G. Maria Jones^1,*, S. Godfrey Winster², P. Valarmathie³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 87-102, 2022, DOI:10.32604/iasc.2022.022972 - 05 January 2022

Abstract Rapid advancement of digital technology has encouraged its use in all aspects of life, including the workplace, education, and leisure. As technology advances, so does the number of users, which leads to an increase in criminal activity and demand for a cyber-crime investigation. Mobile phones have been the epicenter of illegal activity in recent years. Sensitive information is transferred due to numerous technical applications available at one’s fingertips, which play an essential part in cyber-crime attacks in the mobile environment. Mobile forensic is a technique of recovering or retrieving digital evidence from mobile devices so… More >

G. Maria Jones^1,*, S. Godfrey Winster², P. Valarmathie³

Computer Systems Science and Engineering, Vol.40, No.3, pp. 963-978, 2022, DOI:10.32604/csse.2022.019483 - 24 September 2021

Abstract Mobile devices and social networks provide communication opportunities among the young generation, which increases vulnerability and cybercrimes activities. A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters. This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit. We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection. We use forensics techniques, Machine Learning (ML), and Deep Learning More >