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Technological developments in recent years have had profound impacts on our daily lives. They have allowed us to create Smart Factories and personal voice assistants and even work remotely during a pandemic. They have also widened the surface for cyberattacks, resulting in an urgent need to improve cybersecurity across many industries. Now, the demand is growing for automated and AI-based cybersecurity tools that can fill the gaps in human capabilities. These revolutionary tools will lead cybersecurity into a new era, shifting the focus from reactive detection to proactive prediction and prevention.
This research focused on four relevant areas for cybersecurity automation and worked with PAC (Teknowlogy Group) to track the growing investments in:
BIG-5 (USA, China, India, Brazil, and the UK)
EUROPE-5 (Germany, Italy, France, Belgium, and the Netherlands)
Development teams in recent years have united with both operations and security teams to form DevSecOps, an approach with an emphasis on integrating security measures throughout the entire application development lifecycle.
Automating testing at every step is crucial for decreasing the number of vulnerabilities in an application, and many testing and analysis tools are further integrating artificial intelligence to increase their accuracy or capabilities.
As the average number of endpoints in many systems has increased in recent years, companies have a vested interest in discovering more efficient and comprehensive ways of protecting themselves.
Tools like Endpoint detection and response (EDR) and Extended detection and response (XDR) use automation and AI to detect, record, and respond to threats against endpoints.
An impressive range of abilities offered by IoT devices has led to their introduction into many different sectors, from Smart Factories and Connected Cars to in-home voice assistants and security systems.
Automation and AI tools have the potential to assess the trustworthiness of IoT devices and prevent security incidents, avoiding the possibility that a single vulnerability could shut down an entire infrastructure.
Threats to data security (i.e., data breaches) can result in a multitude of consequences for organizations, ranging from legal ramifications to damaged brand reputation.
Locating and classifying all data in a complex network so that it can be protected is a daunting task. Automation and AI can play an integral role in optimizing data discovery, classification, encryption, tokenization, and data loss prevention tools.
Cybersecurity sectors are becoming increasingly complex and interconnected. Current and emerging threats may be better addressed with well-implemented automated processes and artificial intelligence technologies. Though it is not simple to create a foolproof cybersecurity strategy, taking advantage of AI technologies is one way businesses can attain better privacy and protection for applications, endpoints, IoT devices, and sensitive data.