CN110958163A - Method and device for detecting stolen shooting equipment based on network frame transmission characteristics - Google Patents
Method and device for detecting stolen shooting equipment based on network frame transmission characteristics Download PDFInfo
- Publication number
- CN110958163A CN110958163A CN201911247364.9A CN201911247364A CN110958163A CN 110958163 A CN110958163 A CN 110958163A CN 201911247364 A CN201911247364 A CN 201911247364A CN 110958163 A CN110958163 A CN 110958163A
- Authority
- CN
- China
- Prior art keywords
- fingerprint information
- equipment
- frame fingerprint
- frame
- detected
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/50—Testing arrangements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Studio Devices (AREA)
Abstract
The invention provides a method and a device for detecting a stolen shooting equipment based on network frame transmission characteristics, which relate to the technical field of privacy safety and comprise the following steps: firstly, collecting frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected; then matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value; and finally, determining whether the equipment to be detected corresponding to the frame fingerprint information is the equipment to be shot stolen or not based on at least one fitting value. The invention can effectively discover the stolen shooting equipment transmitted by using the encryption network based on the frame fingerprint information, has automatic detection capability and can greatly reduce the technical threshold of a user.
Description
Technical Field
The invention relates to the technical field of privacy security, in particular to a method and a device for detecting a stolen shooting equipment based on network frame transmission characteristics.
Background
The traditional network detection method can only effectively analyze the network without the password or with the known password, so that the traditional network detection method can find the stolen shooting equipment transmitted by the network without the password or with the known password, but cannot find the stolen shooting equipment transmitted by the network encrypted by the unknown password.
Disclosure of Invention
The invention aims to provide a method and a device for detecting a stolen camera equipment based on network frame transmission characteristics, which can effectively discover the stolen camera equipment transmitted by using an encrypted network.
The invention provides a method for detecting a stolen camera equipment based on network frame transmission characteristics, which comprises the following steps: collecting frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected; matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value; and determining whether the equipment to be detected corresponding to the frame fingerprint information is a pirate equipment or not based on the at least one fitting value.
Further, determining whether the device to be detected corresponding to the frame fingerprint information is a pirate device based on the at least one fitting value includes: and if any fitting value in the at least one fitting value is higher than or equal to a preset fitting value, determining the equipment to be detected corresponding to the frame fingerprint information as a pirate equipment.
Further, after the device to be detected corresponding to the frame fingerprint information is determined as a pirate device, the method further includes: and positioning the equipment to be shot stolen based on the frame fingerprint information to obtain the physical position of the equipment to be shot stolen.
Further, after collecting the frame fingerprint information on the physical link to be detected, the method includes: judging whether the collected frame fingerprint information reaches a preset number; if not, continuing to collect the frame fingerprint information until the collected frame fingerprint information reaches a preset number.
Further, the method comprises: judging whether the physical link to be detected is a multichannel link or not; and if the physical link to be detected is a multi-channel link, switching the channels of the physical link to be detected according to a preset sequence.
The invention provides a detection device of a pirate shooting equipment based on network frame transmission characteristics, which comprises: the acquisition module is used for acquiring frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected; the matching module is used for matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value; and the determining module is used for determining whether the equipment to be detected corresponding to the frame fingerprint information is a pirate equipment or not based on the at least one fitting value.
Further, the determining module includes: and the determining unit is used for determining the equipment to be detected corresponding to the frame fingerprint information as the pirate equipment if any fitting value in the at least one fitting value is higher than or equal to a preset fitting value.
Further, the apparatus further comprises: and the positioning module is used for positioning the equipment to be shot based on the frame fingerprint information to obtain the physical position of the equipment to be shot.
The invention also provides an electronic device, which comprises a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor realizes the detection method of the pirate equipment based on the network frame transmission characteristics when executing the computer program.
The present invention also provides a computer readable medium having non-volatile program code executable by a processor, wherein the program code causes the processor to execute the method for detecting a pirate equipment based on the network frame transmission characteristics.
The invention provides a method and a device for detecting a stolen shooting equipment based on network frame transmission characteristics, which comprises the following steps: firstly, collecting frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected; then matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value; and finally, determining whether the equipment to be detected corresponding to the frame fingerprint information is the equipment to be shot stolen or not based on at least one fitting value. The invention can effectively discover the stolen shooting equipment transmitted by using the encryption network based on the frame fingerprint information, has automatic detection capability and can greatly reduce the technical threshold of a user.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for detecting a stolen camera apparatus based on network frame transmission characteristics according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of the detection apparatus;
fig. 3 is a flowchart of another method for detecting a stolen camera equipment based on network frame transmission characteristics according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a detection apparatus for a pirate equipment based on network frame transmission characteristics according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of another apparatus for detecting a stolen camera device based on network frame transmission characteristics according to an embodiment of the present invention.
Icon:
11-an acquisition module; 12-a matching module; 13-a determination module; 14-a positioning module; 15-a first judgment module; 16-a second judgment module; 17-switching module.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
With the increasing of the shooting behavior of the thieves, the black industry chain market brought by the thieves is continuously expanded. The shooting-stealing equipment is gradually developed towards the direction of universal scheme and mass standard production, taking the most common shooting-stealing equipment, namely a pinhole camera as an example, a manufacturer produces a standardized main board and a standardized lens module, and a purchaser can assemble and disguise the equipment by himself. In this mode, camouflage schemes present a diverse set of features, and unidirectional lens technology exists that rivals traditional optical inspection. The data transmission of the equipment for shooting by theft needs to be carried out by a network.
The traditional network detection method can only effectively analyze the network without the password or with the known password, so that the traditional network detection method can find the stolen shooting equipment transmitted by the network without the password or with the known password, but cannot find the stolen shooting equipment transmitted by the network encrypted by the unknown password. Based on the above, the embodiment of the invention detects the unique network frame with strong identification degree generated by the networked stolen shooting equipment so as to automatically discover the potential stolen shooting equipment.
For the convenience of understanding the embodiment, a detailed description will be given to a method for detecting a stolen camera equipment based on network frame transmission characteristics, which is disclosed in the embodiment of the present invention.
The first embodiment is as follows:
referring to fig. 1, an embodiment of the present invention provides a method for detecting a stolen camera apparatus based on network frame transmission characteristics, which may include the following steps:
step S101, collecting frame fingerprint information on a physical link to be detected.
In embodiments of the present invention, a physical link may refer to a physical transmission medium. Computer networks currently have a variety of physical carriers that can be used as physical transmission media, including but not limited to: twisted pair copper cables (mesh wires), fiber optic media and wireless networks that conform to 802.11 related specifications, such as: and Wi-Fi. The physical links can be divided into a multi-channel link and a non-multi-channel link according to the number of the channels, wherein Wi-Fi belongs to the multi-channel link, and Ethernet belongs to the non-multi-channel link.
Referring to fig. 2, on a hardware level, the detection apparatus provided in the embodiment of the present invention includes one or several network frame sampling modules, one or several processors for executing an analysis algorithm, and an optional output device for outputting a detection result. The network frame sampling module includes but is not limited to: ethernet, 2.4G/5GWIFi wireless network, WiFi6 wireless network, and the like. Processors include, but are not limited to: an MCU (Microcontroller Unit, micro control Unit) and an SoC (System-on-a-Chip).
In order to comprehensively collect the frame fingerprint information on the physical link to be detected, a network frame sampling module is required to perform data sampling on the frame fingerprint information on the physical link to be detected for a period of time. If the physical link to be detected only has one channel, monitoring all the equipment to be detected corresponding to the frame fingerprint information on the channel by using a network frame sampling module; if the physical link to be detected has a plurality of channels, the following two ways can be used for comprehensive monitoring. The first mode is multi-channel capture, namely the number of the network frame sampling modules is determined according to the number of the channels, and one network frame sampling module corresponds to one channel, so that the frame fingerprint information on each channel can be collected, and the detection of the stolen shooting equipment is prevented from being missed. The second mode is time-sharing multiplexing, namely, a network frame sampling module is used for firstly collecting the frame fingerprint information on the first channel, then collecting the frame fingerprint information on the second channel, and circularly collecting so that the frame fingerprint information of all channels can be collected.
The embodiment of the invention refers to the minimum unit of computer network transmission as a network frame. Raw data can be collected by a network frame sampling module, and the raw data includes but is not limited to the following characteristic dimensions: the addresses of the sender and receiver, the rate at which frames are generated, the length of a single frame, the sum of the lengths of all frames over a period of time, and the content of the frame being transmitted. Because the embodiment of the invention does not consider the content contained in the network frame which is tried to be decrypted, the embodiment of the invention can analyze the first four characteristic dimensions.
Since an abstract feature of something can be called a fingerprint, a fingerprint represents an abstract feature. Therefore, the frame fingerprint information in the embodiment of the present invention represents the following four features of a frame generated in a network by a device to be detected during network data transmission: the addresses of the sender and receiver, the rate at which frames are generated, the length of a single frame, and the sum of the lengths of all frames over a period of time. Wherein, each kind of frame fingerprint information corresponds to one equipment to be detected.
And S102, matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value.
In the embodiment of the present invention, each frame fingerprint information in the preset frame fingerprint model is measured by the manufacturer, and will be preset in the device to be detected before factory shipment, and can be updated subsequently through OTA (Over-the-Air Technology). The frame fingerprint information in the preset frame fingerprint model is acquired and analyzed by using a typical image transmission algorithm, the original data transmitted on the network is extracted with unique typical characteristics, and then the relevant information of the equipment to be shot is determined according to the frame fingerprint information of the equipment to be shot by people through manual optimization.
Specifically, in the embodiment of the present invention, statistical analysis is performed on frames sent by one network device to other network devices in multiple dimensions, such as frame sending rate, frame size, time continuity, data dispersion degree, data variation degree, and the like, and an obtained continuity sample is referred to as a frame fingerprint. The embodiment of the invention collects samples of a plurality of different shooting-stealing appliances, and can abstract the preset frame fingerprint model according to a specific fitting algorithm by collecting the frame fingerprints. The model weakens the influence brought by specific dimension numerical values, and the fuzzy proportion is adopted to represent the characteristics of certain video plug flow, so that the finally obtained preset frame fingerprint model has robustness in the aspects of video plug flow definition, code rate setting and the like.
And S103, determining whether the equipment to be detected corresponding to the frame fingerprint information is a pirate equipment or not based on at least one fitting value.
In the embodiment of the invention, the shooting-stealing equipment is essentially high-speed video processing and code stream compression transmission equipment. The device for shooting stolen is different from the intelligent Internet of things device, the device for shooting stolen only pushes a real-time video data stream almost on the network, the data stream carries obvious flow characteristics when being transmitted in the network, and the data stream also carries a certain network image transmission algorithm. The data stream includes, but is not limited to: original image stream, MJPEG image stream, h.264 compressed stream, h.265 compressed stream.
The network frame sampling module collects various frame fingerprint information on a physical link to be detected, then matches each frame fingerprint information through the frame fingerprint information in a preset frame fingerprint model, and determines the frame fingerprint information with the matching degree meeting the requirement as a shooting stealing device.
The embodiment of the invention relates to a method for effectively detecting a pirate shooting device based on frame fingerprint information. The embodiment of the invention can effectively identify the frame fingerprint information under the condition of detecting the network environment with the original frame encryption. The original frame encryption case includes but is not limited to: 802.1X enterprise protection, TLS tunnel encryption and unknown password.
The embodiment of the invention provides a method for detecting a stolen camera equipment based on network frame transmission characteristics, which comprises the following steps: firstly, collecting frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected; then matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value; and finally, determining whether the equipment to be detected corresponding to the frame fingerprint information is the equipment to be shot stolen or not based on at least one fitting value. The embodiment of the invention can effectively discover the stolen shooting equipment transmitted by using the encryption network based on the frame fingerprint information, has automatic detection capability and can greatly reduce the technical threshold of a user.
Further, step S103 includes: and step S1031, if any fitting value in the at least one fitting value is higher than or equal to a preset fitting value, determining the equipment to be detected corresponding to the frame fingerprint information as a pirate equipment.
Further, referring to fig. 3, after step S1031, the method further includes:
and step S104, positioning the stolen shooting equipment based on the frame fingerprint information to obtain the physical position of the stolen shooting equipment.
In the embodiment of the invention, after the processor detects the equipment to be detected based on the frame fingerprint information to obtain the detection result, the detection result is output along with the physical link information of the equipment to be detected and the unique identifier of the equipment to be detected. The physical link information of the device to be detected includes but is not limited to: and (4) specific channels of the physical link where the device to be detected is located. The unique identifier of the device to be detected includes, but is not limited to, a Media Access Control Address (MAC Address). The detection result can be used for data display and can also be used for positioning the physical position of the stolen shooting equipment.
Further, referring to fig. 3, after step S101, the method includes:
step S105, judging whether the collected frame fingerprint information reaches a preset number;
and step S106, if not, continuing to collect the frame fingerprint information until the collected frame fingerprint information reaches a preset number.
In the embodiment of the invention, the preset numbers corresponding to different frames of fingerprint information are different, namely, the sample sizes required by the detection of different stolen shooting equipment are different. For example: the sample size of the detected stolen equipment A is 10, the sample size of the stolen equipment B is 20, and the sample size of the stolen equipment C is 30. If the fingerprint information of 10 frames for detecting the stolen shooting equipment A is collected, the processor can correctly identify the stolen shooting equipment A. If only 3 are collected and the preset number of the shooting-stealing appliances A is not reached, the processor cannot correctly identify the shooting-stealing appliances A.
Further, to implement global data collection, referring to fig. 3, the method further includes:
step S107, judging whether the physical link to be detected is a multichannel link;
and step S108, if the physical link to be detected is a multi-channel link, switching the channels of the physical link to be detected according to a preset sequence.
Illustratively, the multi-channel link includes 12 channels, and the acquisition of the frame fingerprint information is performed on channel number 1 by using a network frame sampling module. Because a single network frame sampling module cannot directly capture frame fingerprint information on channels No. 2-No. 12, if data on 12 channels is required to be obtained, 11 network frame sampling modules need to be added, namely, 12 network frame sampling modules simultaneously carry out data acquisition, and the method is multi-path capture. In order to reduce the work of the processor and realize the global data collection work, the single network frame sampling module can be used for collecting data in a time-division multiplexing mode, for example, the single network frame sampling module is switched to a channel 2 for capturing after capturing on a channel 1 for 10 milliseconds, and then switched to a channel 3 after capturing for 10 milliseconds, and so on, and finally, the global data collection work can be realized macroscopically.
The embodiment of the invention selects different types of network frame sampling modules aiming at different physical links to be detected. For example, for a network-wired physical link to be detected, the network frame sampling module may select a wired network card supporting a promiscuous mode. For the Wi-Fi type physical link to be detected, the network frame sampling module can select a wireless network card supporting a monitoring mode.
The embodiment of the invention only analyzes whether the frame fingerprint information accords with the characteristics of the stolen shooting equipment, but does not decrypt the content contained in the frame, solves the technical problem that the traditional network detection cannot analyze the encrypted network, has certain automatic detection capability and can greatly reduce the threshold of a detection device user. In addition, the embodiment of the invention detects the characteristics of the network frame generated when the networked pirate shooting equipment transmits data, and can effectively reduce the misinformation of the legal Internet of things equipment widely used at present.
In the embodiment of the invention, each characteristic dimension of the frame fingerprint information does not depend on decrypting the network frame, and the algorithm execution process does not need manual intervention, so that automatic detection can be completed in a complex network environment, the labor consumption is greatly reduced, and the robustness of the detection equipment is further improved.
Example two:
referring to fig. 4, a detection apparatus for a pirate camera device based on network frame transmission characteristics according to an embodiment of the present invention may include the following modules:
the acquisition module 11 is configured to acquire frame fingerprint information on a physical link to be detected, where each frame fingerprint information corresponds to one device to be detected;
the matching module 12 is configured to match the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value;
and the determining module 13 is configured to determine whether the device to be detected corresponding to the frame fingerprint information is a pirate device based on the at least one fitting value.
The embodiment of the invention provides a detection device for a pirate shooting equipment based on network frame transmission characteristics, which comprises: firstly, collecting frame fingerprint information on a physical link to be detected by using a collection module, wherein each frame fingerprint information corresponds to one device to be detected; then, matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model by using a matching module to obtain at least one fitting value; and finally, determining whether the equipment to be detected corresponding to the frame fingerprint information is a pirate equipment or not by using a determination module based on at least one fitting value. The embodiment of the invention can effectively discover the stolen shooting equipment transmitted by using the encryption network based on the frame fingerprint information, has automatic detection capability and can greatly reduce the technical threshold of a user.
Further, the determining module 13 includes: and the determining unit is used for determining the equipment to be detected corresponding to the frame fingerprint information as the stolen equipment if any one fitting value in the at least one fitting value is higher than or equal to a preset fitting value.
Further, referring to fig. 5, the apparatus further includes:
and the positioning module 14 is used for positioning the stolen shooting equipment based on the frame fingerprint information to obtain the physical position of the stolen shooting equipment.
Further, referring to fig. 5, the apparatus further includes: a first judging module 15.
The first judging module 15 is configured to judge whether the collected frame fingerprint information reaches a preset number; the collecting module 11 is further configured to, if not, continue to collect the frame fingerprint information until the collected frame fingerprint information reaches a preset number.
Further, referring to fig. 5, the apparatus further includes: a second judging module 16 and a switching module 17.
The second judging module 16 is configured to judge whether the physical link to be detected is a multichannel link;
and a switching module 17, configured to switch the channels of the physical link to be detected according to a preset sequence if the physical link to be detected is a multi-channel link.
In another embodiment of the present invention, an electronic device is further provided, which includes a memory and a processor, where the memory stores a computer program executable on the processor, and the processor implements the steps of the method of the above method embodiment when executing the computer program.
In yet another embodiment of the invention, a computer-readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method of the method embodiment is also provided.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The computer program product of the method for detecting a stolen camera equipment based on network frame transmission characteristics provided by the embodiment of the invention comprises a computer readable storage medium storing program codes, wherein instructions included in the program codes can be used for executing the method described in the foregoing method embodiment, and specific implementation can refer to the method embodiment, which is not described herein again.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the description of the present invention, it should be noted that the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein.
Claims (10)
1. A method for detecting a stolen camera equipment based on network frame transmission characteristics is characterized by comprising the following steps:
collecting frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected;
matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value;
and determining whether the equipment to be detected corresponding to the frame fingerprint information is a pirate equipment or not based on the at least one fitting value.
2. The method for detecting the equipment to be detected based on the network frame transmission characteristics according to claim 1, wherein determining whether the equipment to be detected corresponding to the frame fingerprint information is the equipment to be detected based on the at least one fitting value comprises:
and if any fitting value in the at least one fitting value is higher than or equal to a preset fitting value, determining the equipment to be detected corresponding to the frame fingerprint information as a pirate equipment.
3. The method for detecting the stolen camera equipment based on the network frame transmission characteristics according to claim 2, wherein after the device to be detected corresponding to the frame fingerprint information is determined as the stolen camera equipment, the method further comprises:
and positioning the equipment to be shot stolen based on the frame fingerprint information to obtain the physical position of the equipment to be shot stolen.
4. The method for detecting the stolen camera equipment based on the network frame transmission characteristics according to claim 1, after collecting the frame fingerprint information on the physical link to be detected, comprising the following steps:
judging whether the collected frame fingerprint information reaches a preset number;
if not, continuing to collect the frame fingerprint information until the collected frame fingerprint information reaches a preset number.
5. The method for detecting the pirate equipment based on the network frame transmission characteristics according to claim 1, comprising the following steps:
judging whether the physical link to be detected is a multichannel link or not;
and if the physical link to be detected is a multi-channel link, switching the channels of the physical link to be detected according to a preset sequence.
6. A detection device for a device for stealing shooting based on network frame transmission characteristics is characterized by comprising:
the acquisition module is used for acquiring frame fingerprint information on a physical link to be detected, wherein each frame fingerprint information corresponds to one device to be detected;
the matching module is used for matching the frame fingerprint information with each frame fingerprint information in a preset frame fingerprint model to obtain at least one fitting value;
and the determining module is used for determining whether the equipment to be detected corresponding to the frame fingerprint information is a pirate equipment or not based on the at least one fitting value.
7. The apparatus for detecting the pirate equipment according to the claim 6, wherein the determining module comprises:
and the determining unit is used for determining the equipment to be detected corresponding to the frame fingerprint information as the pirate equipment if any fitting value in the at least one fitting value is higher than or equal to a preset fitting value.
8. The apparatus for detecting the stolen camera equipment based on the network frame transmission characteristics according to claim 7, wherein the apparatus further comprises:
and the positioning module is used for positioning the equipment to be shot based on the frame fingerprint information to obtain the physical position of the equipment to be shot.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any of claims 1 to 5 when executing the computer program.
10. A computer-readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method of any of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911247364.9A CN110958163B (en) | 2019-12-06 | 2019-12-06 | Method and device for detecting stolen shooting equipment based on network frame transmission characteristics, electronic equipment and computer readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911247364.9A CN110958163B (en) | 2019-12-06 | 2019-12-06 | Method and device for detecting stolen shooting equipment based on network frame transmission characteristics, electronic equipment and computer readable medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110958163A true CN110958163A (en) | 2020-04-03 |
| CN110958163B CN110958163B (en) | 2022-01-25 |
Family
ID=69980281
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911247364.9A Active CN110958163B (en) | 2019-12-06 | 2019-12-06 | Method and device for detecting stolen shooting equipment based on network frame transmission characteristics, electronic equipment and computer readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110958163B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114448530A (en) * | 2020-10-20 | 2022-05-06 | 华为技术有限公司 | Method for detecting video monitoring equipment and electronic equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105955058A (en) * | 2016-06-27 | 2016-09-21 | 石飞 | Wireless intelligent household system |
| CN106125680A (en) * | 2016-06-23 | 2016-11-16 | 北京东土科技股份有限公司 | Industrial stokehold data safety processing method based on industry internet and device |
| CN106878104A (en) * | 2017-01-13 | 2017-06-20 | 浙江大学 | A kind of wireless camera head inspecting method based on network traffics |
| CN110493369A (en) * | 2019-08-27 | 2019-11-22 | 王晓阳 | Method, system and the detection device that a kind of pair of concealment electronic equipment is detected |
-
2019
- 2019-12-06 CN CN201911247364.9A patent/CN110958163B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106125680A (en) * | 2016-06-23 | 2016-11-16 | 北京东土科技股份有限公司 | Industrial stokehold data safety processing method based on industry internet and device |
| CN105955058A (en) * | 2016-06-27 | 2016-09-21 | 石飞 | Wireless intelligent household system |
| CN106878104A (en) * | 2017-01-13 | 2017-06-20 | 浙江大学 | A kind of wireless camera head inspecting method based on network traffics |
| CN110493369A (en) * | 2019-08-27 | 2019-11-22 | 王晓阳 | Method, system and the detection device that a kind of pair of concealment electronic equipment is detected |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114448530A (en) * | 2020-10-20 | 2022-05-06 | 华为技术有限公司 | Method for detecting video monitoring equipment and electronic equipment |
| CN114448530B (en) * | 2020-10-20 | 2023-06-20 | 华为技术有限公司 | Method for detecting video monitoring equipment and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110958163B (en) | 2022-01-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20220038484A1 (en) | Method for protecting iot devices from intrusions by performing statistical analysis | |
| CN113676464B (en) | Network security log alarm processing method based on big data analysis technology | |
| CN111147513B (en) | Transverse moving attack path determination method in honey net based on attack behavior analysis | |
| KR102045871B1 (en) | System For Detecting Fire Based on Artificial Intelligence And Method For Detecting Fire Based on Artificial Intelligence | |
| US20190273749A1 (en) | Unauthorized Communication Detection Apparatus and Recording Medium | |
| CN113542195B (en) | Method, system and equipment for detecting malicious encrypted traffic | |
| CN107360118B (en) | Advanced persistent threat attack protection method and device | |
| CN110808994B (en) | Method and device for detecting brute force cracking operation and server | |
| CN111371651A (en) | Industrial communication protocol reverse analysis method | |
| CN110958163B (en) | Method and device for detecting stolen shooting equipment based on network frame transmission characteristics, electronic equipment and computer readable medium | |
| CN102111400A (en) | Trojan horse detection method, device and system | |
| CN111064719A (en) | Method and device for detecting abnormal downloading behavior of file | |
| CN113839925A (en) | IPv6 network intrusion detection method and system based on data mining technology | |
| CN114785567A (en) | Traffic identification method, device, equipment and medium | |
| CN115051874B (en) | Multi-feature CS malicious encrypted traffic detection method and system | |
| WO2023280117A1 (en) | Indication signal recognition method and device, and computer storage medium | |
| CN105827627A (en) | Method and apparatus for acquiring information | |
| CN115190056A (en) | Method, device and equipment for identifying and analyzing programmable traffic protocol | |
| US20190156024A1 (en) | Method and apparatus for automatically classifying malignant code on basis of malignant behavior information | |
| WO2018157336A1 (en) | Data processing device and method | |
| CN110912895B (en) | Network data flow tracing method based on perceptual hash | |
| CN114205855A (en) | Feeder automation service network anomaly detection method facing 5G slices | |
| CN112597499B (en) | Nondestructive security inspection method and system for video monitoring equipment | |
| CN111696227A (en) | Unlocking method and device | |
| CN116668085B (en) | Flow multi-process intrusion detection method and system based on lightGBM |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |