Multi-method integrated experimental teaching reform of a programming course based on the OBE-CDIO model under the background of engineering education.

Under the background of engineering education professional certification, the Outcome-Based Education (OBE) education concept of "output-oriented" has been paid more and more attention. The traditional experimental teaching of programming course often focuses on the teaching of theoretical knowledge, and lacks the cultivation of students' practical ability and innovative spirit. Engineering education puts forward new requirements for the teaching mode of program design course. The experimental teaching of programming courses requires further reform and innovation to cultivate high-quality technical engineering talents with good social responsibility, teamwork ability, and innovative thinking ability. Guided by the theory of engineering education combined with the educational philosophy of Conceive-Design-Implement-Operate (CDIO) and OBE, this paper carried out the reform of experimental teaching of programming course among students majoring in computer science and technology and information security. This teaching reform aimed to better cultivate students' practical ability, innovation ability, and knowledge-integrated application ability, considering the course concept, course design, course implementation, and course operation, and exploring the practice of teaching process reconfiguration, teaching content organization, and teaching method integration. This multi-integration experimental teaching reform was found to fully mobilize students' learning enthusiasm, tap into students' potential, greatly improve students' comprehensive practical ability, effectively achieve course goals, and lay a solid foundation for subsequent professional course learning. This teaching mode has been practically applied in current experimental teaching and is widely recognized by students, providing a reference for improving teaching quality.

A novel network security situation assessment model based on multiple strategies whale optimization algorithm and bidirectional GRU.

The rapid development of the internet has brought about a comprehensive transformation in human life. However, the challenges of cybersecurity are becoming increasingly severe, necessitating the implementation of effective security mechanisms. Cybersecurity situational awareness can effectively assess the network status, facilitating the formulation of better cybersecurity defense strategies. However, due to the low accuracy of existing situational assessment methods, situational assessment remains a challenge. In this study, a new situational assessment method, MSWOA-BiGRU, combining optimization algorithms and temporal neural networks, was proposed. Firstly, a scientific indicator system proposed in this research is used to calculate the values of each indicator. Then, the Analytic Hierarchy Process is used to derive the actual situation values, which serve as labels. Taking into account the temporal nature of network traffic, the BiGRU model is utilized for cybersecurity situational assessment. After integrating time-related features and network traffic characteristics, the situational assessment value is obtained. During the evaluation process, a whale optimization algorithm (MSWOA) improved with a mix of strategies proposed in this study was employed to optimize the model. The performance of the proposed MSWOA-BiGRU model was evaluated on publicly available real network security datasets. Experimental results indicate that compared to traditional optimization algorithms, the optimization performance of MSWOA has seen significant enhancement. Furthermore, MSWOA-BiGRU demonstrates superior performance in cybersecurity situational assessment compared to existing evaluation methods.

Public Key Encryption with Keyword Search in Cloud: A Survey.

With the popularization of cloud computing, many business and individuals prefer to outsource their data to cloud in encrypted form to protect data confidentiality. However, how to search over encrypted data becomes a concern for users. To address this issue, searchable encryption is a novel cryptographic primitive that enables user to search queries over encrypted data stored on an untrusted server while guaranteeing the privacy of the data. Public key encryption with keyword search (PEKS) has received a lot of attention as an important branch. In this paper, we focus on the development of PEKS in cloud by providing a comprehensive research survey. From a technological viewpoint, the existing PEKS schemes can be classified into several variants: PEKS based on public key infrastructure, PEKS based on identity-based encryption, PEKS based on attribute-based encryption, PEKS based on predicate encryption, PEKS based on certificateless encryption, and PEKS supporting proxy re-encryption. Moreover, we propose some potential applications and valuable future research directions in PEKS.