The embodiment of the invention provides a method and a device for mixing character strings in a source code. The method and the device are applied to a software development tool. The method specifically comprises the steps of compiling a to-be-mixed source code by use of a Clang tool to obtain a syntax tree; traversing the syntax tree to obtain a character string constant list and a character string reference list of the character string in the source code; reading a character string constant according to a position indicated in the character string constant list and encrypting the characterstring constant, and replacing an original character string constant with the encrypted character string; finding the encrypted character string according to the character string reference list, and inserting a decryption code at a position in the source code where the encrypted character string is located. Through replacement, all character string constants in the source code are converted into the encrypted character strings and are no longer plaintext information which may cause secret leakage, thereby avoiding the corresponding safety risk.

Method and device for mixing character string in source code

The invention provides a data processing method based on big data, and the Internet of Things and a cloud computing server center. The method comprises steps that firstly, directory information corresponding to plaintext codes in a control script is acquired according to the log updating information and communication configuration parameters of Internet of Things equipment; secondly, extracting the text information in a control script through the static directory information in the directory information to generate the state description information, and converting the state description information into the first result information; comparing each group of first equipment attribute parameters in the first result information with each group of second equipment attribute parameters in the second result information one by one; therefore, determining different types of system vulnerabilities appearing when the Internet of Things equipment runs based on the control script, and finally, actively reparing the different types of system vulnerabilities by adopting a corresponding repair mode. The method is advantaged in that software vulnerability of the Internet of Things equipment can be automatically detected and actively repaired, so operation safety and reliability of the Internet of Things equipment are ensured.

Data processing method based on big data, and Internet of Things and cloud computing server center

The invention provides a project version detection method and system based on text information association relation analysis, and the method comprises the steps: unpacking a large-scale IOT firmware file, so as to find a to-be-detected project and corresponding feature information contained in the firmware file; comparing the feature information of the to-be-tested project with information in an open source project graph database, and deducing a version number of the to-be-tested project; and when the obtained version number of the to-be-tested project is not unique, calculating the version matching degree of the to-be-tested project, and outputting the version of the to-be-tested project and the corresponding matching degree. According to the method, the problem that the software projectversion information is difficult to obtain from the Internet of Things equipment is solved, the efficiency and accuracy of vulnerability mining personnel in researching the vulnerability of the Internet of Things equipment can be improved, and the level of security analysis on the Internet of Things equipment is further improved.

Project version detection method and system based on text information association relation analysis

The invention provides a method, a system and a medium for establishing a control flow graph. The method comprises the following steps: S1, based on a function call graph of a target program and a control flow graph in a function, generating a first control flow graph through fusion, wherein the first control flow graph is an inter-process control flow graph and does not contain an indirect skip relation; s2, extracting an indirect jump point in the target program, and executing a distance-based guided grey-box fuzzy test on the target program according to the indirect jump point so as to generate test cases which are cases for executing different paths in a test process; and S3, determining the indirect jump relationship in the target program by using the test case to obtain a second control flow graph, the second control flow graph including the indirect jump relationship.

Method, system and medium for establishing control flow graph

The invention provides a method and system for improving the coverage rate of a fuzzy test. The method comprises the steps: S1, preprocessing a target program serving as a test case to obtain a call graph of a function in the target program; S2, determining anchor nodes for fuzzy test in the target program based on the call graph, the anchor nodes comprising a first anchor node based on a complexnetwork and a second anchor node based on a neural network; S3, according to the anchor nodes, determining the distances from the seed nodes to the anchor nodes through an instrumentation tool; and S4, calculating the energy of the seed nodes based on the distance, and selecting the seed nodes of which the energy is higher than a threshold value as a basis for evaluating the mutation test case.

Method and system for improving coverage of fuzzy test

The invention discloses a firmware version detection method and a vulnerability repair rate evaluation method of an Internet of Things device. The detection method comprises the following steps: S1, acquiring a firmware image file; 2, extracting that file system after decompressing the firmware image files, and determining the Web root directory of each file system; 3, searching Web static resources, respectively extracting eigenvalues of each Web static resource in various firmware versions under each device model, and constructing correspond firmware version characteristic tables; S4, obtaining the IP address list and firmware version characteristic table of the required device type, scanning fingerprint, extracting corresponding fingerprint, and identifying the firmware version number of the device; The evaluation method includes obtaining model version information of the target vulnerability, and calculating the repair rate of the target vulnerability according to the result of thedetection method. The invention has the advantages of simple realization method, high detection accuracy and efficiency, and the vulnerability repair rate evaluation without triggering the vulnerability.

Firmware version detection method and vulnerability repair rate evaluation method of internet of things device

The invention discloses a binary code-oriented guided fuzzy test method. The method comprises the steps of S1, analyzing a target program and marking a target basic block address; s2, loading a binaryprogram, obtaining program address information, disassembling a binary code to obtain an assembly code, and constructing a program control flow graph; s3, recording a branch skip condition when a program is executed, performing decoding after execution is finished, exporting an execution path, constructing and perfecting a control flow graph, and updating statistical data of branch execution; s4,calculating the distance between the current path and the target based on the current execution path in combination with the execution statistical data of the branches; and S5, taking the calculatedtarget distance as feedback, and guiding the selection and test of the next round of seeds. The method has the advantages of simple principle, easiness in implementation, capability of improving precision and the like.

Binary code-oriented guided fuzzy test method

The invention discloses a binary software protection method based on dynamic code conversion. The method comprises the following steps of: S1: extracting the basic block of a code to be protected to obtain pieces; S2: processing the pieces: equally dividing all pieces into two parts including an upper half part and a lower half part, randomly selecting certain pieces from the upper half part, and initializing the pieces into a ciphertext state, wherein the rest pieces of the corresponding lower half part of the upper half part are under the ciphertext state; and S3: inserting a decryption function: inserting the decryption function into the tails of all pieces for jumping, wherein the decryption function has the function that a next piece which is about to be executed is decrypted during operation. The method has the advantages of simple principle, easiness in realization, efficiency in execution, large protection strength and the like.

Yang Qiang

Papers

Firmware version detection method and vulnerability repair rate evaluation method of internet of things device

Binary code-oriented guided fuzzy test method

Binary software protection method based on dynamic code conversion