in Section 4.2 of this paper [4] . There's also this set [5], which contains the pixel content for each file record. And as for the static disassembly you mention, I think you are right, the training data might not exist. During my investigation the best I could find was this study [6].

What are some alternatives?

When comparing strelka and DeepMalwareDetector you can also consider the following projects:

uzen - Website crawler with YARA detection

avclass - AVClass malware labeling tool

halogen - Automatically create YARA rules from malicious documents.

deepNOID - deepNOID, the binary music genre classifier which determines if what you're listening to really is NOIDED

labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.

tinysleepnet - TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively