Enhancing Cyberbullying Detection on Twitter with Psychological Features and Machine Learning DOI

Venkata Lalitha Narla,

Sumaya Thabasum Sk,

N Tejaswini

et al.

Published: Dec. 7, 2023

Today, a large number of people dabble in the realm social media. Due to pandemic situation, are even more engaged since they frequently use media vent their emotions. One many detrimental effects this pervasive usage is cyberbullying, which troubling form online harassment. Though it can take several forms, most common one text. Cyberbullying on media, and instead confronting perpetrator, victims often have mental breakdowns as result it. This study's computerized cyberbullying detection method accesses Twitter users' psychological traits, including personalities, moods, Our study provides an innovative solution for detecting tweets by attention-based transformer algorithm combined with embeddings. model acts detector classifying that related cyberbullied actions. These converted into numerical vectors Embeddings divided fixed segments through padding technique. The learns from encoder part comprising self-attention feed-forward neural network normalization tweet's dataset. Incredibly accurate made possible integrated technology. approach promises identify quickly precisely give control women over situation.

Language: Английский

Data Leakage Detection and Prevention Using Ciphertext-Policy Attribute Based Encryption Algorithm DOI

V Sasikala,

Lakshmi Saipriya P,

Nagaraja Kumari P

et al.

2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Journal Year: 2024, Volume and Issue: unknown, P. 1 - 5

Published: March 14, 2024

Unauthorized information transfer from an enterprise to a third party is known as data leakage. In the modern era, everything done online, including transfers, stocks, groceries, clothing, appliances, and money transactions. To avoid misuse, all shared needs be protected unwanted access. It helps protect prevent leakage of unstructured in addition assisting with preservation formatted data. Utilization Ciphertext-Policy Attribute-Based Encryption Algorithm has surfaced viable approach safeguard both during transmission storage. The system starts preventive actions, such encryption updates or access limits, case suspected breach lessen effect. By combining anomaly detection methods CP-ABE, strong framework for improving security privacy across range domains presented, providing proactive line defense against possible breaches.this method improves System efficiency prevens daa leakages less time.

Language: Английский

Citations

0
Enhancing Cyberbullying Detection on Twitter with Psychological Features and Machine Learning DOI

Venkata Lalitha Narla,

Sumaya Thabasum Sk,

N Tejaswini

et al.

Published: Dec. 7, 2023

Today, a large number of people dabble in the realm social media. Due to pandemic situation, are even more engaged since they frequently use media vent their emotions. One many detrimental effects this pervasive usage is cyberbullying, which troubling form online harassment. Though it can take several forms, most common one text. Cyberbullying on media, and instead confronting perpetrator, victims often have mental breakdowns as result it. This study's computerized cyberbullying detection method accesses Twitter users' psychological traits, including personalities, moods, Our study provides an innovative solution for detecting tweets by attention-based transformer algorithm combined with embeddings. model acts detector classifying that related cyberbullied actions. These converted into numerical vectors Embeddings divided fixed segments through padding technique. The learns from encoder part comprising self-attention feed-forward neural network normalization tweet's dataset. Incredibly accurate made possible integrated technology. approach promises identify quickly precisely give control women over situation.

Language: Английский

Citations

0