#码力全开·技术π对#Chrome浏览器实验性API `computePressure`的隐私保护机制如何绕过？

// 典型使用示例（合法方式）
if ('computePressure' in window) {
  const observer = await computePressureObserver.start({
    cpu: { 
      threshold: 0.5,  // 触发通知的阈值
      duration: 1000   // 状态持续时长(ms)
    }
  }, (update) => {
    console.log(update.cpuState); // "nominal"/"fair"/"serious"/"critical"
  });
}

// Chromium源码中的时间模糊化处理（简化）
base::TimeDelta QuantizeTime(base::TimeDelta actual) {
  constexpr base::TimeDelta kResolution = base::Milliseconds(500);
  return (actual / kResolution) * kResolution;
}

// worker-performance-estimator.js
let lastTimestamp = performance.now();
let samples = [];

setInterval(() => {
  const now = performance.now();
  const delta = now - lastTimestamp;
  
  // 模拟CPU密集型任务
  let sum = 0;
  for(let i = 0; i < 1000000; i++) sum += Math.random();
  
  const elapsed = performance.now() - now;
  const utilization = elapsed / delta;
  
  samples.push(utilization);
  if(samples.length > 10) samples.shift();
  
  lastTimestamp = now;
}, 100);

function getEstimate() {
  return samples.reduce((a,b) => a+b, 0) / samples.length;
}

// pressure-detector.cpp
#include <chrono>
#include <emscripten.h>

extern "C" {
  EMSCRIPTEN_KEEPALIVE
  double measureCPULoad(int iterations) {
    auto start = std::chrono::high_resolution_clock::now();
    
    volatile double sum = 0;
    for(int i = 0; i < iterations; i++) {
      sum += sqrt(i);
    }
    
    auto end = std::chrono::high_resolution_clock::now();
    std::chrono::duration<double> elapsed = end - start;
    return elapsed.count() * 1000; // 返回毫秒耗时
  }
}

// wasm-loader.js
const wasmModule = await WebAssembly.instantiateStreaming(
  fetch('pressure-detector.wasm')
);

function estimateLoad() {
  const ITERATIONS = 1000000;
  const start = performance.now();
  const wasmTime = wasmModule.exports.measureCPULoad(ITERATIONS);
  const jsTime = performance.now() - start;
  
  // 计算相对负载
  return Math.min(1, wasmTime / jsTime * 0.8); 
}

// manifest.json
{
  "name": "System Monitor",
  "version": "1.0",
  "permissions": ["system.cpu"],
  "background": {
    "scripts": ["background.js"]
  }
}

// background.js
chrome.system.cpu.getInfo((info) => {
  const totalUsage = info.processors.reduce((sum, proc) => {
    return sum + (proc.usage.kernel + proc.usage.user);
  }, 0);
  
  chrome.runtime.sendMessage({cpuLoad: totalUsage / info.numOfProcessors});
});

# server_analyzer.py
import psutil
from flask import Flask, jsonify

app = Flask(__name__)

@app.route('/system-load')
def system_load():
    return jsonify({
        'cpu': psutil.cpu_percent(interval=1),
        'memory': psutil.virtual_memory().percent
    })

if __name__ == '__main__':
    app.run(port=3000)

class PressureMonitor {
  constructor() {
    this.precisionLevel = 0; // 0-3
    this.callbacks = [];
  }

  requestHigherPrecision(reason) {
    if (this.precisionLevel < 3 && confirm(`允许提高监控精度吗？\n${reason}`)) {
      this.precisionLevel++;
      return true;
    }
    return false;
  }

  getCurrentLoad() {
    switch(this.precisionLevel) {
      case 0: return this.getCoarseLoad();
      case 1: return this.getMediumLoad();
      case 2: return this.getFineLoad();
      case 3: return this.getPreciseLoad();
    }
  }
}

import numpy as np

def add_noise(true_value, epsilon=0.1):
    """添加拉普拉斯噪声实现差分隐私"""
    scale = 1.0 / epsilon
    noise = np.random.laplace(0, scale)
    return np.clip(true_value + noise, 0, 100)

graph LR
A[用户设备] -->|加密传输| B(边缘节点)
B -->|聚合数据| C[中央服务器]
C --> D[可视化仪表盘]