Refactored advanced entropy operation into entropy operation
This commit is contained in:
mshwed
parent
b99af58636
commit
1b161f997b
41
package-lock.json
generated
41
package-lock.json
generated
@ -5353,8 +5353,7 @@
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"ansi-regex": {
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"version": "2.1.1",
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"dev": true
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"aproba": {
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"version": "1.2.0",
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@ -5375,14 +5374,12 @@
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"balanced-match": {
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"version": "1.0.0",
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"dev": true
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"requires": {
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"balanced-match": "^1.0.0",
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"concat-map": "0.0.1"
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@ -5397,20 +5394,17 @@
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"code-point-at": {
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"version": "1.1.0",
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"dev": true
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"version": "0.0.1",
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"dev": true,
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"dev": true
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"console-control-strings": {
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"version": "1.1.0",
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"dev": true,
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"optional": true
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"dev": true
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},
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"core-util-is": {
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"version": "1.0.2",
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@ -5527,8 +5521,7 @@
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"inherits": {
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"version": "2.0.3",
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"bundled": true,
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"dev": true,
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"optional": true
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"dev": true
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},
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"ini": {
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"version": "1.3.5",
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@ -5540,7 +5533,6 @@
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"version": "1.0.0",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"number-is-nan": "^1.0.0"
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}
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@ -5555,7 +5547,6 @@
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"version": "3.0.4",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"brace-expansion": "^1.1.7"
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}
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@ -5563,14 +5554,12 @@
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"minimist": {
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"version": "0.0.8",
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"bundled": true,
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"dev": true,
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"optional": true
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"dev": true
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},
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"minipass": {
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"version": "2.3.5",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"safe-buffer": "^5.1.2",
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"yallist": "^3.0.0"
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@ -5589,7 +5578,6 @@
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"version": "0.5.1",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"minimist": "0.0.8"
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}
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@ -5670,8 +5658,7 @@
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"number-is-nan": {
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"version": "1.0.1",
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"bundled": true,
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"dev": true,
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"optional": true
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"dev": true
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},
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"object-assign": {
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"version": "4.1.1",
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@ -5683,7 +5670,6 @@
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"version": "1.4.0",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"wrappy": "1"
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}
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@ -5769,8 +5755,7 @@
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"safe-buffer": {
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"version": "5.1.2",
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"bundled": true,
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"dev": true,
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"optional": true
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"dev": true
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},
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"safer-buffer": {
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"version": "2.1.2",
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@ -5806,7 +5791,6 @@
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"version": "1.0.2",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"code-point-at": "^1.0.0",
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"is-fullwidth-code-point": "^1.0.0",
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@ -5826,7 +5810,6 @@
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"version": "3.0.1",
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"bundled": true,
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"dev": true,
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"optional": true,
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"requires": {
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"ansi-regex": "^2.0.0"
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}
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@ -5870,14 +5853,12 @@
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"wrappy": {
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"version": "1.0.2",
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"bundled": true,
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"dev": true,
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"optional": true
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"dev": true
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},
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"yallist": {
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"version": "3.0.3",
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"bundled": true,
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"dev": true,
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"optional": true
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"dev": true
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}
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}
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},
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@ -1,361 +0,0 @@
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/**
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* @author mshwed [m@ttshwed.com]
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* @copyright Crown Copyright 2019
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* @license Apache-2.0
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*/
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import * as d3temp from "d3";
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import * as nodomtemp from "nodom";
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import Operation from "../Operation";
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import Utils from "../Utils";
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const d3 = d3temp.default ? d3temp.default : d3temp;
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const nodom = nodomtemp.default ? nodomtemp.default: nodomtemp;
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/**
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* Advanced Entropy operation
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*/
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class AdvancedEntropy extends Operation {
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/**
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* AdvancedEntropy constructor
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*/
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constructor() {
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super();
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this.name = "Advanced Entropy";
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this.module = "Default";
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this.description = "Shannon Entropy, in the context of information theory, is a measure of the rate at which information is produced by a source of data. It can be used, in a broad sense, to detect whether data is likely to be structured or unstructured. 8 is the maximum, representing highly unstructured, 'random' data. English language text usually falls somewhere between 3.5 and 5. Properly encrypted or compressed data should have an entropy of over 7.5.";
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this.infoURL = "https://wikipedia.org/wiki/Entropy_(information_theory)";
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this.inputType = "byteArray";
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this.outputType = "html";
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this.args = [
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{
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"name": "Visualization",
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"type": "option",
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"value": ["Histogram (Bar)", "Histogram (Line)", "Curve", "Image"]
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}
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];
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}
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/**
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* Calculates the frequency of bytes in the input.
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*
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* @param {byteArray} input
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* @returns {frequency}
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*/
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calculateShannonEntropy(input) {
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const prob = [],
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uniques = input.unique(),
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str = Utils.byteArrayToChars(input);
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let i;
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for (i = 0; i < uniques.length; i++) {
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prob.push(str.count(Utils.chr(uniques[i])) / input.length);
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}
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let entropy = 0,
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p;
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for (i = 0; i < prob.length; i++) {
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p = prob[i];
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entropy += p * Math.log(p) / Math.log(2);
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}
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return -entropy;
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}
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/**
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*
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* @param inputBytes
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* @returns {entropyData}
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*/
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calculateScanningEntropy(inputBytes, binWidth) {
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const entropyData = [];
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if (inputBytes.length < 256) binWidth = 8;
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else binWidth = 256;
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for (let bytePos = 0; bytePos < inputBytes.length; bytePos+=binWidth) {
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const block = inputBytes.slice(bytePos, bytePos+binWidth);
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entropyData.push(this.calculateShannonEntropy(block));
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}
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return { entropyData, binWidth };
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}
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/**
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* Calculates the frequency of bytes in the input.
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*
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* @param {object} svg
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* @param {function} xScale
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* @param {function} yScale
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* @param {integer} svgHeight
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* @param {integer} svgWidth
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* @param {object} margins
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* @param {string} xTitle
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* @param {string} yTitle
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* @returns {undefined}
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*/
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createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, title, xTitle, yTitle) {
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// Axes
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const yAxis = d3.axisLeft()
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.scale(yScale);
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const xAxis = d3.axisBottom()
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.scale(xScale);
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svg.append("g")
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.attr("transform", `translate(0, ${svgHeight - margins.bottom})`)
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.call(xAxis);
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svg.append("g")
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.attr("transform", `translate(${margins.left},0)`)
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.call(yAxis);
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// Axes labels
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svg.append("text")
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.attr("transform", "rotate(-90)")
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.attr("y", 0 - margins.left)
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.attr("x", 0 - (svgHeight / 2))
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.attr("dy", "1em")
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.style("text-anchor", "middle")
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.text(yTitle);
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svg.append("text")
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.attr("transform", `translate(${svgWidth / 2}, ${svgHeight - margins.bottom + 40})`)
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.style("text-anchor", "middle")
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.text(xTitle);
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// Add title
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svg.append("text")
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.attr("transform", `translate(${svgWidth / 2}, ${margins.top - 10})`)
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.style("text-anchor", "middle")
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.text(title);
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}
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/**
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* Calculates the frequency of bytes in the input.
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*
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* @param {byteArray} inputBytes
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* @returns {frequency}
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*/
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calculateByteFrequency(inputBytes) {
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const byteFrequency = [];
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for (let i = 0; i < 256; i++) {
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if (inputBytes.length > 0) {
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let count = 0;
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for (const byte of inputBytes) {
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if (byte === i) count++;
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}
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byteFrequency.push(count / inputBytes.length);
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} else {
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byteFrequency.push(0);
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}
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}
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return byteFrequency;
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}
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/**
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* Calculates the frequency of bytes in the input.
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*
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* @param {byteArray} byteFrequency
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* @returns {frequency}
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*/
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createByteFrequencyLineHistogram(byteFrequency) {
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const margins = { top: 30, right: 20, bottom: 50, left: 30 };
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const svgWidth = 500,
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svgHeight = 500;
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const document = new nodom.Document();
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let svg = document.createElement("svg");
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svg = d3.select(svg)
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.attr("width", "100%")
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.attr("height", "100%")
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.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
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const yScale = d3.scaleLinear()
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.domain([0, d3.max(byteFrequency, d => d)])
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.range([svgHeight - margins.bottom, margins.top]);
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const xScale = d3.scaleLinear()
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.domain([0, byteFrequency.length - 1])
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.range([margins.left, svgWidth - margins.right]);
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const line = d3.line()
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.x((_, i) => xScale(i))
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.y(d => yScale(d))
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.curve(d3.curveMonotoneX);
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svg.append("path")
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.datum(byteFrequency)
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.attr("fill", "none")
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.attr("stroke", "steelblue")
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.attr("d", line);
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this.createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, "", "Byte", "Byte Frequency");
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return svg._groups[0][0].outerHTML;
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}
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/**
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* Creates a byte frequency histogram
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*
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* @param {byteArray} byteFrequency
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* @returns {HTML}
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*/
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createByteFrequencyBarHistogram(byteFrequency) {
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const margins = { top: 30, right: 20, bottom: 50, left: 30 };
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const svgWidth = 500,
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svgHeight = 500,
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binWidth = 1;
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const document = new nodom.Document();
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let svg = document.createElement("svg");
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svg = d3.select(svg)
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.attr("width", "100%")
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.attr("height", "100%")
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.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
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const yExtent = d3.extent(byteFrequency, d => d);
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const yScale = d3.scaleLinear()
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.domain(yExtent)
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.range([svgHeight - margins.bottom, margins.top]);
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const xScale = d3.scaleLinear()
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.domain([0, byteFrequency.length - 1])
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.range([margins.left - binWidth, svgWidth - margins.right]);
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svg.selectAll("rect")
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.data(byteFrequency)
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.enter().append("rect")
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.attr("x", (_, i) => xScale(i) + binWidth)
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.attr("y", dataPoint => yScale(dataPoint))
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.attr("width", binWidth)
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.attr("height", dataPoint => yScale(yExtent[0]) - yScale(dataPoint))
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.attr("fill", "blue");
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this.createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, "", "Byte", "Byte Frequency");
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return svg._groups[0][0].outerHTML;
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}
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/**
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* Creates a byte frequency histogram
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*
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* @param {byteArray} input
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* @param {number} blockSize
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* @returns {HTML}
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*/
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createEntropyCurve(entropyData) {
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const margins = { top: 30, right: 20, bottom: 50, left: 30 };
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const svgWidth = 500,
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svgHeight = 500;
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const document = new nodom.Document();
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let svg = document.createElement("svg");
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svg = d3.select(svg)
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.attr("width", "100%")
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.attr("height", "100%")
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.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
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const yScale = d3.scaleLinear()
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.domain([0, d3.max(entropyData, d => d)])
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.range([svgHeight - margins.bottom, margins.top]);
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const xScale = d3.scaleLinear()
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.domain([0, entropyData.length])
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.range([margins.left, svgWidth - margins.right]);
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const line = d3.line()
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.x((_, i) => xScale(i))
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.y(d => yScale(d))
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.curve(d3.curveMonotoneX);
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if (entropyData.length > 0) {
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svg.append("path")
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.datum(entropyData)
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.attr("d", line);
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svg.selectAll("path").attr("fill", "none").attr("stroke", "steelblue");
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}
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this.createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, "Scanning Entropy", "Block", "Entropy");
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return svg._groups[0][0].outerHTML;
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}
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/**
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* Creates an image representation of the entropy
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*
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* @param {byteArray} input
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* @param {number} blockSize
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* @returns {HTML}
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*/
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createEntropyImage(entropyData) {
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const svgHeight = 100,
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svgWidth = 100,
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cellSize = 1,
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nodes = [];
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for (let i = 0; i < entropyData.length; i++) {
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nodes.push({
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x: i % svgWidth,
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y: Math.floor(i / svgWidth),
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entropy: entropyData[i]
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});
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}
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const document = new nodom.Document();
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let svg = document.createElement("svg");
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svg = d3.select(svg)
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.attr("width", "100%")
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.attr("height", "100%")
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.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
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const greyScale = d3.scaleLinear()
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.domain([0, d3.max(entropyData, d => d)])
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.range(["#000000", "#FFFFFF"])
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.interpolate(d3.interpolateRgb);
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svg
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.selectAll("rect")
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.data(nodes)
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.enter().append("rect")
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.attr("x", d => d.x * cellSize)
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.attr("y", d => d.y * cellSize)
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.attr("width", cellSize)
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.attr("height", cellSize)
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.style("fill", d => greyScale(d.entropy));
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return svg._groups[0][0].outerHTML;
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}
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/**
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* @param {byteArray} input
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* @param {Object[]} args
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* @returns {html}
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*/
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run(input, args) {
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const visualizationType = args[0];
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if (visualizationType === "Histogram (Bar)") {
|
||||
return this.createByteFrequencyBarHistogram(this.calculateByteFrequency(input));
|
||||
} else if (visualizationType === "Histogram (Line)") {
|
||||
return this.createByteFrequencyLineHistogram(this.calculateByteFrequency(input));
|
||||
} else if (visualizationType === "Curve") {
|
||||
return this.createEntropyCurve(this.calculateScanningEntropy(input).entropyData);
|
||||
} else if (visualizationType === "Image") {
|
||||
return this.createEntropyImage(this.calculateScanningEntropy(input).entropyData);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export default AdvancedEntropy;
|
||||
@ -4,9 +4,15 @@
|
||||
* @license Apache-2.0
|
||||
*/
|
||||
|
||||
import * as d3temp from "d3";
|
||||
import * as nodomtemp from "nodom";
|
||||
|
||||
import Operation from "../Operation";
|
||||
import Utils from "../Utils";
|
||||
|
||||
const d3 = d3temp.default ? d3temp.default : d3temp;
|
||||
const nodom = nodomtemp.default ? nodomtemp.default: nodomtemp;
|
||||
|
||||
/**
|
||||
* Entropy operation
|
||||
*/
|
||||
@ -23,22 +29,28 @@ class Entropy extends Operation {
|
||||
this.description = "Shannon Entropy, in the context of information theory, is a measure of the rate at which information is produced by a source of data. It can be used, in a broad sense, to detect whether data is likely to be structured or unstructured. 8 is the maximum, representing highly unstructured, 'random' data. English language text usually falls somewhere between 3.5 and 5. Properly encrypted or compressed data should have an entropy of over 7.5.";
|
||||
this.infoURL = "https://wikipedia.org/wiki/Entropy_(information_theory)";
|
||||
this.inputType = "byteArray";
|
||||
this.outputType = "number";
|
||||
this.presentType = "html";
|
||||
this.args = [];
|
||||
this.outputType = "html";
|
||||
this.args = [
|
||||
{
|
||||
"name": "Visualisation",
|
||||
"type": "option",
|
||||
"value": ["Shannon", "Histogram (Bar)", "Histogram (Line)", "Curve", "Image"]
|
||||
}
|
||||
];
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculates the frequency of bytes in the input.
|
||||
*
|
||||
* @param {byteArray} input
|
||||
* @param {Object[]} args
|
||||
* @returns {number}
|
||||
* @returns {frequency}
|
||||
*/
|
||||
run(input, args) {
|
||||
calculateShannonEntropy(input) {
|
||||
const prob = [],
|
||||
uniques = input.unique(),
|
||||
str = Utils.byteArrayToChars(input);
|
||||
let i;
|
||||
|
||||
let i;
|
||||
for (i = 0; i < uniques.length; i++) {
|
||||
prob.push(str.count(Utils.chr(uniques[i])) / input.length);
|
||||
}
|
||||
@ -54,44 +66,335 @@ class Entropy extends Operation {
|
||||
return -entropy;
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
* @param inputBytes
|
||||
* @returns {entropyData}
|
||||
*/
|
||||
calculateScanningEntropy(inputBytes, binWidth) {
|
||||
const entropyData = [];
|
||||
|
||||
if (inputBytes.length < 256) binWidth = 8;
|
||||
else binWidth = 256;
|
||||
|
||||
for (let bytePos = 0; bytePos < inputBytes.length; bytePos+=binWidth) {
|
||||
const block = inputBytes.slice(bytePos, bytePos+binWidth);
|
||||
entropyData.push(this.calculateShannonEntropy(block));
|
||||
}
|
||||
|
||||
return { entropyData, binWidth };
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculates the frequency of bytes in the input.
|
||||
*
|
||||
* @param {object} svg
|
||||
* @param {function} xScale
|
||||
* @param {function} yScale
|
||||
* @param {integer} svgHeight
|
||||
* @param {integer} svgWidth
|
||||
* @param {object} margins
|
||||
* @param {string} xTitle
|
||||
* @param {string} yTitle
|
||||
* @returns {undefined}
|
||||
*/
|
||||
createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, title, xTitle, yTitle) {
|
||||
// Axes
|
||||
const yAxis = d3.axisLeft()
|
||||
.scale(yScale);
|
||||
|
||||
const xAxis = d3.axisBottom()
|
||||
.scale(xScale);
|
||||
|
||||
svg.append("g")
|
||||
.attr("transform", `translate(0, ${svgHeight - margins.bottom})`)
|
||||
.call(xAxis);
|
||||
|
||||
svg.append("g")
|
||||
.attr("transform", `translate(${margins.left},0)`)
|
||||
.call(yAxis);
|
||||
|
||||
// Axes labels
|
||||
svg.append("text")
|
||||
.attr("transform", "rotate(-90)")
|
||||
.attr("y", 0 - margins.left)
|
||||
.attr("x", 0 - (svgHeight / 2))
|
||||
.attr("dy", "1em")
|
||||
.style("text-anchor", "middle")
|
||||
.text(yTitle);
|
||||
|
||||
svg.append("text")
|
||||
.attr("transform", `translate(${svgWidth / 2}, ${svgHeight - margins.bottom + 40})`)
|
||||
.style("text-anchor", "middle")
|
||||
.text(xTitle);
|
||||
|
||||
// Add title
|
||||
svg.append("text")
|
||||
.attr("transform", `translate(${svgWidth / 2}, ${margins.top - 10})`)
|
||||
.style("text-anchor", "middle")
|
||||
.text(title);
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculates the frequency of bytes in the input.
|
||||
*
|
||||
* @param {byteArray} inputBytes
|
||||
* @returns {frequency}
|
||||
*/
|
||||
calculateByteFrequency(inputBytes) {
|
||||
const byteFrequency = [];
|
||||
for (let i = 0; i < 256; i++) {
|
||||
if (inputBytes.length > 0) {
|
||||
let count = 0;
|
||||
for (const byte of inputBytes) {
|
||||
if (byte === i) count++;
|
||||
}
|
||||
byteFrequency.push(count / inputBytes.length);
|
||||
} else {
|
||||
byteFrequency.push(0);
|
||||
}
|
||||
}
|
||||
|
||||
return byteFrequency;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculates the frequency of bytes in the input.
|
||||
*
|
||||
* @param {byteArray} byteFrequency
|
||||
* @returns {frequency}
|
||||
*/
|
||||
createByteFrequencyLineHistogram(byteFrequency) {
|
||||
const margins = { top: 30, right: 20, bottom: 50, left: 30 };
|
||||
|
||||
const svgWidth = 500,
|
||||
svgHeight = 500;
|
||||
|
||||
const document = new nodom.Document();
|
||||
let svg = document.createElement("svg");
|
||||
|
||||
svg = d3.select(svg)
|
||||
.attr("width", "100%")
|
||||
.attr("height", "100%")
|
||||
.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
|
||||
|
||||
const yScale = d3.scaleLinear()
|
||||
.domain([0, d3.max(byteFrequency, d => d)])
|
||||
.range([svgHeight - margins.bottom, margins.top]);
|
||||
|
||||
const xScale = d3.scaleLinear()
|
||||
.domain([0, byteFrequency.length - 1])
|
||||
.range([margins.left, svgWidth - margins.right]);
|
||||
|
||||
const line = d3.line()
|
||||
.x((_, i) => xScale(i))
|
||||
.y(d => yScale(d))
|
||||
.curve(d3.curveMonotoneX);
|
||||
|
||||
svg.append("path")
|
||||
.datum(byteFrequency)
|
||||
.attr("fill", "none")
|
||||
.attr("stroke", "steelblue")
|
||||
.attr("d", line);
|
||||
|
||||
this.createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, "", "Byte", "Byte Frequency");
|
||||
|
||||
return svg._groups[0][0].outerHTML;
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates a byte frequency histogram
|
||||
*
|
||||
* @param {byteArray} byteFrequency
|
||||
* @returns {HTML}
|
||||
*/
|
||||
createByteFrequencyBarHistogram(byteFrequency) {
|
||||
const margins = { top: 30, right: 20, bottom: 50, left: 30 };
|
||||
|
||||
const svgWidth = 500,
|
||||
svgHeight = 500,
|
||||
binWidth = 1;
|
||||
|
||||
const document = new nodom.Document();
|
||||
let svg = document.createElement("svg");
|
||||
svg = d3.select(svg)
|
||||
.attr("width", "100%")
|
||||
.attr("height", "100%")
|
||||
.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
|
||||
|
||||
const yExtent = d3.extent(byteFrequency, d => d);
|
||||
const yScale = d3.scaleLinear()
|
||||
.domain(yExtent)
|
||||
.range([svgHeight - margins.bottom, margins.top]);
|
||||
|
||||
const xScale = d3.scaleLinear()
|
||||
.domain([0, byteFrequency.length - 1])
|
||||
.range([margins.left - binWidth, svgWidth - margins.right]);
|
||||
|
||||
svg.selectAll("rect")
|
||||
.data(byteFrequency)
|
||||
.enter().append("rect")
|
||||
.attr("x", (_, i) => xScale(i) + binWidth)
|
||||
.attr("y", dataPoint => yScale(dataPoint))
|
||||
.attr("width", binWidth)
|
||||
.attr("height", dataPoint => yScale(yExtent[0]) - yScale(dataPoint))
|
||||
.attr("fill", "blue");
|
||||
|
||||
this.createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, "", "Byte", "Byte Frequency");
|
||||
|
||||
return svg._groups[0][0].outerHTML;
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates a byte frequency histogram
|
||||
*
|
||||
* @param {byteArray} input
|
||||
* @param {number} blockSize
|
||||
* @returns {HTML}
|
||||
*/
|
||||
createEntropyCurve(entropyData) {
|
||||
const margins = { top: 30, right: 20, bottom: 50, left: 30 };
|
||||
|
||||
const svgWidth = 500,
|
||||
svgHeight = 500;
|
||||
|
||||
const document = new nodom.Document();
|
||||
let svg = document.createElement("svg");
|
||||
svg = d3.select(svg)
|
||||
.attr("width", "100%")
|
||||
.attr("height", "100%")
|
||||
.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
|
||||
|
||||
const yScale = d3.scaleLinear()
|
||||
.domain([0, d3.max(entropyData, d => d)])
|
||||
.range([svgHeight - margins.bottom, margins.top]);
|
||||
|
||||
const xScale = d3.scaleLinear()
|
||||
.domain([0, entropyData.length])
|
||||
.range([margins.left, svgWidth - margins.right]);
|
||||
|
||||
const line = d3.line()
|
||||
.x((_, i) => xScale(i))
|
||||
.y(d => yScale(d))
|
||||
.curve(d3.curveMonotoneX);
|
||||
|
||||
if (entropyData.length > 0) {
|
||||
svg.append("path")
|
||||
.datum(entropyData)
|
||||
.attr("d", line);
|
||||
|
||||
svg.selectAll("path").attr("fill", "none").attr("stroke", "steelblue");
|
||||
}
|
||||
|
||||
this.createAxes(svg, xScale, yScale, svgHeight, svgWidth, margins, "Scanning Entropy", "Block", "Entropy");
|
||||
|
||||
return svg._groups[0][0].outerHTML;
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates an image representation of the entropy
|
||||
*
|
||||
* @param {byteArray} input
|
||||
* @param {number} blockSize
|
||||
* @returns {HTML}
|
||||
*/
|
||||
createEntropyImage(entropyData) {
|
||||
const svgHeight = 100,
|
||||
svgWidth = 100,
|
||||
cellSize = 1,
|
||||
nodes = [];
|
||||
|
||||
for (let i = 0; i < entropyData.length; i++) {
|
||||
nodes.push({
|
||||
x: i % svgWidth,
|
||||
y: Math.floor(i / svgWidth),
|
||||
entropy: entropyData[i]
|
||||
});
|
||||
}
|
||||
|
||||
const document = new nodom.Document();
|
||||
let svg = document.createElement("svg");
|
||||
svg = d3.select(svg)
|
||||
.attr("width", "100%")
|
||||
.attr("height", "100%")
|
||||
.attr("viewBox", `0 0 ${svgWidth} ${svgHeight}`);
|
||||
|
||||
const greyScale = d3.scaleLinear()
|
||||
.domain([0, d3.max(entropyData, d => d)])
|
||||
.range(["#000000", "#FFFFFF"])
|
||||
.interpolate(d3.interpolateRgb);
|
||||
|
||||
svg
|
||||
.selectAll("rect")
|
||||
.data(nodes)
|
||||
.enter().append("rect")
|
||||
.attr("x", d => d.x * cellSize)
|
||||
.attr("y", d => d.y * cellSize)
|
||||
.attr("width", cellSize)
|
||||
.attr("height", cellSize)
|
||||
.style("fill", d => greyScale(d.entropy));
|
||||
|
||||
return svg._groups[0][0].outerHTML;
|
||||
}
|
||||
|
||||
/**
|
||||
* Displays the entropy as a scale bar for web apps.
|
||||
*
|
||||
* @param {number} entropy
|
||||
* @returns {html}
|
||||
*/
|
||||
present(entropy) {
|
||||
createShannonEntropyVisualization(entropy) {
|
||||
return `Shannon entropy: ${entropy}
|
||||
<br><canvas id='chart-area'></canvas><br>
|
||||
- 0 represents no randomness (i.e. all the bytes in the data have the same value) whereas 8, the maximum, represents a completely random string.
|
||||
- Standard English text usually falls somewhere between 3.5 and 5.
|
||||
- Properly encrypted or compressed data of a reasonable length should have an entropy of over 7.5.
|
||||
<br><canvas id='chart-area'></canvas><br>
|
||||
- 0 represents no randomness (i.e. all the bytes in the data have the same value) whereas 8, the maximum, represents a completely random string.
|
||||
- Standard English text usually falls somewhere between 3.5 and 5.
|
||||
- Properly encrypted or compressed data of a reasonable length should have an entropy of over 7.5.
|
||||
|
||||
The following results show the entropy of chunks of the input data. Chunks with particularly high entropy could suggest encrypted or compressed sections.
|
||||
The following results show the entropy of chunks of the input data. Chunks with particularly high entropy could suggest encrypted or compressed sections.
|
||||
|
||||
<br><script>
|
||||
var canvas = document.getElementById("chart-area"),
|
||||
parentRect = canvas.parentNode.getBoundingClientRect(),
|
||||
entropy = ${entropy},
|
||||
height = parentRect.height * 0.25;
|
||||
<br><script>
|
||||
var canvas = document.getElementById("chart-area"),
|
||||
parentRect = canvas.parentNode.getBoundingClientRect(),
|
||||
entropy = ${entropy},
|
||||
height = parentRect.height * 0.25;
|
||||
|
||||
canvas.width = parentRect.width * 0.95;
|
||||
canvas.height = height > 150 ? 150 : height;
|
||||
canvas.width = parentRect.width * 0.95;
|
||||
canvas.height = height > 150 ? 150 : height;
|
||||
|
||||
CanvasComponents.drawScaleBar(canvas, entropy, 8, [
|
||||
{
|
||||
label: "English text",
|
||||
min: 3.5,
|
||||
max: 5
|
||||
},{
|
||||
label: "Encrypted/compressed",
|
||||
min: 7.5,
|
||||
max: 8
|
||||
}
|
||||
]);
|
||||
</script>`;
|
||||
CanvasComponents.drawScaleBar(canvas, entropy, 8, [
|
||||
{
|
||||
label: "English text",
|
||||
min: 3.5,
|
||||
max: 5
|
||||
},{
|
||||
label: "Encrypted/compressed",
|
||||
min: 7.5,
|
||||
max: 8
|
||||
}
|
||||
]);
|
||||
</script>`;
|
||||
}
|
||||
|
||||
/**
|
||||
* @param {byteArray} input
|
||||
* @param {Object[]} args
|
||||
* @returns {html}
|
||||
*/
|
||||
run(input, args) {
|
||||
const visualizationType = args[0];
|
||||
|
||||
if (visualizationType === 'Shannon') {
|
||||
return this.createShannonEntropyVisualization(this.calculateShannonEntropy(input));
|
||||
} else if (visualizationType === "Histogram (Bar)") {
|
||||
return this.createByteFrequencyBarHistogram(this.calculateByteFrequency(input));
|
||||
} else if (visualizationType === "Histogram (Line)") {
|
||||
return this.createByteFrequencyLineHistogram(this.calculateByteFrequency(input));
|
||||
} else if (visualizationType === "Curve") {
|
||||
return this.createEntropyCurve(this.calculateScanningEntropy(input).entropyData);
|
||||
} else if (visualizationType === "Image") {
|
||||
return this.createEntropyImage(this.calculateScanningEntropy(input).entropyData);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export default Entropy;
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user