计算机网络上机实验三
协议分析程序的编写
实验目的
目的：分析IP协议，统计流量。大家可以把流量计做成流量地图，显示不同地点间数据实时发送的量，比如武汉到北京的数据包发送的数据量。 可以用echart画地图，用whois获取IP地址的所属地。
任务：根据IP协议，解析每个数据包的PCI，并对不同IP进行流量统计。
任务的说明：
- 实现的软件能显示每个包的PCI。
- 能显示每个IP地址的流量，即显示接收包的数量。
实验原理
首先解释一下 PCI 的具体含义：
使用分层网络方法，每一层都会“封装”从其上一层向下传递的数据，同时添加自己的信息。然后，该层会将新的 PDU 向下传递到下一层（或者一旦您到达第 1 层，就将其通过物理介质发送）。一旦到达另一端，则采取相反的路径；每一层查看与其相关的标头/尾标，处理它们，并将有效负载向上传递到下一层。 每个封装级别的具体信息取决于协议。例如，TCP 将添加源端口和目标端口、校验和、序列/确认号以及其他一些东西。 IP 添加源/目标地址、数据包长度和其他一些内容。以太网将添加源/目标 MAC、EtherType、FCS 等。
然后就是利用实验二中使用的 npcap 进行抓包。这里主要是抓取 TCP 的数据包，然后将抓取到的每一个数据包解析之后，将它们的源 ip 和目标 ip 都存放到 MySQL 数据库中。然后使用 Python 调用解析 ip 归属地的接口，将每一个 ip 的归属地解析好，然后更新数据库中的相关字段。
之后使用 Spring Boot 搭建一个简单的后台接口，主要是给前端网页提供 json 数据。
前端主要使用 echarts 来绘图，绘图所需要的数据就来自上面 Spring Boot 提供的 json 数据接口。这样就可以实时地绘制我们所需的流量地图了。
实验环境
系统：Windows 10 家庭中文版 21H2
Visual Studio 版本：Visual Studio 2022
Npcap 版本：1.60
Npcap SDK 版本：1.12
MySQL 版本：8.0.28
jdk 版本：openjdk version "17.0.2"
Python 版本：3.10.4
echart 版本：
实验内容
分析IP协议，统计流量。把流量计做成流量地图，显示不同地点间数据实时发送的量，比如武汉到北京的数据包发送的数据量。用echart画地图，用whois获取IP地址的所属地。
实验过程
首先，编写 C++ 程序进行抓包，这个在实验二中已经实现，这里就不再赘述。
这里主要介绍一下将捕获到的源 ip 地址和目标 ip 地址存放到数据库中的过程。
首先，配置环境，步骤如下：
之后，还要将 libmysql.lib 文件添加到项目的根目录下：
然后我们写一个 C++ 的类，从而实现对数据库中数据进行增删改查：
//#include "stdafx.h"
#include "DBMySQL.h"
VspdCToMySQL::VspdCToMySQL()
{
}
VspdCToMySQL::~VspdCToMySQL()
{
}
//初始化数据
int VspdCToMySQL::ConnMySQL(const char* host, const char* port, const char* Db, const char* user, const char* passwd, const char* const charset, const char* Msg)
{
if (mysql_init(&mysql) == NULL)
{
Msg = "inital mysql handle error";
return 1;
}
if (mysql_real_connect(&mysql, host, user, passwd, Db, 0, NULL, 0) == NULL)
{
Msg = "Failed to connect to database: Error";
return 1;
}
if (mysql_set_character_set(&mysql, charset) != 0)
{
Msg = "mysql_set_character_set Error";
return 1;
}
return 0;
}
//查询数据
string VspdCToMySQL::SelectData(const char* SQL, int Cnum, const char* Msg)
{
MYSQL_ROW m_row;
MYSQL_RES* m_res;
char sql[2048];
sprintf(sql, SQL);
int rnum = 0;
char rg = '\n';//行隔开
// char rg='\r';
char cg = '\t';//字段隔开
if (mysql_query(&mysql, sql) != 0)
{
Msg = "select ps_info Error";
return "";
}
m_res = mysql_store_result(&mysql);
if (m_res == NULL)
{
Msg = "select username Error";
return "";
}
string str("");
while (m_row = mysql_fetch_row(m_res))
{
for (int i = 0; i < Cnum; i++)
{
str += m_row[i];
str += cg;
}
str += rg;
rnum++;
}
mysql_free_result(m_res);
return str;
}
//插入数据
int VspdCToMySQL::InsertData(const char* SQL, const char* Msg)
{
char sql[2048];
sprintf(sql, SQL);
if (mysql_query(&mysql, sql) != 0)
{
Msg = "Insert Data Error";
return 1;
}
return 0;
}
//更换数据
int VspdCToMySQL::ReplaceData(const char* SQL, const char* Msg)
{
char sql[2048];
sprintf(sql, SQL);
if (mysql_query(&mysql, sql) != 0)
{
Msg = "Replace Data Error";
return 1;
}
return 0;
}
//更新数据
int VspdCToMySQL::UpdateData(const char* SQL, const char* Msg)
{
char sql[2048];
sprintf(sql, SQL);
if (mysql_query(&mysql, sql) != 0)
{
Msg = "Update Data Error";
return 1;
}
return 0;
}
//删除数据
int VspdCToMySQL::DeleteData(const char* SQL, const char* Msg)
{
char sql[2048];
sprintf(sql, SQL);
if (mysql_query(&mysql, sql) != 0)
{
Msg = "Delete Data error";
return 1;
}
return 0;
}
//调用数据库存储过程
int VspdCToMySQL::CallProcedure(const char* SQL, const char* Msg)
{
char sql[2048];
sprintf(sql, SQL);
if (mysql_query(&mysql, sql) != 0)
{
Msg = "Call Procedure error";
return 1;
}
return 0;
}
//关闭数据库连接
void VspdCToMySQL::CloseMySQLConn()
{
mysql_close(&mysql);
printf("disconnect database\n");
}然后在抓包程序的回调函数中增加对数据库的操作即可：
/* Callback function invoked by libpcap for every incoming packet */
void packet_handler(u_char* param,
const struct pcap_pkthdr* header,
const u_char* pkt_data)
{
struct tm ltime;
char timestr[16];
ip_header* ih;
udp_header* uh;
u_int ip_len;
u_short sport, dport;
time_t local_tv_sec;
/*
* Unused variable
*/
(VOID)(param);
/* convert the timestamp to readable format */
local_tv_sec = header->ts.tv_sec;
localtime_s(<ime, &local_tv_sec);
strftime(timestr, sizeof timestr, "%H:%M:%S", <ime);
/* print timestamp and length of the packet */
printf("%s.%.6d len:%d ", timestr, header->ts.tv_usec, header->len);
/* retireve the position of the ip header */
ih = (ip_header*)(pkt_data +
14); //length of ethernet header
/* retireve the position of the udp header */
ip_len = (ih->ver_ihl & 0xf) * 4;
uh = (udp_header*)((u_char*)ih + ip_len);
/* convert from network byte order to host byte order */
sport = ntohs(uh->sport);
dport = ntohs(uh->dport);
/* print ip addresses and udp ports */
printf("%d.%d.%d.%d.%d -> %d.%d.%d.%d.%d\n",
ih->saddr.byte1,
ih->saddr.byte2,
ih->saddr.byte3,
ih->saddr.byte4,
sport,
ih->daddr.byte1,
ih->daddr.byte2,
ih->daddr.byte3,
ih->daddr.byte4,
dport);
// 将源 ip 地址和目的 ip 地址转换成字符串
string srcIp = to_string(ih->saddr.byte1) + "." + to_string(ih->saddr.byte2) + "." + to_string(ih->saddr.byte3) + "." + to_string(ih->saddr.byte4);
string dstIp = to_string(ih->daddr.byte1) + "." + to_string(ih->daddr.byte2) + "." + to_string(ih->daddr.byte3) + "." + to_string(ih->daddr.byte4);
cout << "src ip " << srcIp << "\t" << endl;
cout << "dst ip " << dstIp << "\t" << endl;
cout << "=========" << endl;
string SQLString = "insert into test_tb(id, src_ip, dst_ip) values(" + to_string(++id) + ", '" + srcIp + "', "
+ "'" + dstIp + "')";
cout << SQLString << endl;
// 插入数据
/*const char* SQL = "insert into test_tb(id, src_ip, dst_ip) values(4, 'qingxiaofeng', 'fsdajfjsad')";
*/
const char* SQL = SQLString.c_str();
const char* Msg = "";
if (vspdctomysql->InsertData(SQL, Msg) == 0)
{
printf("insert success\n");
}
}这里的逻辑是每一次启动这个抓包程序时，会自动清空上一次在数据库中存储的数据，然后再将本次抓取到的数据存放到数据库中。
之后就是 Pyhton 实现对 ip 地址的解析，并将解析好的结果更新到数据库中：
import time
from mysql.connector import MySQLConnection, Error
from python_mysql_dbconfig import read_db_config
import requests
def getJson(ip):
myUrl = 'https://ip.useragentinfo.com/json?ip=' + ip
# myUrl = 'http://whois.pconline.com.cn/ipJson.jsp?ip=' + ip + '&json=true'
# ip = '40.79.150.121'
r = requests.get(myUrl)
return r.json()
def query_with_fetchall():
try:
dbconfig = read_db_config()
conn = MySQLConnection(**dbconfig)
cursor = conn.cursor()
cursor.execute("SELECT * FROM test_tb")
rows = cursor.fetchall()
print('Total Row(s):', cursor.rowcount)
res = []
for row in rows:
if row[3] == None and row[4] == None:
res.append(row)
# print(res)
return res
except Error as e:
print(e)
finally:
cursor.close()
conn.close()
def update_testTb():
cityData = ["北京", "天津", "上海", "重庆", "石家庄", "唐山", "秦皇岛", "邯 郸",
"邢台", "保定", "张家口", "承德", "沧州", "廊坊", "衡水", "太原", "大同",
"阳泉", "长治", "晋城", "朔州", "晋中", "运城", "忻州", "临汾", "吕梁",
"呼和浩特", "包头", "乌海", "赤峰", "通辽", "鄂尔多斯", "呼伦贝尔", "巴彦淖尔",
"乌兰察布", "兴安", "锡林郭勒", "阿拉善", "沈阳", "大连", "鞍山", "抚顺",
"本溪", "丹东", "锦州", "营口", "阜新", "辽阳", "盘锦", "铁岭", "朝阳",
"葫芦岛", "长春", "吉林", "四平", "辽源", "通化", "白山", "松原", "白城",
"延边朝鲜族自治", "哈尔滨", "齐齐哈尔", "鸡西", "鹤岗", "双鸭山", "大庆",
"伊春", "佳木斯", "七台河", "牡丹江", "黑河", "绥化", "大兴安岭地", "南京",
"无锡", "徐州", "常州", "苏州", "南通", "连云港", "淮安", "盐城", "扬州",
"镇江", "泰州", "宿迁", "杭州", "宁波", "温州", "嘉兴", "湖州", "绍兴",
"金华", "衢州", "舟山", "台州", "丽水", "合肥", "芜湖", "蚌埠", "淮南",
"马鞍山", "淮北", "铜陵", "安庆", "黄山", "滁州", "阜阳", "宿州", "巢湖",
"六安", "亳州", "池州", "宣城", "福州", "厦门", "莆田", "三明", "泉州",
"漳州", "南平", "龙岩", "宁德", "南昌", "景德镇", "萍乡", "九江", "新余",
"鹰潭", "赣州", "吉安", "宜春", "抚州", "上饶", "济南", "青岛", "淄博",
"枣庄", "东营", "烟台", "潍坊", "济宁", "泰安", "威海", "日照", "莱芜",
"临沂", "德州", "聊城", "滨州", "郑州", "开封", "洛阳", "平顶山", "安阳",
"鹤壁", "新乡", "焦作", "濮阳", "许昌", "漯河", "三门峡", "南阳", "商丘",
"信阳", "周口", "驻马店", "武汉", "黄石", "十堰", "宜昌", "襄樊", "鄂州",
"荆门", "孝感", "荆州", "黄冈", "咸宁", "随州", "恩施土家族苗族自治", "长沙",
"株洲", "湘潭", "衡阳", "邵阳", "岳阳", "常德", "张家界", "益阳", "郴州",
"永州", "怀化", "娄底", "湘西土家族苗族自治", "广州", "韶关", "深圳", "珠海",
"汕头", "佛山", "江门", "湛江", "茂名", "肇庆", "惠州", "梅州", "汕尾", "河源",
"阳江", "清远", "东莞", "中山", "潮州", "揭阳", "云浮", "南宁", "柳州",
"桂林", "梧州", "北海", "防城港", "钦州", "贵港", "玉林", "百色", "贺州",
"河池", "来宾", "崇左", "海口", "三亚", "成都", "自贡", "攀枝花", "泸州",
"德阳", "绵阳", "广元", "遂宁", "内江", "乐山", "南充", "眉山", "宜宾", "广安",
"达州", "雅安", "巴中", "资阳", "阿坝藏族羌族自治", "甘孜藏族自治", "凉山彝族自治",
"贵阳", "六盘水", "遵义", "安顺", "铜仁地", "黔西南布依族苗族自治", "毕节地",
"黔东南苗族侗族自治", "黔南布依族苗族自治", "昆明", "曲靖", "玉溪", "保山",
"昭通", "丽江", "临沧", "楚雄彝族自治", "红河哈尼族彝族自治", "文山壮族苗族自治",
"西双版纳傣族自治", "大理白族自治", "德宏傣族景颇族自治", "怒江傈僳族自治",
"迪庆藏族自治", "拉萨", "昌都地", "山南地", "日喀则地", "那曲地", "阿里地",
"林芝地", "西安", "铜川", "宝鸡", "咸阳", "渭南", "延安", "汉中", "榆林",
"安康", "商洛", "兰州", "嘉峪关", "金昌", "白银", "天水", "武威", "张掖",
"平凉", "酒泉", "庆阳", "定西", "陇南", "临夏回族自治", "甘南藏族自治", "西宁",
"海东地", "海北藏族自治", "黄南藏族自治", "海南藏族自治", "果洛藏族自治",
"玉树藏族自治", "海西蒙古族藏族自治", "银川", "石嘴山", "吴忠", "固原", "中卫",
"乌鲁木齐", "克拉玛依", "吐鲁番地", "哈密地", "昌吉回族自治", "博尔塔拉蒙古自治",
"巴音郭楞蒙古自治", "阿克苏地", "克孜勒苏柯尔克孜自治", "喀什地", "和田地",
"伊犁哈萨克自治", "塔城地", "阿勒泰地", "仙桃", "潜江", "天门", "神农架林",
"五指山", "琼海", "儋州", "文昌", "万宁", "东方", "定安县", "屯昌县", "澄迈县",
"临高县", "白沙黎族自治县", "昌江黎族自治县", "乐东黎族自治县", "陵水黎族自治县",
"保亭黎族苗族自治县", "琼中黎族苗族自治县", "石河子"]
# read database configuration
db_config = read_db_config()
toBeProcessedData = query_with_fetchall()
# prepare query and data
query = """ UPDATE test_tb
SET src_loc = %s, dst_loc = %s
WHERE id = %s """
try:
conn = MySQLConnection(**db_config)
# update book title
cursor = conn.cursor()
# cursor.execute(query, data)
for row in toBeProcessedData:
rowId = row[0]
srcIp = row[1]
dstIp = row[2]
if srcIp == '10.16.80.216': # 这里要替换成本机的 ip
srcLoc = '武汉'
else:
srcJsonData = getJson(srcIp)
print(srcJsonData)
srcLoc = srcJsonData['city'][0:-1]
time.sleep(1)
if dstIp == '10.16.80.216': # 这里要替换成本机的 ip
dstLoc = '武汉'
else:
dstJsonData = getJson(dstIp)
dstLoc = dstJsonData['city'][0:-1]
time.sleep(1)
if srcLoc != '' and srcLoc not in cityData:
srcLoc = '海外'
if dstLoc != '' and dstLoc not in cityData:
dstLoc = '海外'
print(srcLoc + dstLoc)
print(row)
print('==========分割线=========')
data = (srcLoc, dstLoc, rowId)
cursor.execute(query, data)
conn.commit()
# accept the changes
conn.commit()
except Error as error:
print(error)
finally:
cursor.close()
conn.close()
if __name__ == '__main__':
while True:
update_testTb()
再之后，使用 Spring Boot 创建一个 json 接口，主要的逻辑如下：
/**
* 过滤出同时具有 srcLoc 和 dstLoc 并且都是中国城市的数据
*
* @return
* @throws IOException
* @throws InterruptedException
*/
@GetMapping("/getJson")
public List<TestTb> getJsonData() {
// 先从数据库中取出数据
List<TestTb> testTbList = testTbService.list();
List<TestTb> filtedList = new ArrayList<>();
// 过滤
for (TestTb testTb : testTbList) {
if (testTb.getSrcLoc() != null
&& testTb.getSrcLoc().length() != 0
&& !testTb.getSrcLoc().equals("海外")
&& testTb.getDstLoc() != null
&& testTb.getDstLoc().length() != 0
&& !testTb.getDstLoc().equals("海外")) {
filtedList.add(testTb);
System.out.println(testTb);
}
}
// System.out.println(filtedList);
return filtedList;
}最后，是前端的逻辑：
async function getJsonData(url) {
let obj = await (await fetch(url)).json();
return obj;
}
console.log('test');
url = "http://localhost:8080/testTb/getJson"
getJsonData(url).then((jsonData) => {
// console.log(jsonData);
var geoCoordMap = {
'北京': [116.398, 39.9082],
'天津': [117.252, 39.1039],
'上海': [121.476, 31.2244],
'重庆': [106.548, 29.5549],
'石家庄': [114.476, 38.0483],
'唐山': [118.167, 39.6353],
'秦皇岛': [119.59, 39.9479],
'邯郸': [114.489, 36.5994],
'邢台': [114.504, 37.0717],
'保定': [115.466, 38.8799],
'张家口': [114.89, 40.8262],
'承德': [117.935, 40.9955],
'沧州': [116.866, 38.3124],
'廊坊': [116.706, 39.5193],
'衡水': [115.698, 37.7354],
'太原': [112.531, 37.8551],
'大同': [113.3, 40.0784],
'阳泉': [113.58, 37.8567],
'长治': [113.117, 36.1922],
'晋城': [112.853, 35.4906],
'朔州': [112.429, 39.3186],
'晋中': [112.752, 37.6883],
'运城': [110.998, 35.0315],
'忻州': [112.735, 38.4158],
'临汾': [111.527, 36.1021],
'吕梁': [111.13, 37.5203],
'呼和浩特': [111.667, 40.8083],
'包头': [109.871, 40.6617],
'乌海': [106.814, 39.6692],
'赤峰': [118.957, 42.2673],
'通辽': [122.261, 43.6059],
'鄂尔多斯': [110.003, 39.8223],
'呼伦贝尔': [119.756, 49.2458],
'巴彦淖尔': [107.376, 40.7801],
'乌兰察布': [113.121, 41.0317],
'兴安': [122.135, 46.0872],
'锡林郭勒': [116.099, 43.9455],
'阿拉善': [105.686, 38.8464],
'沈阳': [123.434, 41.8057],
'大连': [121.617, 38.9143],
'鞍山': [123.002, 41.1158],
'抚顺': [123.924, 41.8678],
'本溪': [123.786, 41.2984],
'丹东': [124.398, 40.1325],
'锦州': [121.148, 41.1261],
'营口': [122.25, 40.6716],
'阜新': [121.654, 42.0143],
'辽阳': [123.179, 41.2778],
'盘锦': [122.071, 41.1188],
'铁岭': [123.843, 42.2867],
'朝阳': [120.45, 41.5735],
'葫芦岛': [120.856, 40.7481],
'长春': [125.325, 43.8869],
'吉林': [126.571, 43.8458],
'四平': [124.398, 43.1725],
'辽源': [125.145, 42.9058],
'通化': [125.94, 41.7292],
'白山': [126.424, 41.9401],
'松原': [124.824, 45.1409],
'白城': [122.838, 45.6204],
'延边朝鲜族自治': [129.498, 42.8942],
'哈尔滨': [126.652, 45.7613],
'齐齐哈尔': [123.937, 47.3416],
'鸡西': [130.97, 45.2952],
'鹤岗': [130.279, 47.3311],
'双鸭山': [131.16, 46.6469],
'大庆': [125.094, 46.5883],
'伊春': [128.901, 47.7247],
'佳木斯': [130.37, 46.8075],
'七台河': [131.008, 45.7719],
'牡丹江': [129.623, 44.5848],
'黑河': [127.501, 50.2479],
'绥化': [126.99, 46.637],
'大兴安岭地': [124.397, 51.6737],
'南京': [118.792, 32.0562],
'无锡': [120.359, 31.5611],
'徐州': [117.174, 34.2586],
'常州': [119.975, 31.7698],
'苏州': [120.639, 31.3205],
'南通': [120.871, 32.0093],
'连云港': [119.173, 34.5959],
'淮安': [119.015, 33.612],
'盐城': [120.139, 33.3794],
'扬州': [119.413, 32.4195],
'镇江': [119.442, 32.211],
'泰州': [119.921, 32.4617],
'宿迁': [118.297, 33.9539],
'杭州': [120.173, 30.274],
'宁波': [121.544, 29.8683],
'温州': [120.638, 28.027],
'嘉兴': [120.759, 30.7539],
'湖州': [120.097, 30.8706],
'绍兴': [120.586, 29.9958],
'金华': [119.652, 29.0896],
'衢州': [118.874, 28.9359],
'舟山': [122.106, 30.0132],
'台州': [121.456, 28.6708],
'丽水': [119.917, 28.4522],
'合肥': [117.296, 31.8693],
'芜湖': [118.376, 31.3273],
'蚌埠': [117.402, 32.9302],
'淮南': [117.0, 32.6383],
'马鞍山': [118.502, 31.693],
'淮北': [116.793, 33.969],
'铜陵': [117.811, 30.9446],
'安庆': [117.051, 30.527],
'黄山': [118.317, 29.7099],
'滁州': [118.318, 32.3011],
'阜阳': [115.82, 32.8971],
'宿州': [116.984, 33.6381],
'巢湖': [117.87, 31.6009],
'六安': [116.491, 31.7426],
'亳州': [115.783, 33.8696],
'池州': [117.489, 30.6557],
'宣城': [118.755, 30.9469],
'福州': [119.306, 26.0761],
'厦门': [118.117, 24.4838],
'莆田': [119.005, 25.434],
'三明': [117.64, 26.2681],
'泉州': [118.585, 24.9295],
'漳州': [117.666, 24.5124],
'南平': [118.179, 26.6399],
'龙岩': [117.033, 25.0946],
'宁德': [119.537, 26.6528],
'南昌': [115.897, 28.6788],
'景德镇': [117.193, 29.298],
'萍乡': [113.852, 27.6227],
'九江': [115.99, 29.7156],
'新余': [114.918, 27.8163],
'鹰潭': [117.034, 28.2394],
'赣州': [114.942, 25.8553],
'吉安': [114.987, 27.1136],
'宜春': [114.399, 27.8068],
'抚州': [116.363, 27.9793],
'上饶': [117.969, 28.4456],
'济南': [117.021, 36.6594],
'青岛': [120.357, 36.084],
'淄博': [118.05, 36.8063],
'枣庄': [117.309, 34.8127],
'东营': [118.675, 37.4321],
'烟台': [121.392, 37.5379],
'潍坊': [119.122, 36.7159],
'济宁': [116.588, 35.4133],
'泰安': [117.121, 36.1813],
'威海': [122.122, 37.5043],
'日照': [119.526, 35.4188],
'莱芜': [117.679, 36.2136],
'临沂': [118.346, 35.0538],
'德州': [116.302, 37.4545],
'聊城': [115.986, 36.4561],
'滨州': [118.016, 37.3832],
'郑州': [113.663, 34.7619],
'开封': [114.34, 34.7893],
'洛阳': [112.401, 34.6567],
'平顶山': [113.304, 33.7274],
'安阳': [114.346, 36.1112],
'鹤壁': [114.297, 35.7481],
'新乡': [113.89, 35.3015],
'焦作': [113.228, 35.2338],
'濮阳': [115.029, 35.7632],
'许昌': [113.832, 34.0222],
'漯河': [114.036, 33.5673],
'三门峡': [111.192, 34.7758],
'南阳': [112.534, 32.9993],
'商丘': [115.651, 34.4389],
'信阳': [114.075, 32.124],
'周口': [114.653, 33.6166],
'驻马店': [114.028, 32.9832],
'武汉': [114.281, 30.5781],
'黄石': [115.06, 30.2063],
'十堰': [110.782, 32.6553],
'宜昌': [111.295, 30.7012],
'襄樊': [112.135, 32.062],
'鄂州': [114.904, 30.3898],
'荆门': [112.196, 31.0277],
'孝感': [113.919, 30.9246],
'荆州': [112.245, 30.3252],
'黄冈': [114.875, 30.4465],
'咸宁': [114.336, 29.8337],
'随州': [113.375, 31.7167],
'恩施土家族苗族自治': [109.482, 30.2899],
'长沙': [113.009, 28.2085],
'株洲': [113.149, 27.8406],
'湘潭': [112.907, 27.8612],
'衡阳': [112.612, 26.8962],
'邵阳': [111.467, 27.2371],
'岳阳': [113.108, 29.3663],
'常德': [111.703, 29.0366],
'张家界': [110.477, 29.1197],
'益阳': [112.356, 28.58],
'郴州': [113.032, 25.7968],
'永州': [111.608, 26.438],
'怀化': [109.977, 27.5484],
'娄底': [111.998, 27.7259],
'湘西土家族苗族自治': [109.601, 27.9472],
'广州': [113.322, 23.1341],
'韶关': [113.598, 24.8024],
'深圳': [114.056, 22.5421],
'珠海': [113.547, 22.2532],
'汕头': [116.724, 23.3601],
'佛山': [113.121, 23.0305],
'江门': [113.085, 22.583],
'湛江': [110.421, 21.1989],
'茂名': [110.927, 21.6616],
'肇庆': [112.476, 23.0734],
'惠州': [114.417, 23.0896],
'梅州': [116.118, 24.2988],
'汕尾': [115.368, 22.7782],
'河源': [114.697, 23.7503],
'阳江': [111.984, 21.872],
'清远': [113.045, 23.6882],
'东莞': [113.759, 23.0384],
'中山': [113.372, 22.525],
'潮州': [116.642, 23.6713],
'揭阳': [116.37, 23.5276],
'云浮': [112.044, 22.9294],
'南宁': [108.311, 22.8178],
'柳州': [109.413, 24.3068],
'桂林': [110.285, 25.2827],
'梧州': [111.304, 23.5036],
'北海': [109.123, 21.4788],
'防城港': [108.346, 21.6146],
'钦州': [108.609, 21.9509],
'贵港': [109.606, 23.0939],
'玉林': [110.151, 22.6255],
'百色': [106.621, 23.9018],
'贺州': [111.563, 24.4279],
'河池': [108.062, 24.6972],
'来宾': [109.222, 23.7351],
'崇左': [107.339, 22.4248],
'海口': [110.32, 20.0323],
'三亚': [109.514, 18.2355],
'成都': [104.066, 30.6581],
'自贡': [104.77, 29.3534],
'攀枝花': [101.699, 26.5733],
'泸州': [105.444, 28.8889],
'德阳': [104.388, 31.1368],
'绵阳': [104.726, 31.467],
'广元': [105.834, 32.4384],
'遂宁': [105.583, 30.5137],
'内江': [105.063, 29.5825],
'乐山': [103.746, 29.5866],
'南充': [106.095, 30.7844],
'眉山': [103.826, 30.0389],
'宜宾': [104.621, 28.7705],
'广安': [106.642, 30.4706],
'达州': [107.488, 31.2126],
'雅安': [103.015, 29.9937],
'巴中': [106.755, 31.8574],
'资阳': [104.651, 30.1286],
'阿坝藏族羌族自治': [102.222, 31.8992],
'甘孜藏族自治': [101.866, 30.1414],
'凉山彝族自治': [102.242, 27.9095],
'贵阳': [106.713, 26.5768],
'六盘水': [104.873, 26.5821],
'遵义': [106.931, 27.6926],
'安顺': [105.927, 26.2573],
'铜仁地': [109.188, 27.7184],
'黔西南布依族苗族自治': [104.895, 25.0935],
'毕节地': [105.288, 27.3032],
'黔东南苗族侗族自治': [107.981, 26.5831],
'黔南布依族苗族自治': [107.511, 26.283],
'昆明': [102.703, 25.0499],
'曲靖': [103.784, 25.4913],
'玉溪': [102.536, 24.3472],
'保山': [99.1647, 25.1249],
'昭通': [103.704, 27.3656],
'丽江': [100.277, 26.9229],
'临沧': [100.085, 23.8971],
'楚雄彝族自治': [101.545, 25.0549],
'红河哈尼族彝族自治': [103.18, 23.4301],
'文山壮族苗族自治': [104.255, 23.3803],
'西双版纳傣族自治': [100.799, 22.0109],
'大理白族自治': [100.222, 25.5842],
'德宏傣族景颇族自治': [98.5669, 24.4484],
'怒江傈僳族自治': [98.903, 25.8583],
'迪庆藏族自治': [99.709, 27.859],
'拉萨': [91.1189, 29.6553],
'昌都地': [97.1503, 31.1816],
'山南地': [91.805, 29.2407],
'日喀则地': [88.8884, 29.2717],
'那曲地': [92.0593, 31.4524],
'阿里地': [80.1027, 32.5517],
'林芝地': [94.4083, 29.6352],
'西安': [108.954, 34.2649],
'铜川': [108.948, 34.9005],
'宝鸡': [107.139, 34.3698],
'咸阳': [108.71, 34.3268],
'渭南': [109.51, 34.5073],
'延安': [109.496, 36.5948],
'汉中': [107.031, 33.0799],
'榆林': [109.754, 38.2954],
'安康': [109.031, 32.6917],
'商洛': [109.943, 33.8825],
'兰州': [103.835, 36.0599],
'嘉峪关': [98.2536, 39.8001],
'金昌': [102.175, 38.4764],
'白银': [104.151, 36.5506],
'天水': [105.702, 34.5875],
'武威': [102.634, 37.9317],
'张掖': [100.451, 38.931],
'平凉': [106.725, 35.5097],
'酒泉': [98.5139, 39.7563],
'庆阳': [107.862, 35.9344],
'定西': [104.622, 35.5852],
'陇南': [104.934, 33.4695],
'临夏回族自治': [103.201, 35.5914],
'甘南藏族自治': [102.899, 34.9854],
'西宁': [101.777, 36.6172],
'海东地': [102.086, 36.5092],
'海北藏族自治': [100.973, 36.9433],
'黄南藏族自治': [102.027, 35.5399],
'海南藏族自治': [100.638, 36.3244],
'果洛藏族自治': [100.295, 34.4775],
'玉树藏族自治': [97.013, 33.0183],
'海西蒙古族藏族自治': [97.3632, 37.4214],
'银川': [106.283, 38.4628],
'石嘴山': [106.386, 39.0146],
'吴忠': [106.194, 37.9852],
'固原': [106.281, 36.011],
'中卫': [105.686, 37.4829],
'乌鲁木齐': [87.6168, 43.8235],
'克拉玛依': [84.9312, 45.5964],
'吐鲁番地': [89.2107, 43.007],
'哈密地': [93.5502, 42.8991],
'昌吉回族自治': [87.9882, 44.0044],
'博尔塔拉蒙古自治': [82.0787, 44.9126],
'巴音郭楞蒙古自治': [86.1827, 41.8974],
'阿克苏地': [80.2445, 41.1239],
'克孜勒苏柯尔克孜自治': [76.67, 39.8878],
'喀什地': [75.9994, 39.4657],
'和田地': [79.7641, 37.2296],
'伊犁哈萨克自治': [81.3383, 43.9233],
'塔城地': [83.0148, 46.7523],
'阿勒泰地': [88.069, 47.81],
'仙桃': [113.453, 30.3646],
'潜江': [112.894, 30.4198],
'天门': [113.164, 30.6513],
'神农架林': [110.676, 31.7448],
'五指山': [109.517, 18.7773],
'琼海': [110.46, 19.248],
'儋州': [109.579, 19.5199],
'文昌': [110.748, 19.6159],
'万宁': [110.388, 18.8122],
'东方': [108.693, 19.0807],
'定安县': [110.447, 19.4883],
'屯昌县': [110.097, 19.3686],
'澄迈县': [110.016, 19.7302],
'临高县': [109.689, 19.8973],
'白沙黎族自治县': [109.44, 19.2375],
'昌江黎族自治县': [109.036, 19.3083],
'乐东黎族自治县': [109.175, 18.7435],
'陵水黎族自治县': [110.029, 18.5167],
'保亭黎族苗族自治县': [109.7, 18.6263],
'琼中黎族苗族自治县': [109.832, 19.0467],
'石河子': [86.0526, 44.3051]
};
var WHData = []
for (let i = 0; i < jsonData.length; i++) {
// console.log(jsonData[i]);
tmp = [];
tmp.push({ name: jsonData[i].srcLoc });
tmp.push({ name: jsonData[i].dstLoc, value: 10 });
WHData.push(tmp);
}
var planePath = 'path://M1705.06,1318.313v-89.254l-319.9-221.799l0.073-208.063c0.521-84.662-26.629-121.796-63.961-121.491c-37.332-0.305-64.482,36.829-63.961,121.491l0.073,208.063l-319.9,221.799v89.254l330.343-157.288l12.238,241.308l-134.449,92.931l0.531,42.034l175.125-42.917l175.125,42.917l0.531-42.034l-134.449-92.931l12.238-241.308L1705.06,1318.313z';
planePath = "arrow";
var convertData = function (data) {
var res = [];
for (var i = 0; i < data.length; i++) {
var dataItem = data[i];
var fromCoord = geoCoordMap[dataItem[0].name];
var toCoord = geoCoordMap[dataItem[1].name];
if (fromCoord && toCoord) {
res.push([{
coord: fromCoord
}, {
coord: toCoord
}]);
}
}
return res;
};
var color = ['#a6c84c', '#ffa022', '#46bee9'];
var series = [];
[['Beijing', WHData]].forEach(function (item, i) {
series.push({
name: item[0],
type: 'lines',
zlevel: 1,
effect: {
show: true,
period: 6,
trailLength: 0.7,
color: '#fff',
symbolSize: 3
},
lineStyle: {
normal: {
color: color[i],
width: 0,
curveness: 0.2
}
},
data: convertData(item[1])
},
{
name: item[0],
type: 'lines',
zlevel: 2,
effect: {
show: true,
period: 6,
trailLength: 0,
symbol: planePath,
symbolSize: 8
},
lineStyle: {
normal: {
color: color[i],
width: 1,
opacity: 0.4,
curveness: 0.2
}
},
data: convertData(item[1])
},
{
name: item[0],
type: 'effectScatter',
coordinateSystem: 'geo',
zlevel: 2,
rippleEffect: {
brushType: 'stroke'
},
label: {
normal: {
show: true,
position: 'right',
formatter: '{b}'
}
},
symbolSize: function (val) {
return val[2] / 8;
},
itemStyle: {
normal: {
color: color[i]
}
},
data: item[1].map(function (dataItem) {
return {
name: dataItem[1].name,
value: geoCoordMap[dataItem[1].name].concat([dataItem[1].value])
};
})
});
});
// based ready dom, initialize echarts instance
var chart = echarts.init(document.getElementById('main'));
option = {
backgroundColor: '#404a59',
title: {
text: '流量地图',
subtext: '数据来自 npcap 实时抓取',
left: 'center',
textStyle: {
color: '#fff'
}
},
tooltip: {
trigger: 'item'
},
legend: {
orient: 'vertical',
top: 'bottom',
left: 'right',
data: ['Beijing Top10', 'Shanghai Top10', 'Canton Top10'],
textStyle: {
color: '#fff'
},
selectedMode: 'single'
},
geo: {
map: 'china',
label: {
emphasis: {
show: false
}
},
roam: true,
itemStyle: {
normal: {
areaColor: '#323c48',
borderColor: '#404a59'
},
emphasis: {
areaColor: '#2a333d'
}
}
},
series: series
};
// Use just the specified configurations and data charts.
chart.setOption(option);
});实验其中一次的结果如下：
说明：图中的每一条路径上的箭头数量代表了流量包的数量。
习题与思考题
1、应用WINPCAP能实现哪些网络应用?
- 捕获原始数据包。不管这个包是发往本地机，还是其他机器之间的交换包
- 在数据包被发送到应用程序之前，通过用户定义的规则过滤
- 向网络发送原始数据包
- 对网络通信量做出统计
应用 winpcap 实现的典型应用程序如 WireShark。
项目源码地址
https://github.com/FanyFull/ComputerNetworkExperiment
参考：
1、https://www.reddit.com/r/ccna/comments/7mh86d/what_does_protocol_control_information_means/
计算机网络上机实验三
http://fanyfull.github.io/2022/06/20/计算机网络上机实验三/