Study On Detection Technology Of Application Software Vulnerabilities

With the fast development of computer technology, software has been widely used in various fields, and has played an important role in people's daily life and work. At the same time, the scale of the software is increasing, the structure of the software is more complex, and the difficulty to design software with high security is more and more difficult. The great progress of network technology makes software security defects for a long time in the risk of all aspects of the malicious attacks and illegal invasion, so software security problems need to invest more research efforts.This article on application software vulnerabilities are and the common vulnerability detection method for in-depth study, analysis of different application software vulnerability detection framework respective development situation and the characteristics of, and a comparison of the advantages and disadvantages of vulnerability detection method. For commercial software under Windows environment, the source code is not open to the public, so that existing feasible vulnerability detection method in choice of subject to some constraints, disassembly analysis and the problem of high false alarm rate, and fuzzing detection technology as the main method to the software developers vulnerability detection at present, both vulnerability detection veracity and vulnerability detection efficiency, with low cost, high efficiency, easy realization of automation, easy to configure features is a very effective method of software testing. But different procedures for different hole types, to improve the detection rate, you need to re enact effective test programs and the corresponding test data, only depending on the fuzzing testing technology in detecting efficiency and cannot meet the corresponding standards.We are aiming to the problem of detecting vulnerabilities of the above proposed a new adaptive software vulnerability detection scheme. The scheme includes fuzzing module, API hook module and data processing module in the program in order to improve the efficiency of vulnerability detection, using fuzzing technique to detect the design model of a module and AC automata algorithm is introduced. Analysis the specific circumstances of the search tree, try the AC automata algorithm is improved because search tree does not need to be a contains another situation, so we get rid of the traditional AC automata algorithm failure pointer part. Here we use improved AC automata algorithm to obtain an API sequence, and the modified AC automata algorithm efficiency respectively with Apriori and FP growth were compared. Experimental results show that AC automata algorithm spend less time can complete vulnerability detection, greatly improving the detection efficiency.