欺骗性网络钓鱼检测系统:基于数据挖掘方法的即时通讯语音和文本信息

M. M. Ali, L. Rajamani
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引用次数: 14

摘要

欺骗性网络钓鱼是即时通讯工具中的主要问题,许多敏感和个人信息通过社会工程文本消息泄露,对此提出了解决方案[2],但是,利用语音聊天技术检测即时通讯软件中的网络钓鱼的研究尚未完成,这是开展这项工作的激励因素,并提出了利用关联规则挖掘(ARM)技术和语音识别系统相结合的数据挖掘方法来解决即时通讯软件(IM)中的隐私问题。在FFT频谱分析和LPC系数方法的帮助下,从语音中识别单词。当今网络犯罪分子将语音聊天技术与文本信息协同使用,或者在IM中使用其中之一,并包装个人信息,导致隐私受到威胁和阻碍。为了保护用户的隐私,我们开发并试验了IM中的反网络钓鱼检测系统(APD),以协同检测文本和音频的欺骗性网络钓鱼。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deceptive phishing detection system: From audio and text messages in Instant Messengers using Data Mining approach
Deceptive Phishing is the major problem in Instant Messengers, much of sensitive and personal information, disclosed through socio-engineered text messages for which solution is proposed[2] but, detection of phishing through voice chatting technique in Instant Messengers is not yet done which is the motivating factor to carry out the work and solution to address this problem of privacy in Instant Messengers (IM) is proposed using Association Rule Mining (ARM) technique a Data Mining approach integrated with Speech Recognition system. Words are recognized from speech with the help of FFT spectrum analysis and LPC coefficients methodologies. Online criminal's now-a-days adapted voice chatting technique along with text messages collaboratively or either of them in IM's and wraps out personal information leads to threat and hindrance for privacy. In order to focus on privacy preserving we developed and experimented Anti Phishing Detection system (APD) in IM's to detect deceptive phishing for text and audio collaboratively.
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