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The Future Remains Data-Driven

By Erez Tadmor, Tufin's Network Security Evangelist

In today's intricate enterprise environments, the complexity of managing data and ensuring cybersecurity is a constant challenge. Each new device and application introduced adds to the variables that data and analytics professionals must consider, making it increasingly difficult to understand and defend against potential threats. Despite years of discussions about alert fatigue, substantial progress has remained elusive. However, the dawn of 2024 promises a brighter future for data and analytics professionals. Advanced tools, automation and AI technologies are set to revolutionize the way we manage attack surfaces and understand data points.

Advanced Tools for Managing Complexity

The complexity of modern enterprise environments has reached unprecedented levels. With each new device and application integrated into the corporate infrastructure, the attack surface grows, making it harder to understand and defend against potential threats. This expanded attack surface has brought back into vogue the phenomenon known as alert fatigue, a state where the sheer volume of alerts and data becomes overwhelming, rendering them less effective in identifying real threats.

Alert fatigue has always been a problem for security professionals, but before the expansion of connected device and cloud use in the enterprise, there seemed to be a period of time where it was at least more controlled. That has changed as today's enterprise networks grow every day in size and complexity. Because of the sheer volume of inputs, it has become difficult once again for security professionals to know what data to pay attention to and what to deprioritize.

In 2024, the tide is set to turn. Advanced tools, powered by artificial intelligence (AI) and machine learning technologies, will play a pivotal role in providing security professionals with the force multiplier to intelligently understand and manage their attack surfaces. These AI-based tools will not only streamline the detection of anomalies and threats but also offer the data and analysis needed to establish proactivity, helping organizations stay one step ahead of potential issues.

Moreover, machine learning algorithms will enable security tools to adapt and learn from data patterns, continually improving their threat detection accuracy. These advanced systems will enable organizations to respond rapidly to evolving threats, reducing the risk of data breaches and cyberattacks.

Continuous Compliance

Networks are growing increasingly intricate and segmented, particularly in hybrid cloud environments. The absence of a centralized view of security and connectivity may result in misconfigurations, amplifying the risk of network vulnerabilities and potential outages. Without the insights that this visibility creates, there is little to no chance of a security team member being able to analyze and identify what the reason for an outage may be.

Next year, we will see organizations begin to adhere more closely to the idea of continuous compliance. Meeting compliance requirements - and proving it to auditors - takes up an inordinate amount of time for security and IT teams. The amount of time spent proving compliance will come into question, and teams will decide it makes more sense to strive for a state of continuous compliance. But accessing and managing this data is easier said than done, especially given the growing scale and complexity of enterprise networks and the data they produce.

To continually align with both industry regulations and internal standards, businesses need to embrace automation. A centralized and automated solution can help teams oversee, regulate, analyze and troubleshoot misconfigurations across a spectrum of devices, including firewalls, routers, switches, SDNs, SD-WAN, public clouds, and containers. With an automated solution, the data insights are presented, indicating any potential problems and the potential solutions, enabling teams to act quickly and regularly to maintain compliance.

Collaboration is Necessary

As enterprises have evolved and moved to the cloud, there have been gaps between the responsibilities and efforts of network and cloud security teams. Critical data has gone unnoticed, and potentially important alerts or issues un-analyzed. This will finally come to a head in 2024, as many companies realize that the communication and collaboration gaps between different departments are holding them back, and potentially have become the direct cause for security issues falling through the cracks and becoming major problems.

To solve this, security data will need to be de-siloed and shared by all parties. A new approach of collaboration is necessary, where information is shared and all are responsible for understanding what it means to the organization - and what should be done in response. This approach will be further embraced with the necessity to comply with PCI 4 regulation and the Cybersecurity Risk Management, Strategy, Governance, and Incident Disclosure set forth by the SEC. Automated tools and AI technologies will prove critical at closing the gap between network and cloud security analysts, fostering collaboration and improving security readiness.

Making Security Data Work

2024 will be a pivotal year for enhancing cybersecurity measures within organizations. The incorporation of AI and machine learning technologies will empower security professionals and revolutionize threat detection and mitigation, while collaboration across the board will lead to better analysis of security data and improved preparedness to respond to threats or outages.

By staying proactive, embracing these trends, and adapting to the changing landscape, security professionals can position themselves and their organizations for success and make more data-driven security decisions in the next year.

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ABOUT THE AUTHOR

Erez Tadmor holds a two-decade career in the ever-evolving information security field, marked by his diverse background in managing various product portfolios and verticals. His expertise spans Cloud and network security, Automation & Orchestration, IAM, and fraud detection and prevention. He's playing a pivotal role in guiding Fortune 500 enterprises through digital transformations, focusing on security and compliance programs. As Tufin's Network Security Evangelist, he bridges customers and the marketing and product teams, educating stakeholders on network security technologies, cyber security best practices and Tufin's solutions. Erez holds a track record of strong leadership in Product Management, enterprise cybersecurity, and product strategy development, honed through work with startups and multinationals. His core strengths include new product launches, go-to-market strategies, and product lifecycle management.