- DeepMalwareDetector VS avclass
- DeepMalwareDetector VS deepNOID
- DeepMalwareDetector VS tinysleepnet
- DeepMalwareDetector VS Unredactor
- DeepMalwareDetector VS easyesn
- DeepMalwareDetector VS strelka
- DeepMalwareDetector VS MDML
- DeepMalwareDetector VS MalConv2
- DeepMalwareDetector VS sharpened-cosine-similarity
- DeepMalwareDetector VS SparK
DeepMalwareDetector Alternatives
Similar projects and alternatives to DeepMalwareDetector
-
deepNOID
deepNOID, the binary music genre classifier which determines if what you're listening to really is NOIDED
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
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
-
Unredactor
In this project we are tryinbg to create unredactor. Unredactor will take a redacted document and the redacted flag as input, inreturn it will give the most likely candidates to fill in redacted location. In this project we are only considered about unredacting names only. The data that we are considering is imdb data set with many review files. These files are used to buils corpora for finding tfidf score. Few files are used to train and in these files names are redacted and written into redact
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
SparK
[ICLR'23 Spotlightš„] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling" (by keyu-tian)
DeepMalwareDetector reviews and mentions
-
Looking for insight on labelling portable executable (PE) malware files using a VirusTotal API response report.
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].
Stats
The primary programming language of DeepMalwareDetector is Python.
Popular Comparisons
Sponsored