Abstract
This paper combines the common ideas and methods in an offensive and defensive confrontation in recent years and uses artificial intelligence technology-based network asset automatic mining technology and artificial intelligence technology-based vulnerability automatic exploitation technology carries out research and specific practices in discovering and using system vulnerability based on artificial intelligence technology designs and implemented automatic binary vulnerability discovering and exploitation system, which improves the efficiency and success rate of vulnerability discovering and exploitation.
Author Keywords
- artificial intelligence,
- automatic binary vulnerability discovering and exploitation system,
- network attack, and defense
Introduction
At present, major countries in the world have invested research and development forces in artificial intelligence-based automation network offense and defense. In the 2016 DEFCON final, the automated attack team Mayhem (the champion of the CGC in 2014) participated in the competition with 14 human teams and once defeated two human teams, indicating that the automatic attack methods generated by artificial intelligence systems can already be faster than humans. Continuously scan system defects and discover vulnerabilities more effectively. The Ministry of Defense of Japan also announced recently that in order to strengthen its ability to respond to Cyberattacks, artificial intelligence technology will be introduced into the information defense network defense system of the Japan Self-Defense Force. It is foreseeable that the deep application of artificial intelligence in the field of Cyber offense and defense may bring revolutionary changes and increase the imbalance in the strategic power of cyberspace in various countries. Therefore, systematically investigating the development status of artificial intelligence-based network offense and defense at home and abroad, comprehensively analyzing the development trends of domestic and international related technologies, analyzing the development outlines and specifications of artificial intelligence offense and defense in various countries in the world, and studying the application status and future of artificial intelligence offense and defense are of great significance for promoting the development of China’s artificial intelligence offensive and defensive technologies and ensuring the core interests of cyberspace.
This paper found the following problems during the research of network attack and defense: (1) The method of manual vulnerability discovering manually is time-consuming and costly, and it may cause omissions. At the same time, the code path coverage of existing vulnerability discovering methods is low and inefficient. (2) The existing vulnerability exploitation methods are mainly based on dynamic or static memory analysis methods. Through analysis of the memory, the crash points and runtime states are found. However, many vulnerabilities cannot be proven to be exploitable. Based on the above problems, this paper combines the common ideas and methods in an offensive and defensive confrontation in recent years and uses artificial intelligence technology-based network asset automatic mining technology and artificial intelligence technology-based vulnerability automatic exploitation technology carries out research and specific practices in discovering and using system vulnerability based on artificial intelligence technology, and enhance the system’s vulnerability discovery and utilization capabilities.
Conclusion
With the development of business, various components such as terminals, information systems, software, and programs that support the operation of various types of power grids continue to increase. However, the traditional security protection methods, such as vulnerability discovering various components that use manual attacks as the main means, have problems such as incomplete security discovery, poor timeliness, and low accuracy. The existing methods based on fuzzy testing have low coverage. The symbolic execution method has problems such as path explosion. Therefore, discovering potential security risks through artificial intelligence technology is of great significance for improving the network security confrontation ability of the State Grid Corporation and strengthening the construction of the information security system.
This paper combines the common ideas and methods in an offensive and defensive confrontation in recent years and uses artificial intelligence technology-based network asset automatic mining technology and artificial intelligence technology-based vulnerability automatic exploitation technology, carries out research and specific practices in discovering and using system vulnerability based on artificial intelligence technology, which improves the system’s vulnerability discovery and utilization capabilities, reduces the work of security personnel to a certain extent and improves the efficiency and success rate of vulnerability mining and utilization. It provides an idea for other types of repetitive work in the future.
About KSRA
The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.
KSRA research association, as a non-profit research firm, is committed to providing research services in the field of knowledge. The main beneficiaries of this association are public or private knowledge-based companies, students, researchers, researchers, professors, universities, and industrial and semi-industrial centers around the world.
Our main services Based on Education for all Spectrum people in the world. We want to make an integration between researches and educations. We believe education is the main right of Human beings. So our services should be concentrated on inclusive education.
The KSRA team partners with local under-served communities around the world to improve the access to and quality of knowledge based on education, amplify and augment learning programs where they exist, and create new opportunities for e-learning where traditional education systems are lacking or non-existent.
FULL Paper PDF file:
Research on Network Attack and Defense Based on Artificial Intelligence TechnologyBibliography
author
Year
2020
Title
Research on Network Attack and Defense Based on Artificial Intelligence Technology
Publish in
2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chongqing, China, 2020, pp. 2532-2534
Doi
10.1109/ITNEC48623.2020.9085100.
PDF reference and original file: Click here
Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.
Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.
Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.
