The rise of offensive content on social media, encompassing both abusive language and inappropriate images, poses a significant threat to individuals and communities, often resulting in bullying or emotional harm. To address this challenge, researchers have explored supervised approaches and curated datasets to enable automatic detection of such content. This study proposes a comprehensive model that integrates both text and image classification techniques. For text, the model incorporates a modular cleaning phase, tokenization, three embedding methods, and eight classifiers. For image detection, computer vision techniques such as convolutional neural networks (CNNs) are employed to identify harmful or offensive visual content. Experimental results on a Twitter dataset demonstrate promising outcomes, with AdaBoost, SVM, and MLP achieving the highest F1-scores using the popular TF-IDF embedding method for text, while pre-trained CNN models like ResNet and EfficientNet show high accuracy in identifying offensive images. These findings highlight the effectiveness of combining advanced NLP and computer vision techniques for detecting offensive content on social media.
Introduction
In today’s digital age, ensuring the authenticity, integrity, and security of electronic documents is crucial. Digital signatures serve as secure, tamper-evident marks that verify a document's origin and prevent unauthorized changes. Unlike traditional handwritten signatures, digital signatures use cryptographic algorithms—mainly RSA and ECDSA—to generate unique identifiers for documents, enabling reliable signing and verification.
The project "Digital Signature Tool" aims to develop a user-friendly, secure application for signing and verifying digital documents, targeting both individuals and organizations. It emphasizes robust cryptographic methods, secure key management, and ease of use to address growing cybersecurity threats.
The literature review highlights the origins of digital signatures, their cryptographic foundations, evolution (from RSA to ECC/ECDSA), wide-ranging applications (government, finance, healthcare, legal), and current digital signature tools. It also discusses challenges such as key management, user awareness, interoperability, and legal compliance.
Key success factors for the tool include:
Strong, secure implementation of cryptographic algorithms.
Cross-platform compatibility and support for common document formats.
Comprehensive application security.
Compliance with relevant legal standards.
Efficient performance.
Building user trust through transparency and possibly open-source options.
Ongoing maintenance and user education.
The tool aims to bridge the gap between complex cryptographic technology and everyday users by providing a secure, accessible platform to promote trustworthy digital communication.
Conclusion
In an era where digital communication and document exchange have become the norm, ensuring the authenticity, integrity, and security of information is more critical than ever. This project, Digital Signature Tool, addresses these pressing needs by providing a secure, efficient, and user-friendly application for signing and verifying digital documents.
By leveraging powerful cryptographic techniques such as RSA and ECDSA, the tool ensures that users can confidently protect their documents against tampering and unauthorized access. The integration of essential features like secure key management, fast signing and verification processes, and an intuitive user interface further enhances the tool\'s practicality and accessibility for both technical and non-technical users.
Through this project, we have demonstrated that it is possible to build a lightweight yet highly secure digital signature solution that operates independently, without reliance on external servers or third-party cloud services. By prioritizing security, performance, legal compliance, and ease of use, the Digital Signature Tool offers a reliable platform that individuals, businesses, and organizations can trust to safeguard their digital communications.
Looking forward, this project lays the groundwork for future enhancements, such as incorporating additional signing algorithms, expanding support for various document types, and potentially integrating hardware-based key storage for even stronger security. Overall, the Digital Signature Tool contributes meaningfully to promoting secure, transparent, and trustworthy digital interactions in a rapidly evolving digital landscape.
Future Enhancements
While the Digital Signature Tool meets the essential requirements for secure signing and verification of documents, there are several possibilities for further improvement and expansion. Implementing these future enhancements would make the application more powerful, versatile, and aligned with evolving user needs and technological advancements.
References
[1] Stallings, William.\"Cryptography and Network Security: Principles and Practice.\"6th Edition, Pearson Education, 2014.
[2] Menezes, Alfred J., van Oorschot, Paul C., and Vanstone, Scott A.\"Handbook of Applied Cryptography.\"CRC Press, 1996.
[3] Rivest, R. L., Shamir, A., & Adleman, L.\"A Method for Obtaining Digital Signatures and Public-Key Cryptosystems.\"Communications of the ACM, 21(2), 1978, pp. 120–126.National Institute of Standards and Technology (NIST).
\"Digital Signature Standard (DSS).\"FIPS PUB 186-4, July 2013.Available at: https://nvlpubs.nist.gov/nistpubs/FIPS/NIST.FIPS.186-4.pdfEuropean Union.
\"eIDAS Regulation: Regulation (EU) No 910/2014 on electronic identification and trust services for electronic transactions in the internal market.\"Available at: https://eur-lex.europa.eu/eli/reg/2014/910/oj
[4] Diffie, W., & Hellman, M.\"New Directions in Cryptography.\"IEEE Transactions on Information Theory, 22(6), 1976, pp. 644–654.OpenSSL Project.\"OpenSSL: Cryptography and SSL/TLS Toolkit.\"Available at: https://www.openssl.org/