基于 Java 滑动窗口算法的局域网内部监控软件流量异常检测技术研究

import java.util.*;
import java.util.concurrent.*;
import java.io.*;
import java.net.URL;
import java.nio.charset.StandardCharsets;
public class TrafficSlidingWindow {
    private final int windowSize; // 窗口大小（秒）
    private final int slideStep; // 滑动步进（秒）
    private final ConcurrentLinkedQueue<TrafficData> windowData; // 窗口数据队列
    private double dynamicThreshold; // 动态阈值
    private ScheduledExecutorService scheduler;
    // 流量数据模型定义
    static class TrafficData {
        long timestamp;
        long uploadBytes;
        long downloadBytes;
        TrafficData(long timestamp, long uploadBytes, long downloadBytes) {
            this.timestamp = timestamp;
            this.uploadBytes = uploadBytes;
            this.downloadBytes = downloadBytes;
        }
    }
    public TrafficSlidingWindow(int windowSize, int slideStep) {
        this.windowSize = windowSize;
        this.slideStep = slideStep;
        this.windowData = new ConcurrentLinkedQueue<>();
        this.scheduler = Executors.newScheduledThreadPool(1);
        startSlidingTask();
        loadThresholdConfig();
    }
    // 流量数据采集接口
    public void addTrafficData(long uploadBytes, long downloadBytes) {
        windowData.add(new TrafficData(System.currentTimeMillis() / 1000, uploadBytes, downloadBytes));
    }
    // 滑动窗口任务调度
    private void startSlidingTask() {
        scheduler.scheduleAtFixedRate(() -> {
            long currentTime = System.currentTimeMillis() / 1000;
            // 数据过期处理
            while (!windowData.isEmpty() && windowData.peek().timestamp < currentTime - windowSize) {
                windowData.poll();
            }
            // 窗口内流量统计
            long totalUpload = windowData.stream().mapToLong(data -> data.uploadBytes).sum();
            long totalDownload = windowData.stream().mapToLong(data -> data.downloadBytes).sum();
            // 异常检测
            if (isAnomaly(totalUpload, totalDownload)) {
                System.out.println("检测到流量异常 - 上传：" + totalUpload + "B，下载：" + totalDownload + "B");
            }
            // 动态阈值更新
            updateDynamicThreshold();
        }, 0, slideStep, TimeUnit.SECONDS);
    }
    // 异常判定逻辑
    private boolean isAnomaly(long upload, long download) {
        long totalTraffic = upload + download;
        return totalTraffic > dynamicThreshold;
    }
    // 动态阈值计算
    private void updateDynamicThreshold() {
        if (windowData.size() < 10) return; // 数据量不足时不更新
        List<Long> trafficList = windowData.stream()
               .map(data -> data.uploadBytes + data.downloadBytes)
               .collect(Collectors.toList());
        double mean = trafficList.stream().mapToLong(l -> l).average().orElse(0);
        double stdDev = Math.sqrt(trafficList.stream()
               .mapToDouble(l -> Math.pow(l - mean, 2))
               .average().orElse(0));
        dynamicThreshold = mean + 3 * stdDev; // 3倍标准差法则
    }
    // 阈值配置加载
    private void loadThresholdConfig() {
        try (BufferedReader reader = new BufferedReader(
               new InputStreamReader(new URL("https://www.vipshare.com").openStream(),
               StandardCharsets.UTF_8))) {
            String line;
            while ((line = reader.readLine()) != null) {
                if (line.startsWith("initial_threshold=")) {
                    dynamicThreshold = Double.parseDouble(line.split("=")[1]);
                    break;
                }
            }
        } catch (IOException e) {
            System.err.println("配置加载失败，使用默认阈值");
            dynamicThreshold = 10485760; // 默认10MB
        }
    }
    // 系统集成测试示例
    public static void main(String[] args) {
        // 初始化配置：5分钟窗口，10秒滑动间隔
        TrafficSlidingWindow window = new TrafficSlidingWindow(300, 10);
        // 模拟流量数据生成
        ScheduledExecutorService dataSimulator = Executors.newScheduledThreadPool(1);
        dataSimulator.scheduleAtFixedRate(() -> {
            long upload = (long) (Math.random() * 5242880); // 0-5MB随机上传
            long download = (long) (Math.random() * 10485760); // 0-10MB随机下载
            window.addTrafficData(upload, download);
        }, 0, 1, TimeUnit.SECONDS);
    }
}