New Online Safety App Seeks to Detect Child Sexual Abuse

Online Safety

Salus App Aims to Use Tech to Promote Child Online Safety

While the world wide web provides people with many great opportunities, there are also many concerns when it comes to online safety. While there are many negative aspects of the internet that need to be addressed, one of the most critical involves the online safety of children. Issues like human trafficking of children, sexual exploitation, and child pornography are some of the most severe aspects that organizations are working to address. A new online safety app seeks to help address child sexual abuse through the use of machine learning. 

Background Behind the Salus Online Safety App

The app at the center of today’s discussion was named Salus, after the Roman goddess. Salus was known as the goddess of security, prosperity, and well-being. It is the focus on well-being and safety that led the project to take on this name as the app’s mission is to better strengthen online safety and protect the well-being of children. 

The Salus app was created due to an extensive partnership. Funded by the European Commission to the tune of £1.8 million, the project is being led by a university hospital in Germany and created by a tech firm in the United Kingdom. The project is also being supported by the Internet Watch Foundation, which is currently Europe’s largest hotline dedicated to removing child sexual abuse images and videos. 

The large-scale nature of collaboration on this project reveals the importance of this issue across the global community. For example, the Internet Watch Foundation itself acted to remove over 255,000 URLs that contained child sexual abuse material from the internet last year, illustrating the extensive gravity of this problem. 

Online Safety

How Does the Salus App Seek to Address Online Safety? 

At its core, the goal of this particular project is to detect child abuse content in real time. This would allow the content to be immediately blocked to prevent the user from accessing it. SafeToNet, the UK company charged with creating the app, utilized machine learning techniques in order to accomplish this goal. 

Machine learning is a branch of artificial intelligence that seeks to utilize large sets of data in order to help computers “learn” to interpret new data on their own. A popular form of machine learning is classification algorithms, where computers are able to learn how to categorize different photos or videos based on prior knowledge. This is likely the technology at the root of this project which will enable the app to determine if images or videos contain child sexual abuse. 

With the Salus app installed on a computer, it would screen images for illegal content and prevent them from being displayed on the screen if they are classified as child sexual exploitation. The thought behind this particular process is that the app could be required to be installed on devices of those at risk of accessing this type of content. The app would then detect and block child sexual exploitation, reducing the demand for this type of online content, which could serve to reduce the demand for child trafficking. 

Online Safety

Salus Online Safety App Based on Research

While there are many online safety apps available, the Salus app provides a unique frame of reference for addressing the issue of child exploitation. The design of the app is also rooted in research that seeks to inform its ultimate effectiveness. 

Specifically, researchers have explored the reasons why offenders are viewing child pornography as well as what can be useful in helping them stop. By basing the app’s creation on research, experts seek to strengthen its ability to serve as an effective tool aimed at increasing online safety by reducing the demand for exploitative content. 

The developers of the app do not see Salus as a solution on its own. Rather, they view it as a tool that can work alongside existing efforts for addressing child pornography online. This would yield a more layered approach to promoting online safety and reducing the risk of spreading child sexual abuse through the internet. 

Participants in this program cite widespread collaboration as an important means of strengthening the solution. The project aims to utilize volunteers to test the app’s effectiveness. By training and testing the app, machine learning techniques can be refined, making the app more effective. 

Salus App Could Play an Important Role in Reducing Child Sexual Abuse

While the app is still being tested, its creators believe this software could play a vital role in lowering the demand for child pornography. It also has the potential of serving as a useful tool to help the rehabilitation of prior offenders. As the app enters the marketplace, it will be interesting to keep tabs on its effectiveness over the next few years.