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The cybersecurity landscape is under pressure to enhance technology and defenses as cyberthreats increasingly diversify the ways in which they strategically incapacitate organizations. Cyberattacks are on the rise each year, and the cost to unprepared businesses is only increasing.
A data breach can damage an organization’s wallet as well as its reputation. Therefore, it is imperative for businesses to expand their operations when it comes to data protection, and artificial intelligence (AI) could be the answer needed to detect and prevent threats before cyber operations centers can do damage. there is.
no industry is safe
Cyberattacks are not limited to one sector. As we’ve seen over the past year, no industry is safe. In the healthcare industry alone, 20 million Americans are at risk of “dangerous” healthcare following the CommonSpirit Health cyberattack in October. A massive IT breach caused by a ransomware hack affected systems running 140 US hospitals and his over 1,000 care sites. In other words, patients in 21 states may still be at risk of receiving incomplete care. Cyber actors are increasingly targeting hospitals and healthcare providers to gain access to sensitive patient data, with significant consequences for patients, hospitals and other national healthcare systems around the world. increase. These attackers have no remorse. Therefore, it is very important for organizations to keep their cybersecurity up to date. Especially when lives can be in danger.
Similarly for carriers, governments around the world are starting to crack down on the adoption of cybersecurity regulations by all mobile and broadband providers. To protect broadband and mobile networks from potential threats, CSPs should pay more attention to cybersecurity. Otherwise, he risks fines of up to $100,000 per day for failing to comply. As governments recognize the importance of investing in the latest technologies for data protection, businesses across all sectors will benefit from either updating their systems or risking sound payments. I can.
It is predicted that by 2025, cybercrime could cost the world over $10 trillion annually. This estimate is based on a growing number of factors including data damage or destruction, theft of intellectual property and financial assets, business disruption and reputational damage after an attack. Organizations should prioritize identifying and preventing complex cyber-attacks before they occur. This is not possible with legacy systems.
Challenges of legacy software
Enterprises that rely on traditional reactive security monitoring software (such as legacy SIEM solutions) have access to basic analytics and log data aggregation to detect cyber incidents. Unfortunately this can be limiting. This is because most solutions only focus on alerting mechanisms that trigger when known attack patterns occur. Due to the dynamically changing threat landscape, legacy systems often do not provide enough organization-wide visibility and scalability to truly defend against attacks as they occur.
Cybercriminals have access to the best software available. This means that even the most advanced security software can be bypassed. Criminals can hide their activities in hundreds of gigabytes of data collected from various log sources. This is because legacy systems do not have the ability to learn and distinguish them from typical user behavior. When alerts are triggered, these are often false positives and real threats go unnoticed and completely ignored.
Therefore, updating legacy systems is essential. By investing in the latest technologies, such as cloud-based AI and machine learning (ML)-based threat detection, IT managers and Security Operations Center (SOC) analysts can automate their actions in cyber threat monitoring and prevention. You can be much more proactive by anticipating of highly complex IT networks and systems.
Proactively detect threats
Companies that maintain legacy cybersecurity systems, rather than updating and modernizing their technology, will become increasingly ineffective at preventing threats. Relying on being able to fix the problem after the damage is done only allows attacks that would otherwise be preventable to be carried out.
With the right AI systems in place, next-generation SIEM solutions can not only detect cyber threats at the impact stage, but also contextualize and predict information. Additionally, multiple AI models can be used in sequence to optimize threat detection output and detect early signs of attack. By integrating automated data and web scrapers to incorporate the latest contextual threat intelligence for your organization, AI-driven solutions can help you discover vulnerabilities, compromised credentials, malicious domains in context, and Provides near real-time adjustments that reflect actual exposure from risk exposure. of any client. Additionally, you can prioritize and tailor alerts based on their potential impact on your organization, putting the most serious alerts at the top of your agenda.
Incorporating AI into threat detection is critical
Predictive threat detection using the potential of AI is critical to avoiding the cost of potentially damaging attacks for businesses. Dynamically changing threats must be addressed using similarly complex and reactive defense systems. This is something businesses need to do quickly to ensure customer data is safe and protected. AI solutions also help business leaders maintain peace of mind, focus and worry less about the threat of disruptive cyberattacks, and instead focus more time and money on business development.
Ralph Chammah is CEO and Miro Pihkanen is CSO. OwlGaze is a company that specializes in cybersecurity software and advisory and offers a proprietary AI software called Blacklight.
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