Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs

Author(s):  
Animesh Nandi ◽  
Atri Mandal ◽  
Shubham Atreja ◽  
Gargi B. Dasgupta ◽  
Subhrajit Bhattacharya
Author(s):  
Vladislav Vladislavovich Lukashenko ◽  
Vitaly Aleksandrovich Romanchuk

In terms of the problem of insufficient computational resources for a number of tasks, realization of computational cluster of neurocomputers is being considered as a variant. To implement the basic principle of distributed computing, there has been presented an algorithm for splitting the tasks entering the computational cluster of neurocomputers into sub-tasks. For this purpose, the program introduced into the cluster is suggested to present for execution in the modified postfix Polish record and to store it in the program command stack. To modify the program Polish notation should include different, non-arithmetic, operators and constructions. The next step is to get an abstract syntax tree of the program, following the rules for translating the modified postfix Polish record from the command stack into an abstract syntax tree. Then, the data should be sent to the abstract syntax tree of the program taking into account their bit depth, and to obtain the contiguity matrix of the program control flow graph that will display the set of all ways of program execution. The authors come to the conclusion that all operations recorded in the modified reverse Polish record presented in the form of an abstract syntax tree when data of a certain bit depth are transmitted to them, at the moment of transition to the program control flow graph executed in a single clock cycle are indivisible operations and can be represented as subprograms of the source program, which was submitted for processing to the computer cluster of neurocomputers.


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