COPS:用于实时检测钓鱼网站的紧凑型设备管道

Harichandana B S S, Sumit Kumar, Manjunath B. Ujjinakoppa, Barath Raj Kandur Raja
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引用次数: 0

摘要

智能手机已成为我们日常生活中不可或缺的工具,从通讯到网上购物,几乎无所不能。然而,随着使用率的提高,针对移动设备的网络犯罪也在急剧上升。尤其是 Smishing 攻击,近年来显著增加。由于犯罪者每天都在创建新的欺骗性网站,而网站的平均生命周期不到 15 个小时,这进一步加剧了这一问题。这使得保存恶意 URL 数据库的标准做法无法奏效。为此,我们提出了一种新颖的设备管道:COPS 可智能识别欺诈信息和 URL 的特征,从而实时向用户发出警报。COPS 是一个轻量级的管道,它的检测模块基于离散变异自动编码器(Disentangled Variational Autoencoder),大小为 3.46MB,可用于网络钓鱼和 URL 钓鱼检测,我们在开放数据集上对其进行了基准测试。在这两项任务中,我们的准确率分别达到了 98.15% 和 99.5%,假阴性率和假阳性率仅为 0.037 和 0.015,性能优于之前的研究成果,而且还能确保在资源有限的设备上发出实时警报。
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COPS: A Compact On-Device Pipeline for Real-Time Smishing Detection
Smartphones have become indispensable in our daily lives and can do almost everything, from communication to online shopping. However, with the increased usage, cybercrime aimed at mobile devices is rocketing. Smishing attacks, in particular, have observed a significant upsurge in recent years. This problem is further exacerbated by the perpetrator creating new deceptive websites daily, with an average life cycle of under 15 hours. This renders the standard practice of keeping a database of malicious URLs ineffective. To this end, we propose a novel on-device pipeline: COPS that intelligently identifies features of fraudulent messages and URLs to alert the user in real-time. COPS is a lightweight pipeline with a detection module based on the Disentangled Variational Autoencoder of size 3.46MB for smishing and URL phishing detection, and we benchmark it on open datasets. We achieve an accuracy of 98.15% and 99.5%, respectively, for both tasks, with a false negative and false positive rate of a mere 0.037 and 0.015, outperforming previous works with the added advantage of ensuring real-time alerts on resource-constrained devices.
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