Intel Shield

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@article{1710648,
      author = {Shruthi B L, Ramya H P, Swathi R, Sangeetha C R, Yashodha S},
      title = {Intel Shield},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {3},
      pages = {774-778},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710648.pdf},
      abstract = {Cyberbullying is a growing threat in the digital age, particularly among teenagers and young adults on social media platforms. Traditional moderation methods such as manual review and keyword filtering often fail to capture the nuanced and evolving nature of abusive behaviour, especially across multimedia formats. This paper proposes Intel Shield, an AI-powered mobile application that leverages deep learning models like CNN, RNN, and LSTM to detect cyberbullying across text, images, and audio. The system includes a dynamic reputation score that penalizes users exhibiting repeated abusive behaviour, encouraging accountability. Real-time alerts, multilingual support, and seamless integration with popular communication platforms ensure timely intervention and a safer digital environment. With its modular, plug-and-play design, Intel Shield offers a scalable and effective solution to address cyberbullying across various online ecosystems},
      keywords = {Cyberbullying Detection, Deep Learning, CNN, RNN, LSTM, Multimodal Content Analysis, Reputation Scoring, Real-Time Monitoring, AI in Social Media, Digital Safety, -Play Architecture, Multilingual Support},
      month = {September},
  }