| Title | Privacy Preserving Cyberbullying Prevention with AI Methods in 5G Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Ramezanian, Sara, Niemi, Valtteri |
| Conference Name | 2019 25th Conference of Open Innovations Association (FRUCT) |
| Date Published | nov |
| Keywords | 5G mobile communication, 5G networks, AI, AI methods, Cyberbullying Detection, cyberbullying incidents, data privacy, Human Behavior, human factors, learning (artificial intelligence), online social media, operator labels subscribers, privacy, privacy preserving cyberbullying prevention, psychological effects, pubcrawl, resilience, Resiliency, Scalability, social networking (online), subscribers benign messages, telecommunication computing, term frequency-inverse document frequency |
| Abstract | Children and teenagers that have been a victim of bullying can possibly suffer its psychological effects for a lifetime. With the increase of online social media, cyberbullying incidents have been increased as well. In this paper we discuss how we can detect cyberbullying with AI techniques, using term frequency-inverse document frequency. We label messages as benign or bully. We want our method of cyberbullying detection to be privacy-preserving, such that the subscribers' benign messages should not be revealed to the operator. Moreover, the operator labels subscribers as normal, bully and victim. The operator utilizes policy control in 5G networks, to protect victims of cyberbullying from harmful traffic. |
| DOI | 10.23919/FRUCT48121.2019.8981521 |
| Citation Key | ramezanian_privacy_2019 |
Privacy Preserving Cyberbullying Prevention with AI Methods in 5G Networks