Brij B. Gupta^1,2,3,4,*, Akshat Gaurav⁵, Varsha Arya^6,7, Razaz Waheeb Attar⁸, Shavi Bansal⁹, Ahmed Alhomoud¹⁰, Kwok Tai Chui¹¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2165-2183, 2024, DOI:10.32604/cmes.2024.056473 - 31 October 2024

Abstract Phishing attacks present a serious threat to enterprise systems, requiring advanced detection techniques to protect sensitive data. This study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers (BERT) for feature extraction and CNN for classification, specifically designed for enterprise information systems. BERT’s linguistic capabilities are used to extract key features from email content, which are then processed by a convolutional neural network (CNN) model optimized for phishing detection. Achieving an accuracy of 97.5%, our proposed model demonstrates strong proficiency in identifying phishing emails. This approach represents a significant advancement in More >

Tehreem Aslam¹, Ayesha Maqbool¹, Maham Akhtar¹, Alina Mirza^2,*, Muhammad Anees Khan³, Wazir Zada Khan⁴, Shadab Alam⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1089-1109, 2022, DOI:10.32604/cmc.2022.019416 - 07 September 2021

Abstract Enterprise Resource Planning (ERP) software is extensively used for the management of business processes. ERP offers a system of integrated applications with a shared central database. Storing all business-critical information in a central place raises various issues such as data integrity assurance and a single point of failure, which makes the database vulnerable. This paper investigates database and Blockchain integration, where the Blockchain network works in synchronization with the database system, and offers a mechanism to validate the transactions and ensure data integrity. Limited research exists on Blockchain-based solutions for the single point of failure More >