Purpose: The purpose of this paper is to explore broader and dynamic features of talent, talent management, its policies and its impact on academic working environment. Design/methodology/approach: This research was based on qualitative research in the form of unstructured interviews containing open-ended questions. Data were collected from the university management, deans, heads of departments (HoDs), assistant professors, associate professors and lecturers. The research was conducted in the form of interviews and the participants were asked to define talent, talent management (TM) policies, its usefulness and its impact on the working environment within the university. This study was conducted into two parts. In the first part, all deans, HoDs and human resource management (HRM) (stakeholders) were interviewed, and in the second part, all professors, associate professors, assistant professors and lecturers (talents) were interviewed. Findings: The present study investigated that talent and TM are very important in any academic organization. The impact of HRM on TM is very important, as it defines how an academic organization works to retain its talent and improve working conditions within the organization. In addition, this paper details the barriers that the human resource department faces with regard to TM and vice versa. Further, the authors attempted to ascertain the academic staff’s perspectives, their needs and the difficulties they face within the university. Originality/value: This research paper shows the difficulties faced by the government institutions in China and Pakistan and how they cope with the current situation of TM within the available resources, polices and the impact of these on the working environment.

This paper focuses on electromagnetic information security in communication systems. Classical correlation electromagnetic analysis (CEMA) is known as a powerful way to recover the cryptographic algorithm’s key. In the classical method, only one byte of the key is used while the other bytes are considered as noise, which not only reduces the efficiency but also is a waste of information. In order to take full advantage of useful information, multiple bytes of the key are used. We transform the key into a multidimensional form, and each byte of the key is considered as a dimension. The problem of the right key searching is transformed into the problem of optimizing correlation coefficients of key candidates. The particle swarm optimization (PSO) algorithm is particularly more suited to solve the optimization problems with high dimension and complex structure. In this paper, we applied the PSO algorithm into CEMA to solve multidimensional problems, and we also add a mutation operator to the optimization algorithm to improve the result. Here, we have proposed a multibyte correlation electromagnetic analysis based on particle swarm optimization. We verified our method on a universal test board that is designed for research and development on hardware security. We implemented the Advanced Encryption Standard (AES) cryptographic algorithm on the test board. Experimental results have shown that our method outperforms the classical method; it achieves approximately 13.72% improvement for the corresponding case.

Correlation electromagnetic analysis (CEMA) is a method prevalent in side-channel analysis of cryptographic devices. Its success mostly depends on the quality of electromagnetic signals acquired from the devices. In the past, only one byte of the key was analyzed and other bytes were regarded as noise. Apparently, other bytes’ useful information was wasted, which may increase the difficulty of recovering the key. Multi-objective optimization is a good way to solve the problem of a single byte of the key. In this work, we applied multi-objective optimization to correlation electromagnetic analysis taking all bytes of the key into consideration. Combining the advantages of multi-objective optimization and genetic algorithm, we put forward a novel multi-objective electromagnetic analysis based on a genetic algorithm to take full advantage of information when recovering the key. Experiments with an Advanced Encryption Standard (AES) cryptographic algorithm on a Sakura-G board demonstrate the efficiency of our method in practice. The experimental results show that our method reduces the number of traces required in correlation electromagnetic analysis. It achieved approximately 42.72% improvement for the corresponding case compared with CEMA.