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Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks. However, their practical application in high-stake domains, such as fraud and abuse detection, remains an area that requires…

计算与语言 · 计算机科学 2024-09-11 Joymallya Chakraborty , Wei Xia , Anirban Majumder , Dan Ma , Walid Chaabene , Naveed Janvekar

Recent advancements in Large Language Models (LLMs) have significantly enhanced the capabilities of AI-Powered Search Engines (AIPSEs), offering precise and efficient responses by integrating external databases with pre-existing knowledge.…

密码学与安全 · 计算机科学 2025-06-16 Zeren Luo , Zifan Peng , Yule Liu , Zhen Sun , Mingchen Li , Jingyi Zheng , Xinlei He

We present REMARK-LLM, a novel efficient, and robust watermarking framework designed for texts generated by large language models (LLMs). Synthesizing human-like content using LLMs necessitates vast computational resources and extensive…

密码学与安全 · 计算机科学 2024-04-09 Ruisi Zhang , Shehzeen Samarah Hussain , Paarth Neekhara , Farinaz Koushanfar

The emerging success of large language models (LLMs) heavily relies on collecting abundant training data from external (untrusted) sources. Despite substantial efforts devoted to data cleaning and curation, well-constructed LLMs have been…

计算与语言 · 计算机科学 2024-02-26 Tianlin Li , Qian Liu , Tianyu Pang , Chao Du , Qing Guo , Yang Liu , Min Lin

Large Language Models (LLMs) are being integrated into applications such as chatbots or email assistants. To prevent improper responses, safety mechanisms, such as Reinforcement Learning from Human Feedback (RLHF), are implemented in them.…

密码学与安全 · 计算机科学 2026-05-01 Matteo Gioele Collu , Tom Janssen-Groesbeek , Stefanos Koffas , Mauro Conti , Stjepan Picek

Research shows that phishing emails often utilize persuasion techniques, such as social proof, liking, consistency, authority, scarcity, and reciprocity to gain trust to obtain sensitive information or maliciously infect devices. The link…

密码学与安全 · 计算机科学 2024-12-25 Kalam Khadka , Abu Barkat Ullah , Wanli Ma , Elisa Martinez Marroquin

Large Language Models (LLMs) are deployed in interactive contexts with direct user engagement, such as chatbots and writing assistants. These deployments are vulnerable to prompt injection and jailbreaking (collectively, prompt hacking), in…

Large Language Models (LLMs) are increasingly deployed in sensitive domains including healthcare, legal services, and confidential communications, where privacy is paramount. This paper introduces Whisper Leak, a side-channel attack that…

密码学与安全 · 计算机科学 2025-11-06 Geoff McDonald , Jonathan Bar Or

Counterspeech is a key strategy against harmful online content, but scaling expert-driven efforts is challenging. Large Language Models (LLMs) present a potential solution, though their use in countering conspiracy theories is…

计算与语言 · 计算机科学 2025-08-04 Mareike Lisker , Christina Gottschalk , Helena Mihaljević

With the rise of sophisticated scam websites that exploit human psychological vulnerabilities, distinguishing between legitimate and scam websites has become increasingly challenging. This paper presents ScamFerret, an innovative agent…

密码学与安全 · 计算机科学 2025-02-17 Hiroki Nakano , Takashi Koide , Daiki Chiba

Large language models (LLMs) are complex artificial intelligence systems capable of understanding, generating and translating human language. They learn language patterns by analyzing large amounts of text data, allowing them to perform…

密码学与安全 · 计算机科学 2024-03-15 Biwei Yan , Kun Li , Minghui Xu , Yueyan Dong , Yue Zhang , Zhaochun Ren , Xiuzhen Cheng

Warning: This article includes red-teaming experiments, which contain examples of compromised LLM responses that may be offensive or upsetting. Large Language Models (LLMs) have the potential to create harmful content, such as generating…

密码学与安全 · 计算机科学 2026-03-18 Ali Raza , Gurang Gupta , Nikolay Matyunin , Jibesh Patra

Identifying deceptive content like phishing emails demands sophisticated cognitive processes that combine pattern recognition, confidence assessment, and contextual analysis. This research examines how human cognition and machine learning…

人工智能 · 计算机科学 2026-01-09 Paras Jain , Khushi Dhar , Olyemi E. Amujo , Esa M. Rantanen

The risks derived from large language models (LLMs) generating deceptive and damaging content have been the subject of considerable research, but even safe generations can lead to problematic downstream impacts. In our study, we shift the…

计算与语言 · 计算机科学 2024-02-22 Federico Bianchi , James Zou

We present "Bot Wars," a framework using Large Language Models (LLMs) scam-baiters to counter phone scams through simulated adversarial dialogues. Our key contribution is a formal foundation for strategy emergence through chain-of-thought…

计算与语言 · 计算机科学 2025-03-11 Nardine Basta , Conor Atkins , Dali Kaafar

Growing applications of large language models (LLMs) trained by a third party raise serious concerns on the security vulnerability of LLMs.It has been demonstrated that malicious actors can covertly exploit these vulnerabilities in LLMs…

密码学与安全 · 计算机科学 2023-12-11 Shuli Jiang , Swanand Ravindra Kadhe , Yi Zhou , Ling Cai , Nathalie Baracaldo

As we increasingly depend on software systems, the consequences of breaches in the software supply chain become more severe. High-profile cyber attacks like those on SolarWinds and ShadowHammer have resulted in significant financial and…

密码学与安全 · 计算机科学 2023-08-10 Tanmay Singla , Dharun Anandayuvaraj , Kelechi G. Kalu , Taylor R. Schorlemmer , James C. Davis

Large language models (LLMs) have demonstrated remarkable capabilities across a broad spectrum of tasks. They have attracted significant attention and been deployed in numerous downstream applications. Nevertheless, akin to a double-edged…

计算与语言 · 计算机科学 2023-11-28 Zishan Guo , Renren Jin , Chuang Liu , Yufei Huang , Dan Shi , Supryadi , Linhao Yu , Yan Liu , Jiaxuan Li , Bojian Xiong , Deyi Xiong

Large Language Models have become critical to modern software development, but their reliance on uncurated web-scale datasets for training introduces a significant security risk: the absorption and reproduction of malicious content. This…

密码学与安全 · 计算机科学 2026-05-12 Zhiyang Chen , Tara Saba , Xun Deng , Xujie Si , Fan Long

Phishing is one of the most prevalent and expensive types of cybercrime faced by organizations and individuals worldwide. Most prior research has focused on various technical features and traditional representations of text to characterize…

密码学与安全 · 计算机科学 2024-08-20 Tarini Saka , Rachiyta Jain , Kami Vaniea , Nadin Kökciyan
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