Joining forces against harassing software begins

In order to protect internet users against harassment software and raise awareness, 10 different institutions came together and launched a global initiative called “Coalition Against Stalkerware”. The organization will also support victims of cyber attacks, which is one of the biggest threats of our time. The initiative, which was established to raise awareness of users, raise awareness in this area and provide expert support to victims, gathers stakeholders in other fields such as non-profit organizations, related sectors and law enforcement agencies under the same umbrella.

What is harassment software?

Harassment software (stalkerware), which can be used to monitor people’s private lives, is encountered in cases of domestic violence and covert stalking.. Abusers who install these applications on the devices of their targets can access messages, photos, social media shares, location, audio and camera recordings.. In some cases, they can also do this in real time.. These programs run in the background, without the victim’s knowledge or consent.

The problem of ‘harassment software’ has been growing steadily over the past few years.. The number of victims is increasing at an alarming rate. Nonprofits report a steady increase in requests for help from victims facing this problem.. According to the information obtained by Kaspersky, the number of users who encountered harassment software increased from 27,798 in 2018 to 37,532 in 2019, an increase of 35 percent.. In addition, the threat range of harassment software has also expanded.. Kaspersky detected 380 different harassment software in 2019. This number is 31 percent more than a year ago.

Until now, no common standard definition or detection criteria for harassment software has been determined.. This was a factor that made it difficult for the IT security industry to raise this issue.. The founding members of the Force Against Harassment Software took an important step towards combating these programs, creating a neat definition and consensus on detection criteria.

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