TFD: TELECOM FRAUD DETECTION USING CONSOLIDATED WEIGHTED REPUTATION ALGORITHM

J. Anbarasi, V. Radha
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Abstract

Noisy phone calls are aggravating and distracting, as well as frustrating. They may be classed as 'nuisance', 'emergency', 'random', and 'unsolicited' calls. Users have no inherent privileges on the internet; rather, their personalities are produced without any arrangement or evidence of involvement. It costs the U.S. communications company $8 billion per year to avoid call spam on the phone grid. Between January 2014 and June 2018, the FTC (Federal Trade Commission) received over 22 million reports of fraudulent and illegal telemarketing calls. Nowadays, the mobile network is used to issue automatic phone calls such as robocalls. Since it operates on text, we struggle with the following: What tactics and methods do we use to combat spam? Telephone TFD (Telecom Fraud Detection) here is discussed first. Concerning spam, we advanced our proposal by proposing a targeted traffic detection using a single weighted credibility algorithm with appropriate weighting criteria.
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Tfd:基于合并加权信誉算法的电信欺诈检测
嘈杂的电话会让人恼火、分心,也会让人沮丧。这些电话可分为“滋扰电话”、“紧急电话”、“随机电话”和“非应邀电话”。用户在互联网上没有固有的特权;相反,他们的个性是在没有任何安排或参与证据的情况下产生的。为了避免电话网络上的垃圾电话,美国通信公司每年要花费80亿美元。2014年1月至2018年6月,美国联邦贸易委员会共收到2200多万起欺诈和非法电话营销举报。现在,移动网络被用来发出自动电话,如机器人电话。由于它是在文本上操作的,我们在以下方面遇到了困难:我们使用什么策略和方法来打击垃圾邮件?这里首先讨论电话TFD(电信欺诈检测)。对于垃圾邮件,我们提出了一种针对性的流量检测方法,该方法使用具有适当加权标准的单一加权可信度算法。
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来源期刊
Information Technology in Industry
Information Technology in Industry COMPUTER SCIENCE, SOFTWARE ENGINEERING-
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