appscanjs

a machine learning project to predict app by app's flow

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A month ago, I found @pipcook/boa a project which makes node.js call the machine learning library of Python.So I tried！

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npm install appscanjs and ./node_modules/.bin/bip install dpkt ipaddress scikit-learn

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``javascript
const Appscan = require('appscanjs');

const appscan = new Appscan();

const data = appscan.processor(pcapfilePath, timeThreshold, dataScale, appTimeLog);

appscan.fit(data.xTrain, data.yTrain);
const result = appscan.predict(data.xTest);

const ret = appscan.report(data.yTest, result);
console.log(ret);

`

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- new Appscan(classificationType)

classificationType:

1. 'RandomForestClassifier'
2. 'RidgeClassifier'
3. 'KNeighborsClassifier'

- processor(pcapFliePath, timeThreshold, dataScale, appTimeLog)

- pcapFliePath: Your pcap file's path

- timeThreshold: Default value is 1 (s), you can custom threshold. The smaller the threshold, the more data.

- dataScale: Ratio of training data to test data. Default value is 0.7.

- appTimeLog: Used to mark each flow.it's a object.

Example: [{"label": 1, "closeTime": 1617691826.000627}, {"label": 2, "closeTime": 1617692026.001097}...]

- label: app's label
- closeTime: app's closeTime in pcapfile

and if don't passed-in appTimeLog. processor function only return a features array.

return a object {xTrain:[][],xTest:[][],yTrain:[],yTest:[]}

- fit(X,y)

same as sklearn's fit. To train a classifier.

- predict(X, threshold)

- X: the data to predict
- threshold: use to sklearn'spredict_proba(), if the probability below threshold then prediction's label will set to -1.

return a array as predict result.

- report(yTest, yPred)

same as sklearn's classification_report()`

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Thank you for using and downloading