X-Phishing-Writer: A Framework for Cross-Lingual Phishing Email Generation

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Shih-Wei Guo, Yao-Chung Fan
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引用次数: 0

Abstract

Cybercrime is projected to cause annual business losses of $10.5 trillion by 2025, a significant concern given that a majority of security breaches are due to human errors, especially through phishing attacks. The rapid increase in daily identified phishing sites over the past decade underscores the pressing need to enhance defenses against such attacks. Social Engineering Drills (SEDs) are essential in raising awareness about phishing, yet face challenges in creating effective and diverse phishing email content. These challenges are exacerbated by the limited availability of public datasets and concerns over using external language models like ChatGPT for phishing email generation. To address these issues, this paper introduces X-Phishing-Writer, a novel cross-lingual Few-Shot phishing email generation framework. X-Phishing-Writer allows for the generation of emails based on minimal user input, leverages single-language datasets for multilingual email generation, and is designed for internal deployment using a lightweight, open-source language model. Incorporating Adapters into an Encoder-Decoder architecture, X-Phishing-Writer marks a significant advancement in the field, demonstrating superior performance in generating phishing emails across 25 languages when compared to baseline models. Experimental results and real-world drills involving 1,682 users showcase a 17.67% email open rate and a 13.33% hyperlink click-through rate, affirming the framework’s effectiveness and practicality in enhancing phishing awareness and defense.

X-Phishing-Writer:跨语言网络钓鱼电子邮件生成框架
预计到 2025 年,网络犯罪每年将造成 10.5 万亿美元的商业损失,鉴于大多数安全漏洞都是人为失误造成的,特别是通过网络钓鱼攻击造成的,因此这是一个重大问题。在过去十年中,每天发现的网络钓鱼网站迅速增加,这突出表明迫切需要加强对此类攻击的防御。社会工程演习 (SED) 对于提高人们对网络钓鱼的认识至关重要,但在创建有效和多样化的网络钓鱼电子邮件内容方面却面临挑战。公共数据集的有限可用性以及对使用 ChatGPT 等外部语言模型生成网络钓鱼电子邮件的担忧加剧了这些挑战。为了解决这些问题,本文介绍了一种新颖的跨语言 Few-Shot 网络钓鱼电子邮件生成框架 X-Phishing-Writer。X-Phishing-Writer 允许基于最少的用户输入生成电子邮件,利用单语言数据集生成多语言电子邮件,并使用轻量级开源语言模型进行内部部署。X-Phishing-Writer 将适配器整合到编码器-解码器架构中,标志着该领域的重大进步,与基线模型相比,它在生成 25 种语言的网络钓鱼电子邮件方面表现出色。有 1682 名用户参与的实验结果和实际演练显示,电子邮件打开率为 17.67%,超链接点击率为 13.33%,这肯定了该框架在增强网络钓鱼意识和防御方面的有效性和实用性。
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来源期刊
CiteScore
3.60
自引率
15.00%
发文量
241
期刊介绍: The ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) publishes high quality original archival papers and technical notes in the areas of computation and processing of information in Asian languages, low-resource languages of Africa, Australasia, Oceania and the Americas, as well as related disciplines. The subject areas covered by TALLIP include, but are not limited to: -Computational Linguistics: including computational phonology, computational morphology, computational syntax (e.g. parsing), computational semantics, computational pragmatics, etc. -Linguistic Resources: including computational lexicography, terminology, electronic dictionaries, cross-lingual dictionaries, electronic thesauri, etc. -Hardware and software algorithms and tools for Asian or low-resource language processing, e.g., handwritten character recognition. -Information Understanding: including text understanding, speech understanding, character recognition, discourse processing, dialogue systems, etc. -Machine Translation involving Asian or low-resource languages. -Information Retrieval: including natural language processing (NLP) for concept-based indexing, natural language query interfaces, semantic relevance judgments, etc. -Information Extraction and Filtering: including automatic abstraction, user profiling, etc. -Speech processing: including text-to-speech synthesis and automatic speech recognition. -Multimedia Asian Information Processing: including speech, image, video, image/text translation, etc. -Cross-lingual information processing involving Asian or low-resource languages. -Papers that deal in theory, systems design, evaluation and applications in the aforesaid subjects are appropriate for TALLIP. Emphasis will be placed on the originality and the practical significance of the reported research.
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