In a dynamic computing environment, it is a nontrivial task to verify code running in the environment because most approaches to software similarity require extensive and time-consuming analysis of a binary, or the approaches fail to recognize executables that are similar but nonidentical. A biosequence-based method for quantifying similarity of executable binaries is used to identify allowed codes in a real-world multi-user environment.

According to one aspect of the present disclosure, a method comprises receiving a command to load first compiled program code for execution by a processor. The first compiled program code is decompiled to generate source code. The source code is compiled to generate second compiled program code, the second compiled program code comprising information associated with the source code. The second compiled program code is provided to a debugger.

Various embodiments relate to a method, controller, and machine-readable storage medium for verifying controlled devices attached to the controller including one or more of the following: selecting, using a system model that models a system of devices comprising the controlled devices attached to the controller, a grouping of the system of devices to be tested; conducting a test of the grouping to produce a test result for the grouping, wherein conducting the test comprises transmitting a communication to at least one device associated with the grouping; choosing a graphical representation of a portion of the system model from a plurality of graphical representations based on the graphical representation including a representation of the grouping; and displaying, on a user interface, the graphical representation and an indication of the test result.

Various embodiments relate to a method, controller, and machine-readable storage medium for verifying controlled devices attached to the controller including one or more of the following: selecting, using a system model that models a system of devices comprising the controlled devices attached to the controller, a grouping of the system of devices to be tested; conducting a test of the grouping to produce a test result for the grouping, wherein conducting the test comprises transmitting a communication to at least one device associated with the grouping; choosing a graphical representation of a portion of the system model from a plurality of graphical representations based on the graphical representation including a representation of the grouping; and displaying, on a user interface, the graphical representation and an indication of the test result.

A method for identifying a type of a variable within a binary performed on a computing device is provided. The method comprises, identifying a variable from disassembly code of a binary, and determining a type of the variable based on an instruction of the disassembly code, associated with the variable.

A method for identifying a type of a variable within a binary performed on a computing device is provided. The method comprises, identifying a variable from disassembly code of a binary, and determining a type of the variable based on an instruction of the disassembly code, associated with the variable.

Disclosed is a description-entropy-based intelligent detection method for a big data mobile software similarity. The method comprises the following steps: acquiring a path of mobile software, and reading a file of the mobile software according to the path; performing preliminary reverse engineering decompilation on the file of the mobile software to obtain function characteristics of each piece of mobile software; counting distribution of description entropy of each piece of mobile software by means of description entropy in the function characteristics; further integrating description entropy of each piece of mobile software, after integration, comparing description entropy distribution conditions among the mobile software, and carrying out similarity score calculation to obtain similarity scores among the mobile software; and outputting the similarity scores of all mobile software to obtain a mobile software similarity result. According to the method, a source code of the mobile software is acquired by means of decompilation, a function compression code is acquired, and then the description entropy is acquired; and the description entropy is used as an information amount for representing an object and used for similarity detection of the mobile software, thus greatly increasing the speed of intelligent calculation of software similarity.

An improved CFI system and method is described that provides security from attacks to hijack computer software. The improved CFI system and method inserts two tags to execute label identification. The first tag is positioned before any instruction that would result in an indirect control flow transfer and requires the program to execute a check. The second tag is located before the first line of any legitimate transfer destination and when discovered by the tag check allows a program to carry out the indirect transfer. This tag orientation does not prevent transfers to targets other than the origin instruction's specific intended destination but limits transfers to destinations that begin with the proper label dedication. Although, an incorrect address may be called, that will be within the software program's assortment of legitimate indirect transfer targets. Attempts to exploit or reroute indirect transfers outside of the established control flow are eliminated.

Controllers that control a building's state functions can be controlled by a master controller that the controllers choose themselves. The master controller communicates with the controllers and sensors to determine when a building state should change. When the building state should change, the master controller or another controller determines the device or devices that need to modify state values of the building, and send messages to the devices so that they can change building state. If the master controller has a fault, the working controllers can choose another master controller. When a sensor indicates that a building state needs to be changed the master controller determines which device should change state, then tells the controller that is attached to the device.

Controllers that control a building's state functions can be controlled by a master controller that the controllers choose themselves. The master controller communicates with the controllers and sensors to determine when a building state should change. When the building state should change, the master controller or another controller determines the device or devices that need to modify state values of the building, and send messages to the devices so that they can change building state. If the master controller has a fault, the working controllers can choose another master controller. When a sensor indicates that a building state needs to be changed the master controller determines which device should change state, then tells the controller that is attached to the device.