For a better detection in Network information security monitoring system, the author proposes a method based on adaptive depth detection. A deep belief network was designed and implemented, and the intrusion detection system model was combined with a support vector machine. The data set adopts the NSL-KDD network communication data set, and this data set is authoritative in the security field. Redundant cleaning, data type conversion, normalization, and other processing operations are performed on the data set. Using the data conversion (...) method based on the probability mass function probability mass function coding, a standard data set with low redundancy and low dimensionality can be obtained. Research indicates that when the batch size reaches 64, the accuracy of the test set reaches its maximum value. As the batch size increases, the accuracy first increases and then decreases. When the batch size continues to increase, the model will inevitably fall into the local optimal state, resulting in the degradation of the detection performance of the system. In terms of the false alarm rate, the DBN-SVM model is also the highest; however, it is only 10.73%. Under the premise of increasing the detection rate, the false alarm rate is improved; for the overall detection performance of the model, it is within an acceptable range. In terms of accuracy, the DBN-SVM model also scored the highest. The accuracy rate is the ratio of normal and correct classification for intrusion detection. It can explain the detection ability of the model. In summary, the overall detection ability of the DBN-SVM model is the best. The good classification ability to use SVM is proved, and the classification of low-dimensional features is expected to increase the detection rate of the system. (shrink)

This paper explores the level of corporate social responsibility contributions disclosed by central public sector enterprises in India. This paper analyses the nature and quality of CSR disclosures made by CPSEs listed in India following the issue of CSR guidelines by the Department of Public Enterprises for CPSEs in March 2010. The purpose of the study is to investigate the impact of CSR guidelines on the reporting practices of the CPSEs. A content analysis of annual reports across seven themes shows (...) that Human Resources and Community Development are the prime focus areas of CSR disclosures, whereas Carbon and Greenhouse Gas emissions are the least reported activity. The disclosures across all CSR themes are primarily narrative rather than quantitative or in monetary terms. The findings of the study may help policy makers in India to assess practices and devise detailed and specific CSRD requirements, rather than the current general mandatory requirements, to enhance the performance and quality of CSRDs by the CPSEs. (shrink)

This study provides evidence on the governance of CSR policies and activities by Indian central government-owned companies [i.e. Central Public Sector Enterprises ] within a unique mandatory regulatory setting. We utilise the multi-level ‘Logic of governance’ conceptual framework and draw upon interview data collected from 25 senior managers in 21 CPSEs to assess the dynamics of CSR implementation within CPSEs. Our findings indicate most managers believe that a mandatory policy has enhanced the accountability and commitment of governing boards and senior (...) management to CSR. However, CSR policy implementation within Indian CPSEs is still nascent, fraught with bureaucratic hurdles, insufficient human and knowledge resources, limited stakeholder analysis and over-emphasis on CSR budget utilisation as an outcome. Several key areas for improvements include the need for better translation of national CSR policy goals to firm-level strategies, more formal assessment of stakeholder needs, clearer communication lines with external service providers, such as NGOs and local government agencies, and the better evaluation of CSR outcomes. The findings of this study have implications for both theory and policy development. (shrink)