Research Background and Significance
With the development of enterprise application information technology, information security faces more challenges. Traditional security technologies and methods can no longer meet the growing needs of enterprises, so it is necessary to introduce new technical means for information security management (ISM) and risk assessment (RA). As an emerging technology field, big data (BD) and artificial intelligence (AI) technologies have powerful data processing and analysis capabilities, which can help enterprises achieve accurate and efficient RA and prediction (Dai, 2022; Meng et al., 2022). Especially in the hot development of new payment methods, such as mobile payment, how to ensure information security in the payment process has become an urgent problem to be solved. Based on this, this paper aims to discuss the application of BD and AI technologies in enterprise ISM and RA, aiming to provide new solutions to help enterprises ensure information security (Lei et al., 2022; Ye & Chen, 2021).
The application of BD and AI technologies in enterprise ISM and RA is significant (Wang & Dai, 2022). First, the accuracy and precision of RA can be improved. BD and AI technologies can conduct in-depth analysis and mining of massive data to help enterprises identify potential risks and provide accurate RA results. Second, risk monitoring and early warning can be strengthened. BD and AI technologies can realize the monitoring and analysis of network traffic and abnormal behavior to detect and respond to potential risks. Third, it can help enterprises develop a scientific security strategy. Through the analysis and mining of BD and AI technologies, enterprises can understand their information security status to provide a basis for formulating scientific and effective security strategies. Finally, it can improve the efficiency and effectiveness of security management. BD and AI technologies can realize automated RA and prediction, reduce the burden of security management, and improve management efficiency and effectiveness.
Based on this, this paper analyzes the specific steps of the mobile payment signature scheme based on the Number Theory Research Unit (NTRU) lattice, compares its superiority with the traditional mobile payment signature scheme, constructs the enterprise ISM and RA systems, and evaluates the system dynamically and in real time through the system performance evaluation index system. The innovation point of the research is to use the mobile payment signature scheme based on the digital signature scheme to improve the security of the mobile payment system and establish a set of enterprise ISM and RA systems, including risk identification, RA, monitoring and early warning, emergency response, and other links. This paper proposes a new solution for applying BD and AI technologies in enterprise ISM and RA, which has significant theoretical and practical value.
Research Objective
The main objective of this paper is to discuss the application of BD and AI technologies in enterprise ISM and RA, aiming to provide new solutions for enterprises to help enterprises protect information security. Specifically, the objectives include:
- 1.
Research and analyze BD and AI technologies' application status and trends in enterprise ISM and RA.
- 2.
Explore a mobile payment signature scheme based on the NTRU lattice to improve the security of mobile payment systems and conduct relevant experimental verification.
- 3.
Establish a set of enterprise ISM and RA systems, including risk identification, RA, monitoring and early warning, and emergency response, and use BD and AI technologies to analyze internal and external data of the enterprise to achieve automated RA.
- 4.
Verify the feasibility and effectiveness of the proposed methods and schemes and evaluate their application effects, advantages, and disadvantages.
Through the above research, the application and applicability of BD and AI technologies in enterprise ISM and RA can be deeply understood to provide scientific and reasonable ISM and RA solutions for enterprises and improve enterprise information security.