A Survey on Emoji and Unicode-Based Data Masking Attacks on AI Systems

With the constant introduction of AI technologies into our lives, attack surfaces are emerging on the basis of vulnerabilities in AI processing systems. Text input manipulation, through the use of Unicode-based data obfuscation (e.g. the use of emojis, zero-width characters, and homoglyph replacements) is one of them. such techniques enable attackers to bypass filters, evade content moderation, and even insert adversarial prompts into large language models (LLMs). This survey studies the situation regarding emoji and Unicode-based data masking attacks, categorizes the techniques used, determines legitimate uses, and discusses the difficulties with defending against these attacks. Future work is also suggested in the research as well as summarizing possible defence schemes. This paper has tried to assemble recent research and field-based case studies in an effort to form a concrete basis of research.