Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Black hole attack detection and tracking method based on doubtful degree accumulation

A black hole attack and suspicion technology, applied in the field of mobile ad hoc network routing security, can solve the problems of no technical means for detection, misjudgment, and no consideration of intense channel conditions for topology changes

Active Publication Date: 2019-05-14
CHONGQING UNIV OF POSTS & TELECOMM
View PDF7 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This algorithm does not take into account the characteristics of intense topology changes and complex channel conditions in ad hoc networks, and the algorithm does not give a specific technical means to achieve detection
[0009] At present, most of the research is only to detect a certain malicious behavior of black hole attack, and lacks comprehensive considerations from various aspects, so more frequent misjudgments will occur

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Black hole attack detection and tracking method based on doubtful degree accumulation
  • Black hole attack detection and tracking method based on doubtful degree accumulation
  • Black hole attack detection and tracking method based on doubtful degree accumulation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0058] In this embodiment, the BADTOAC algorithm is divided into four parts: active detection, passive monitoring, suspicious value recording and abnormal reporting. The present invention uses the global topology record method, each node not only records the shortest path from the current node to the destination node through the sparse tree algorithm when exchanging topology updates, but also maintains a global topology data according to the topology update data surface. A(G) is the adjacency matrix about the current node, and the node m obtains the sparse tree route between m point and each destination node through A(G) and the sparse tree algorithm.

[0059] a. Active detection

[0060] The present invention uses an end-to-end confirmation mechanism to track malicious nodes. The source node sends several test messages to the destination node. When the destination node receives the test messages, the destination node will reply to the source node with a confirmation message....

Embodiment 2

[0090] This embodiment mainly describes the passive monitoring process. The network topology of the embodiment is as follows Figure 5 As shown, the source node A sends data to the destination node D through the routing path A-B-M2-D, the malicious nodes M1 and M2 are in two different stages of the black hole attack, the M1 node is in the initial stage of the black hole attack, and the M2 node is in the obtained Trust stage of source node A.

[0091] In order to reduce the delay and network load as much as possible in the process of data transmission, nodes use UDP transmission services in large quantities, and a small part of data that requires high information accuracy uses TCP transmission services. It is impossible for the source node to calculate its end-to-end packet loss rate during the UDP service process using multi-hop relays, so the BADTOAC algorithm introduces active detection to make up for the lack of passive monitoring. The packet loss rate calculation in passiv...

Embodiment 3

[0115] This embodiment mainly describes the active detection process. The routing path for node A to send data to destination node D is A-B-M2-D, and the reputation registration table of the current node D is stored in node A, such as Figure 4 As shown, the specific steps that node A performs to node D are as follows:

[0116] S1. Node A determines that the remote destination node and the destination node are D;

[0117] S2. Node A sends 20 test messages that require end-to-end confirmation to node D;

[0118] S3. Node A starts a reply confirmation timer after sending each test message, and waits for node D to reply;

[0119] S4. After the countdown of the last reply confirmation timer of node A ends, it is calculated that the packet loss rate on the A-B-M2-D path is greater than 10%. Node A determines that there may be malicious nodes in this path, and suspicious nodes need to be detected. track;

[0120] S5. Node A changes the destination node to the upstream node M2 ​​o...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention belongs to the field of mobile ad hoc network routing security, and discloses a black hole attack detection and tracking method based on doubtful accumulation. According to the method, in a detection period, a passive monitoring mode is adopted, a node detects whether current topology update meets a suspicious condition, and if a data packet of the topology update meets the suspicious condition, the node adds a IV-type suspicious degree to a reputation registration table corresponding to the suspicious node; The node monitors the packet loss rate in each routing path, and triggers active detection if the packet loss rate exceeds the threshold value; an active detection mode is aodpted to detect suspicious behaviors so as to determine a correspondingly increased doubtful value, and performing weighted calculation on credit changes at different moments according to a forgetting factor so as to obtain a final doubtful value; And according to the final doubtful value of the suspicious node, the network control station determines whether the suspicious node is a malicious node through analysis, and once the suspicious node is confirmed to be the malicious node, the networkcontrol station broadcasts the whole network so as to isolate the malicious node from the whole network.

Description

technical field [0001] The invention belongs to the field of mobile ad hoc network (Mobile Ad-hoc Networks, MANET) routing security, and relates to a black hole attack detection and tracking method based on accumulation of suspicion under network attack using table-driven routing equipment. Background technique [0002] With the advancement of science and technology, the volume of wireless communication equipment is getting smaller and smaller, the communication range is gradually increasing, and the communication quality is gradually increasing. The network built by multiple wireless communication equipment is called a wireless ad hoc network. The wireless ad-hoc network is self-organized through several parallel wireless communication devices, and each device is also responsible for relaying the business data of other nodes in the process of sending its own business data. The most classic application of wireless ad hoc network is the tactical mobile ad hoc network composed...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06
Inventor 李云陈其荣彭钦鹏吴广富屈元远刘叶
Owner CHONGQING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products