Showing 91 open source projects for "malware-samples"

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  • 1

    PolyRec

    Unistroke gesture recognizer

    ...Please visit https://github.com/cluelab/polyrec PolyRec is a unistroke gesture recognizer suitable for fast prototyping of gesture-based applications. The recognizer uses a nearest neighbor approach, and requires a small number of samples for each class. The similarity between two gestures is calculated through a three steps procedure: -firstly, each gesture is approximated to a polyline, in order to extract its main movements; - then, the two polylines are aligned to obtain an equal number of segments from both of them; - lastly, the distance is found by summing the contribution of each pair of segments. ...
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  • 2

    cyborg

    Cyborg is an cybernetic organism project written with Ada programming

    Cyborg is an cybernetic organism project written with Ada programming language and using PragmARC library ; Developped on GNU/Linux system with 160x64 characters terminal.
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  • 3

    cmdSayIt

    Command Line Text to Speech tool for windows

    This program uses SAPI voices for Text to speech from the commandline. its a simple tool written in C# Samples included for English and Japanese, but you will need a Japanese voice installed on your PC
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  • 4
    Malware Analysis Network in Taiwan <Man in Taiwan, MiT> Welcome to contact us (TonTon@TWMAN.ORG) if you are interested in collaborating with us. This project is open source and distributed under the GNU General Public License version 3. Please feel free to add to or modify this source and propose changes or new converters. Developer & Copyrighted by : TonTon Hsien-De Huang Prompter: Jazz Yao-Tsung Wang, Figaro Chen-Ho Yang | Logo Desinger:Temaki Guo Community on Google+:http://X.TWMAN.ORG/Community/ SourceForge: https://sourceforge.net/projects/twmanplus/files/ FaceBook: https://www.facebook.com/TWMAN.PLUS
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  • 5

    Virtual Botmaster

    Simulate Botnet NetFlow traffic for research analysis

    Simulate Botnet NetFlow traffic for research analysis
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  • 6

    Botnet Detectors Comparer

    Compares botnet detection methods

    Compares botnet detection methods by computing the error metrics by reading the labels on a NetFlow file. The original NetFlow should have a new column for the ground-truth label, and a new column with the prediction label for each botnet detection method. This program computes all the error metrics (TPR, TNR, FPR, FNR, Precision, Accuracy, ErrorRate, FMeasure1, FMeasure2, FMeasure0.5) and output the comparison results. It also ouputs a png plot. The program can compare in a...
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  • 7

    NN Image Recognition (with source-code)

    This is ANN trained application to predict digits from 0 - 9.

    It can predict digits from 0-9 with Artificial Neural Network. I trained ANN with 100 samples of each digit. It takes input of 20x20 pixel image and predicts it with Neural Network. It may predict wrong digit due to very low sample data but it work 90% correctly. Note: JRE 1.6 is required to run this application.
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  • 8
    OpenAIL

    OpenAIL

    Open Artificial Intelligence Library

    [Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field.
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  • 9
    Supernova programming language

    Supernova programming language

    Natural programming language for GUI applications

    Modern scripting language and the first one that presents the concept of programming with direct fiction description using a clear subset of pure human language. Using Supernova you can write the source code using Arabic and/or English keywords and you can create GUI applications for Windows and Linux.
    Downloads: 4 This Week
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  • 10
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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  • 11
    This easy to run and change program for developers, it contains several evolutionary based strategies allowing you try among some function samples
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  • 12
    A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.
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  • 13
    Fuzzy Logic Library for Microsoft .Net (fuzzynet). The library is an easy to use component that implements fuzzy inference system (both, Mamdani and Sugeno methods supported). The library is written in C#. Samples and API documentation are provided. The library was used in http://bettingstudio.com algorithms.
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  • 14
    Bayesian Surprise Matlab toolkit is a basic toolkit for computing Bayesian surprise values given a large set of input samples. It is also useful as way of exploring surprise theory. For more information see also: http://ilab.usc.edu/
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  • 15
    granite-timeseries-ttm-r2

    granite-timeseries-ttm-r2

    Tiny pre-trained IBM model for multivariate time series forecasting

    ...Unlike massive foundation models, TTM models are designed to be lightweight yet powerful, with only ~805K parameters, enabling high performance even on CPU or single-GPU machines. The r2 version is pre-trained on ~700M samples (r2.1 expands to ~1B), delivering up to 15% better accuracy than the r1 version. TTM supports both zero-shot and fine-tuned forecasting, handling minutely, hourly, daily, and weekly resolutions. It can integrate exogenous variables, static categorical features, and perform channel-mixing for richer multivariate forecasting. The get_model() utility makes it easy to auto-select the best TTM model for specific context and prediction lengths. ...
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  • 16
    Hermes 4

    Hermes 4

    Hermes 4 FP8: hybrid reasoning Llama-3.1-405B model by Nous Research

    Hermes 4 405B FP8 is a cutting-edge large language model developed by Nous Research, built on Llama-3.1-405B and optimized for frontier reasoning and alignment. It introduces a hybrid reasoning mode with explicit <think> segments, enabling the model to deliberate deeply when needed and switch to faster responses when desired. Post-training improvements include a vastly expanded corpus with ~60B tokens, boosting performance across math, code, STEM, logic, creativity, and structured outputs....
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