CN105740477A - Function searching method for large-scale embedded device firmware and search engine - Google Patents
Function searching method for large-scale embedded device firmware and search engine Download PDFInfo
- Publication number
- CN105740477A CN105740477A CN201610157731.6A CN201610157731A CN105740477A CN 105740477 A CN105740477 A CN 105740477A CN 201610157731 A CN201610157731 A CN 201610157731A CN 105740477 A CN105740477 A CN 105740477A
- Authority
- CN
- China
- Prior art keywords
- firmware
- function
- platform
- function information
- retrieval
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/31—Indexing; Data structures therefor; Storage structures
- G06F16/316—Indexing structures
- G06F16/325—Hash tables
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Stored Programmes (AREA)
Abstract
The invention relates to a function searching method for large-scale embedded device firmware and a search engine.Firstly, the firmware is collected and preprocessed, and a firmware function information database is constructed according to extracted function information; then, functions on the same platform and with same code options are subjected to quick offline clustering through a method based on Minhash, and accordingly the number of samples of the function information database is compressed; then the firmware function information is further processed, accordingly index entries are extracted, and a firmware function index database is constructed.When firmware functions to be tested are subjected to associative retrieval, functions which are in the same platform with the to-be-associated functions and have the same code options with the to-be-associated functions and functions which are not in the same platform with the to-be-associated functions and have the same code options with the to-be-associated functions are retrieved and recognized sequentially in the firmware function index database through the method based on Minhash; then, functions which are in the same platform with the to-be-associated functions and have different code options with the to-be-associated functions are retrieved and recognized, and functions which are in different platforms with the to-be-associated functions and have same code options with the to-be-associated functions are searched for with a retrieval result as aredirector.The method can increase the speed of firmware function association and improve the accuracy of firmware function association.
Description
Technical field
The present invention relates to the search of embedded device firmware and associate analysis field with leak function, be specifically related to a kind of Selecting Function System method for extensive embedded device firmware and Selecting Function System engine.
Background technology
The importance of industrial control system, fragile safe condition and day by day serious attack threaten, and have caused the great attention of countries in the world, and expand in policy, standard, technology, scheme etc. and respond actively.
In history due to the use environment of relative closure, industrial control system is the functional realiey of multiple viewing system when exploitation, and the concern of safety is lacked relatively.Having strict fail-safe software development specifications and safety test flow process unlike tradition IT information system software when exploitation, this necessarily causes industrial control system inevitably to have more safety defect.According to statistics, 2011 to industrial control system leak disclosed in 2013 up to 330, and present the trend of cumulative year after year, and wherein high-risk leak accounting reach 54%.
After " shake net virus " event of Iran's nuclear power station, the unexposed leak of a large amount of excessive risks is betrayed by underground economy or is offered high prices for by some country/tissue, and it is utilized to exploitation 0-day attack or senior sustainability threat (AdvancedPersistentThreat, be called for short APT) attack technology, prepare for possible network antagonism in future.Therefore, the novel attack utilizing 0-day leak is just becoming the new challenge of cyberspace security protection, and today that the industrial control system relating to the industries such as the electric power of national economy, traffic, municipal administration, chemical industry, crucial manufacturing industry merges day by day in industrialization and informationization, greatly will become the important target of attack of future network war possibly.
As the sensor in industrial control system and final executor, they play an important role industrial control equipment (PLC, SCADA, RTU, converter, motion controller, intelligent electric meter, industrial switch etc.) in industrial control system.In NVD only the open leak of PLC device just up to 38, wherein high-risk leak 24.Particular device is mainly carried out man-to-man bug excavation by the bug excavation method currently for industrial control equipment.But due to the modularized design of code and the reason such as shared of increasing income, industrial control equipment leak has strongly connected feature, and the leak of certain function being namely present in certain equipment firmware will also tend to be present in the firmware of other equipment.Lack the relatedness between a kind of function utilized in firmware at present, the equipment firmware leak excavated is diffused into automatically the automatic mode of other equipment.
Summary of the invention
It is desirable to provide a kind of Selecting Function System method for extensive embedded device firmware and Selecting Function System engine, the quick discovery of leak function can be realized based on this search engine.The present invention utilizes the relatedness between the function in firmware, and the equipment firmware leak excavated is diffused into other equipment automatically, in order to provide timely early warning for manufacturer.
The method flow that the present invention relates to specifically includes that the steps such as the collection of embedded device firmware, firmware pretreatment, firmware function index data base structure, firmware function retrieval, result output display.When the innovation point of the present invention is in that to carry out firmware function association analysis, first identifies the function of same platform, different compiling option, and in this, as springboard, removal search, with the function compiling option, different platform, improves the speed of function association, accuracy rate.
For achieving the above object, the present invention adopts the following technical scheme that
A kind of Selecting Function System method for extensive embedded device firmware, comprises the following steps:
1) collect the firmware of embedded device and build firmware library；
2) to step 1) in firmware in firmware library carry out pretreatment and obtain firmware function information, and be stored in firmware function information bank；
3) conventional open source software is collected, for every a source code, binary image file many parts different is generated by different platform, different compiling option compiling, adopt step 2) in method the binary image file obtained is carried out pretreatment, obtain the function information in binary image file, be also stored in firmware function information bank；
4) to platform same in firmware function information bank, quick off-line cluster is carried out with the firmware function compiling option；
5) to step 4) in carry out quick off-line cluster after the firmware function information that obtains be further processed, therefrom extract index entry, build firmware function index data base；
6) firmware of storage in an optional non-firmware library, according to step 2) in method this firmware is carried out pretreatment, obtain the function information in firmware；
7) based on step 6) in certain firmware function information of obtaining, customize corresponding search strategy, then by firmware function index data library searching, identify associated function.
Further, step 1) in, the firmware collecting embedded device regularly crawls each producer information such as disclosed firmware and associated date issued, firmware name, version number etc. on its firmware renewal website mainly by spiders, and it is stored in firmware library.
Further, step 2) in, for the firmware in firmware library, mainly by firmware conversed analysis instrument and binary system disassemblers, and firmware is carried out pretreatment operation by the technology such as plot location, symbol table reduction, function identification that are aided with, obtain the function information in firmware, and be stored in firmware function information bank.
Further, step 3) in, described different platform includes, but are not limited to X86, ARM, MIPS, PowerPC, SPARC, and described different compiling options include-O0 ,-O1 ,-O2 ,-O3 ,-Os.
Further, step 4) in, adopt the method based on min-hash to platform same in firmware function information bank, carry out quick off-line cluster with the function compiling option.
Further, step 5) in, the firmware function information that above-mentioned off-line cluster is obtained processes further, therefrom extracts index entry, firmware function information table it is shown as a kind of mode being easy to retrieval and is stored in index data base, generating the concordance list in order to retrieve firmware function storehouse.
Further, step 6) in, adopt step 2) in method firmware that certain arbitrary non-firmware library is stored carry out pretreatment, obtain the function information relevant to this firmware.
Further, step 7) in, according to step 6) in the function information (including the information such as the platform of function, compiling option) of acquired certain firmware, adopt the method based on min-hash to retrieve in firmware function index data base successively, identify with function to be associated with platform with function with compiling option of compiling option and different platform；Then retrieving again, identify and the function to be associated function with the different compiling option of platform, and retrieve result for springboard with gained, removal search and springboard function different platform are with the function compiling option.
A kind of Selecting Function System engine for extensive embedded device firmware, including:
Firmware collection module: for searching for, collect the firmware of embedded device, and build firmware library；
Firmware pretreatment module: for the firmware in firmware library being carried out file system identification, plot location, symbol table reduction and the pretreatment operation such as platform and compiling option identification, obtain firmware function information；
Firmware function off-line cluster module: adopt the method based on min-hash to same platform, carry out off-line cluster with the firmware function compiling option；
Index functions module: for the firmware function information obtained is processed further, therefrom extracts index entry, builds firmware function index data base；
Function retrieval module: for for firmware function same or similar in concrete firmware function search strategy retrieval, identification firmware function index data base；
User interface: be used for providing a user with the input of visual retrieval and inquisition and retrieval result output interface, according to the retrieval and inquisition strategy that user provides, export corresponding retrieval and inquisition result.
Further, firmware pretreatment module also includes by collecting conventional open source software, for every a source code, different platforms, different compiling options is selected to generate binary image file many parts different, the binary image file obtained is processed, obtains the function information in binary image file.
Further, function retrieval module and user interface are mainly according to the concrete function search strategy of user's customization, output display Top5, Top10 result.
The present invention can obtain following beneficial effect:
The present invention, when the firmware function in firmware function information bank carries out off-line cluster, have employed the method based on min-hash, have compressed the sample size of firmware function information bank, improves the speed of firmware function association.
The present invention is when building firmware function information bank, on the one hand by the firmware collected in firmware library carries out pretreatment acquisition firmware function information；On the other hand, by collecting conventional open source software, for every a source code, by different platform, different compiling option, source code is compiled, obtain binary image file many parts different, adds somewhat to the springboard quantity of firmware function association, improve speed and the recall rate of firmware function association.
The present invention when carrying out actual association retrieval to firmware function, and employing is retrieved in firmware function index data base successively based on the method for min-hash, identified with platform with the same function compiling option of compiling option and different platform；Then retrieving, identify the function of same platform difference compiling option again, and retrieve result for springboard with gained, removal search different platform, with the function compiling option, improves speed and the accuracy rate of firmware function association.
Accompanying drawing explanation
Fig. 1 is the overview flow chart of method proposed by the invention.
The FB(flow block) that Fig. 2 (a) builds for firmware function index data base in method proposed by the invention, Fig. 2 (b) for carrying out the FB(flow block) of function associative search for certain firmware in method proposed by the invention.
Fig. 3 is each function schematic diagram in firmware function information bank.
Fig. 4 is that in Fig. 3, in firmware function information bank, each function is classified and off-line cluster result schematic diagram according to each platform, each compiling option.
Fig. 5 is the principle schematic implementing function association for certain function according to concrete search strategy.
Detailed description of the invention
Below in conjunction with exemplary embodiment and accompanying drawing the present invention made and illustrating.
The overview flow chart of the inventive method is as it is shown in figure 1, mainly comprise the steps that
A) first, collect the firmware of embedded device, automatization's reptile code can be write by the Scrapy reptile framework in Python and regularly crawl each producer information such as disclosed firmware and associated date issued, firmware name, version number etc. on its firmware renewal website, and by Mysql database sharing firmware information storehouse.
B) Binwalk automatization batch decoding is utilized to extract the file system of collected firmware, filtration can the binary file of dis-assembling, by IDAPro binary system static analysis tools to can the binary file analysis of dis-assembling, it is aided with the function information in the technical limit spacing binary files such as plot location, symbol table reduction, function identification again, builds firmware function information bank.
C) conventional open source software is collected (such as Busybox, Openssl), for every a source code, binary image file many parts different is generated in compiling option compilings such as-O0 ,-O1 ,-O2 ,-O3 ,-Os by platforms such as X86, ARM, MIPS, PowerPC, SPARC, adopt the method in step b), and utilize IDAPro binary system static analysis tools that the binary image file obtained is carried out pretreatment, obtain the function information in binary image file, and be stored in firmware function information bank.Fig. 3 is each function schematic diagram in firmware function information bank.
D) adopt the method based on min-hash to platform same in firmware function information bank, carry out quick off-line cluster with the function compiling option.Fig. 4 is that in Fig. 3, in firmware function information bank, each function is classified and off-line cluster result schematic diagram according to each platform, each compiling option.First, with platform and compiling option for criteria for classification, by same platform, with compile option function be placed on same set；Then adopt the method based on min-hash that same platform, the same function compiling option in certain set are carried out Jaccard Similarity Measure and according to being ranked up from big to small, the function of Top10 in result is aggregated in same set.
For set A={a1,a2,…,ai,…,am, i=1,2 ..., m and set B={b1,b2,…,bj,…,bn, j=1,2 ..., n, the element chosen in A ∪ B region drops on the probability Jaccard similarity equal to the two in A ∩ B region.
Namely the Jaccard similarity of set A and set B is:Conventional computing formula is: sim (mhA,mhB) :=| { mhA[i]=mhB[i] } |/n, i=1,2 ..., n.Wherein, mhA[i] represents that set A is hashed function fiIn the new set A' obtained after mapping, each element is by the minima after dictionary sequence；mhB[i] represents that set B is hashed function fiIn the new set B' obtained after mapping, each element is by the minima after dictionary sequence.
Select hash function h that each element in A and set B is done Hash operation, then choose minimum element operation result, compare the whether equal probability of the minimum element operation result of the two and be the similarity of set.
Detailed process: choose one group of hash function, generates one group of Minhash, calculates the Jaccard similarity of two set.
Research shows, when using 800 hash functions, the Jaccard similarity error of two set calculated is less than 3.5%.
E) the firmware function information bank that above-mentioned off-line cluster is obtained processes further, for each of which function record, therefrom extract index entry, firmware function information table is shown as a kind of mode being easy to retrieval and is stored in index data base, generate the concordance list in order to retrieve firmware function storehouse, form firmware function index data base.In idiographic flow such as Fig. 2 that firmware function index data base builds shown in (a) figure.
F) when being associated concrete firmware function retrieving, in Fig. 2 shown in (b) figure, an optional non-firmware library is collected the firmware of storage, can adopt the method in (b) that firmware carries out pretreatment on the one hand and obtain its function information (including the information such as the platform of function, compiling option)；The key message (relevant to search strategy) such as the platform of such as function, compiling option can be provided by the user retrieved on the other hand, then adopt the method based on min-hash to retrieve in firmware function index data base successively for each function, identify with platform with compiling option, different platform with the function compiling option；Then retrieving, identify the function of same platform, different compiling option again, and retrieve result for springboard with gained, removal search different platform is with the function compiling option.
Fig. 5 is the principle schematic implementing function association for certain function according to concrete search strategy, wherein: step 1a) represent by firmware function index data base being retrieved, identifying with platform with the function compiling option；Step 1b) represent by firmware function index data base being retrieved, identified different platform with the function compiling option；Step 2a) with step 2b) represent by firmware function index data library searching, identify with platform different compiling option function；Step 3a) and step 3b) represent respectively with step 2a) and step 2b) associative search result for springboard go retrieval, identify be different from platform with compiling option function.
In sum, the invention discloses a kind of Selecting Function System engine for extensive embedded device firmware.Application described above scene and embodiment, be not intended to limit the present invention, any those skilled in the art, without departing from the spirit and scope of the present invention, can do various change and retouching.Therefore, protection scope of the present invention is defined depending on right.
Claims (10)
1. the Selecting Function System method for extensive embedded device firmware, it is characterised in that comprise the following steps:
1) collect the firmware of embedded device and build firmware library；
2) to step 1) in firmware in firmware library carry out pretreatment and obtain firmware function information, and be stored in firmware function information bank；
3) conventional open source software is collected, for every a source code, binary image file many parts different is generated by different platform, different compiling option compiling, adopt step 2) in method the binary image file obtained is carried out pretreatment, obtain the function information in binary image file, be also stored in firmware function information bank；
4) to platform same in firmware function information bank, quick off-line cluster is carried out with the firmware function compiling option；
5) to step 4) in carry out quick off-line cluster after the firmware function information that obtains be further processed, therefrom extract index entry, build firmware function index data base；
6) firmware of storage in an optional non-firmware library, according to step 2) in method this firmware is carried out pretreatment, obtain the function information in firmware；
7) based on step 6) in certain firmware function information of obtaining, customize corresponding search strategy, then by firmware function index data library searching, identify same or similar function.
2. the method for claim 1, it is characterized in that, step 1) in, utilize spiders regularly to crawl each producer and update disclosed firmware on website at its firmware, and relative date issued, firmware name, version number, and it is stored in firmware library.
3. the method for claim 1, it is characterized in that, step 2) in, utilize firmware conversed analysis instrument and binary system disassemblers, and be aided with plot location, symbol table reduction, platform and compiling option identification technology firmware is carried out described pretreatment operation.
4. the method for claim 1, it is characterised in that step 3) in, described different platform includes X86, ARM, MIPS, PowerPC, SPARC, and described different compiling options include-O0 ,-O1 ,-O2 ,-O3 ,-Os.
5. the method for claim 1, it is characterised in that step 4) in, adopt the method based on min-hash to platform same in firmware function information bank, carry out quick off-line cluster with the function compiling option.
6. method as claimed in claim 5, it is characterised in that step 5) in, firmware function information table it is shown as the mode being easy to retrieval and is stored in index data base, generating the concordance list in order to retrieve firmware function storehouse.
7. the method for claim 1, it is characterized in that, step 7) in, according to step 6) in the function information of acquired certain firmware, including the platform of function, compiling option, employing is retrieved in firmware function index data base successively based on the method for min-hash, is identified with platform with the same function compiling option of compiling option and different platform；Then retrieving, identify the function of same platform difference compiling option again, and retrieve result for springboard with gained, removal search different platform is with the function compiling option.
8. the Selecting Function System engine for extensive embedded device firmware, it is characterised in that including:
Firmware collection module: for searching for, collect the firmware of embedded device, and build firmware library；
Firmware pretreatment module: for the firmware in firmware library is carried out pretreatment operation, obtain firmware function information；And collect conventional open source software, for every a source code, select different platforms, different compiling options to generate binary image file many parts different, the binary image file obtained is processed, obtains the function information in binary image file；
Firmware function off-line cluster module: carry out off-line cluster for the firmware function to same platform, with compiling option；
Index functions module: for the firmware function information obtained is further processed, therefrom extracts index entry, builds firmware function index data base；
Function retrieval module: for for concrete firmware function search strategy, same or analogous firmware function in retrieval, identification firmware function index data base；
User interface: be used for providing a user with the input of visual retrieval and inquisition and retrieval result output interface, according to the retrieval and inquisition strategy that user provides, export corresponding retrieval and inquisition result.
9. Selecting Function System engine as claimed in claim 8, it is characterized in that, described firmware pretreatment module utilizes firmware conversed analysis instrument and binary system disassemblers, and is aided with plot location, symbol table reduction, platform and compiling option identification technology firmware is carried out pretreatment operation；Described firmware function off-line cluster module adopts the method based on min-hash to carry out quick off-line cluster.
10. Selecting Function System engine as described in claim 8, it is characterised in that the function search strategy that described function retrieval module and described user interface customize according to user, output display Top5 or Top10 result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610157731.6A CN105740477B (en) | 2016-03-18 | 2016-03-18 | For the Selecting Function System method and search engine of extensive embedded device firmware |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610157731.6A CN105740477B (en) | 2016-03-18 | 2016-03-18 | For the Selecting Function System method and search engine of extensive embedded device firmware |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105740477A true CN105740477A (en) | 2016-07-06 |
| CN105740477B CN105740477B (en) | 2019-03-29 |
Family
ID=56251724
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610157731.6A Active CN105740477B (en) | 2016-03-18 | 2016-03-18 | For the Selecting Function System method and search engine of extensive embedded device firmware |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105740477B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107861729A (en) * | 2017-11-08 | 2018-03-30 | 中国信息安全测评中心 | A kind of firmware loads localization method, device and the electronic equipment of plot |
| CN109101504A (en) * | 2017-06-20 | 2018-12-28 | 恒为科技（上海）股份有限公司 | A kind of efficient log compression and indexing means |
| CN109740347A (en) * | 2018-11-23 | 2019-05-10 | 中国科学院信息工程研究所 | A kind of identification of the fragile hash function for smart machine firmware and crack method |
| CN111258915A (en) * | 2020-02-27 | 2020-06-09 | 成都乐创自动化技术股份有限公司 | Method for carrying out automatic unit test aiming at PLC program |
| CN111444513A (en) * | 2019-11-14 | 2020-07-24 | 中国电力科学研究院有限公司 | Firmware compiling optimization option identification method and device for power grid embedded terminal |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110413909B (en) * | 2019-06-18 | 2022-06-10 | 中国科学院信息工程研究所 | Machine learning-based intelligent identification method for online firmware of large-scale embedded equipment |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110119765A1 (en) * | 2009-11-18 | 2011-05-19 | Flexilis, Inc. | System and method for identifying and assessing vulnerabilities on a mobile communication device |
| CN103699389A (en) * | 2013-12-30 | 2014-04-02 | 北京大学 | Linux kernel module relation extracting method based on compiling options |
-
2016
- 2016-03-18 CN CN201610157731.6A patent/CN105740477B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110119765A1 (en) * | 2009-11-18 | 2011-05-19 | Flexilis, Inc. | System and method for identifying and assessing vulnerabilities on a mobile communication device |
| CN103699389A (en) * | 2013-12-30 | 2014-04-02 | 北京大学 | Linux kernel module relation extracting method based on compiling options |
Non-Patent Citations (2)
| Title |
|---|
| ANDREI COSTIN等: ""A Large-Scale Analysis of the Security of Embedded Firmwares"", 《PROCEEDINGS OF USENIX SECURITY SYMPOSIUM 》 * |
| 黄飞: ""嵌入式Linux逆向解析技术研究"", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109101504A (en) * | 2017-06-20 | 2018-12-28 | 恒为科技（上海）股份有限公司 | A kind of efficient log compression and indexing means |
| CN109101504B (en) * | 2017-06-20 | 2023-09-19 | 恒为科技（上海）股份有限公司 | Log compression and indexing method |
| CN107861729A (en) * | 2017-11-08 | 2018-03-30 | 中国信息安全测评中心 | A kind of firmware loads localization method, device and the electronic equipment of plot |
| CN109740347A (en) * | 2018-11-23 | 2019-05-10 | 中国科学院信息工程研究所 | A kind of identification of the fragile hash function for smart machine firmware and crack method |
| CN109740347B (en) * | 2018-11-23 | 2020-07-10 | 中国科学院信息工程研究所 | Method for identifying and cracking fragile hash function of intelligent device firmware |
| CN111444513A (en) * | 2019-11-14 | 2020-07-24 | 中国电力科学研究院有限公司 | Firmware compiling optimization option identification method and device for power grid embedded terminal |
| CN111444513B (en) * | 2019-11-14 | 2024-03-12 | 中国电力科学研究院有限公司 | Firmware compiling optimization option identification method and device for power grid embedded terminal |
| CN111258915A (en) * | 2020-02-27 | 2020-06-09 | 成都乐创自动化技术股份有限公司 | Method for carrying out automatic unit test aiming at PLC program |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105740477B (en) | 2019-03-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105740477A (en) | Function searching method for large-scale embedded device firmware and search engine | |
| Nguyen et al. | A study of repetitiveness of code changes in software evolution | |
| CN107391598B (en) | Automatic threat information generation method and system | |
| CN108062484A (en) | A kind of classification stage division based on data sensitive feature and database metadata | |
| CN104331446A (en) | Memory map-based mass data preprocessing method | |
| CN101882163A (en) | Fuzzy Chinese address geographic evaluation method based on matching rule | |
| CN102637172B (en) | Webpage blocking marking method and system | |
| CN111459799A (en) | Software defect detection model establishing and detecting method and system based on Github | |
| CN111143838B (en) | Database user abnormal behavior detection method | |
| CN102073708A (en) | Large-scale uncertain graph database-oriented subgraph query method | |
| CN111125086A (en) | Method, device, storage medium and processor for acquiring data resources | |
| CN109257383A (en) | A kind of BGP method for detecting abnormality and system | |
| JP2024502730A (en) | Medical data element automated classification method and system based on depth map matching | |
| CN115033895B (en) | Binary program supply chain safety detection method and device | |
| CN103279476A (en) | Detection method and system for WEB application system sensitive words | |
| CN112231391A (en) | Big data information analysis system based on cloud computing | |
| CN114398069B (en) | Method and system for identifying accurate version of public component library based on cross fingerprint analysis | |
| CN106874762A (en) | Android malicious code detecting method based on API dependence graphs | |
| CN111984673A (en) | Fuzzy retrieval method and device for tree structure of power grid electric energy metering system | |
| CN105573984B (en) | The recognition methods of socio-economic indicator and device | |
| CN115617689A (en) | Software defect positioning method based on CNN model and domain features | |
| CN102710616B (en) | data stream Prediction method and device | |
| CN113657443B (en) | On-line Internet of things equipment identification method based on SOINN network | |
| CN112612785B (en) | Dynamic monitoring method for key development path of unconventional energy technology | |
| CN102193859A (en) | Code analysis method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |