A new AI-based tool to detect DDoS attacks

Protect Your Online Presence From DDoS Attacks

Cybercriminals are becoming increasingly sophisticated in the ways they disrupt online services, access sensitive data, and crash internet users' devices. One of the most common cyber-attacks today is the Distributed Denial of Service (DDoS) attack.

A DDoS attack is when a malicious actor floods a network with requests or data packets, overloading it and rendering it incapable of servicing other requests. This type of attack is meant to disrupt the services of a website or server, and can cause a website to be slow or unavailable.

How to Protect Yourself from a DDoS Attack

There are a few steps you can take to protect yourself from a DDoS attack:

• Monitor your network for signs of an attack.
• Set up a firewall that can detect and filter out malicious traffic.
• Use a web application firewall to thwart malicious attacks.
• Keep your software and systems up-to-date.

By taking these precautions, you can prevent a DDoS attack from disrupting your online services and access to sensitive data.

Conclusion

DDoS attacks are a serious threat to the security of any online presence. By taking the proper measures and understanding the risk, you can protect yourself from these malicious cyber-attacks.

https://www.lifetechnology.com/blogs/life-technology-technology-news/a-new-ai-based-tool-to-detect-ddos-attacks

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Predicting city traffic using a machine learning model

Using Machine Learning to Predict City Traffic Activity

A Complexity Science Hub researcher has successfully used a new machine learning model to predict traffic activity in different zones of cities. The model was tested using data from a main car-sharing company in Italy as a proxy for overall city traffic.

Understanding how different urban zones interact and how that influences traffic activity can help avoid traffic jams, and enable more targeted responses from policy makers—such as local expansion of public transportation.

The researcher hopes that this approach to predicting traffic activity can be applied in other cities and regions, and further their understanding of traffic activity in urban zones.

https://www.lifetechnology.com/blogs/life-technology-technology-news/predicting-city-traffic-using-a-machine-learning-model

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