Who Views Your Ad? Bot or Human?

May 15, 2019

Programmed by hackers to perform certain tasks on specific sites and to mimic human behaviour on digital platforms, spambots, string of malicious code, are nowadays able to leave comments on forum, to fill in the information to subscription form, to click on an advertisement, etc.

The problem when it comes to advertisement is that the cost and effectiveness of digital advertising is determined by the number of views, clicks and impressions. Thus, the budget of advertisers can inflate and the effectiveness of advertising campaigns can hinder when an online banner is played again and again by a spambot.

Although ad frauds are constantly trained to find new ways to fool the system, technology is also evolving to tackle this issue. REM and Passive Monitoring are two such examples.

What is REM?

REM, Runtime Execution Monitoring, is an analysis software on internet to detect spambot and fake engagement. While human behaviour is marred by irregularity (people randomly move their cursors when browsing websites and often complete online forms slowly), Bots on there side usually act concisely, with an intention.This irregularity of actions is considered natural on REM and repetitive bot activity is not treated as a genuine response.

However, bots acting more humanly are conceived every day, creating a limitless challenge for the digital world and the REM’s verification system.

How does Passive Monitoring work?

Passive Monitoring is another ad fraud recognition and standardized user action software. It requires a device on the network to collect statistics for the analysis of site performance.

By examining the traffic flow on a website, Passive Monitoring can determine when multiple users perform similar or repeated behaviour within a certain period of time; it can then be concluded that users performing such similar or exact actions are bots following the same command.

Thus, this resolves the problem of distinguishing human-like click frauds from genuine user performance.

Fraud prevention



In order to filter out spam bot traffic and to monitor any deliberate user action, Noiz Network bank on the above technology (both REM and Passive Monitoring). To prevent spam activity, the difference in engagement between bots and humans within NOIZ community.

In the NOIZ ecosystem — consisting of consumers, advertisers, publishers and social impact organisations — investigative software can keep track of the NOIZ credit flow.

Thus, user activity is closely monitored to prevent spam bot activity from affecting the efficacy of ads or dirtying data for publishers. The goal is to revamp the ecosystem of digital advertising and eliminate fraud traffic.

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