AI can be leveraged for cyberattacks

Security is moving higher on the agendas of boards of directors. At a time when most budgets are shrinking, worldwide security spending is expected to grow 8.1% annually and hit $174.7 billion by 2024, according to IDC. There's a good reason for this. Major data breaches and crippling ransomware attacks can rise to the level of natural disasters - often bringing business to a standstill and damaging the brand, customer loyalty, partner relationships and more. It’s startling, but the projected cost of cybercrime - an estimated $6 trillion in 2021 - represents “the greatest transfer of economic wealth in history,” according to Cybersecurity Ventures.

It is time to leverage cyber resilience into your IT security, operations and culture. Whether you need help migrating to the cloud, protecting data with a Zero Trust strategy or managing your security operations center, it is time for the tech companies to handle security so you can focus on your business. Much of today’s security isn’t built to face modern challenges. It’s too slow, and reactive to threats rather than proactive. Threats grow more complex every day, and existing cybersecurity offerings struggle to keep up. There’s a steady stream of new malware created every single day.

There is a dramatic surge in ransomware attacks that has targeted critical national infrastructure. Protecting the organization and users against advanced targeted threats such as malware, phishing, and data exfiltration becomes exponentially more difficult. Check Point Research (CPR) warns of potential ransomware attacks, as it sees samples of Emotet fast-spreading via Trickbot.

Emotet is a strong indicator of future ransomware attacks, as the malware provides ransomware gangs with a backdoor into compromised machines. CPR spotted more than 140,000 victims affected by Trickbot all around the globe since the botnet takedown, including organizations and individuals. Trickbot affected 149 countries in total, which marks more than 75% of all the countries in the world. It’s important to note that security isn’t just about patching and protecting IT systems anymore.

Not all machine learning is created equally. Deep learning neural networks have consistently out-performed other forms of machine learning when it comes to detecting malware. Smarter than other forms of machine learning, deep learning automatically finds the best combination of inputs for detection. This makes it capable of detecting stealthy malware other engines would miss.