Research On PLC Vulnerability Mining Method Based On Protocol Reverse And Fuzzing

Industrial control systems are widely used in industrial production,and their safety issues affect the lifeblood of the entire country.With the development of the industrial Internet,more and more industrial control equipment is connected to the Internet,and the industrial control system is becoming more and more open and facing greater risks.Industrial control programmable logic controllers are widely used in industrial control systems,and attackers can exploit their vulnerabilities to achieve damage and intrusion of the entire industrial control system.As a communication format within the industrial control system,the industrial control protocol is one of the keys to the research of industrial control security.Therefore,how to better mine the loopholes of PLC in reverse with the protocol is a hot research issue in the field of security in recent years.In order to better realize PLC vulnerability mining,this paper investigates the research status and related applications of vulnerability mining and protocol reversal.On this basis,this paper proposes a PLC vulnerability mining method based on protocol reverse and fuzzy testing.The specific research carried out in this paper is as follows:1.The advantages and limitations of the existing protocol inverse method are analyzed,and a new algorithm for field boundary division using statistical learning is proposed.Starting from the packet data,the boundaries of the message data fields are extracted based on the clustering and multi-sequence alignment algorithms of key information.2.A new semantic extraction algorithm based on deep learning is proposed.Firstly,a variety of semantic definitions based on the definition of field numerical change law are proposed,and then a special precoding processing method is proposed to improve the accuracy of the algorithm,and finally the improved deep model algorithm is used to realize the semantic extraction.3.A new fuzzy test method combining genetic algorithm and result feedback is designed for PLC vulnerability mining.The result weight of the feedback message is calculated by using the pre-sequence reverse result,and the effective test case is generated efficiently by combining the genetic variation algorithm.Finally,experiments are performed on a variety of devices and protocols,which show the effectiveness of all methods in this paper.