Why The Future of Cybersecurity Needs Both Humans and AI Working Together
As we look to the future of cybersecurity, we must consider the recent past and understand what the pandemic has taught us about our security needs.
Many cybersecurity platforms proved inadequate when a large percentage of the world’s workforce abruptly shifted to remote work in the Spring of 2020. Companies found themselves fighting against the limitations of their own cybersecurity platforms.
Yesterday’s Cybersecurity Approach Is Inadequate Against Today’s Threats
Modern systems enhanced with self-learning AI capabilities have fared best in the face of the pandemic’s impact on networking.
For others, immediate, manual interventions were the only thing standing between enterprise security and the bad actors who had been standing by waiting for a global event of this scale.
They swooped in almost immediately, targeting governments and hospital systems, and a wide swath of commercial enterprises. Everything from ransomware to DDOS to phishing schemes ramped up right alongside the upheaval so many companies were experiencing in the early days of the pandemic.
Many inadequate systems were enhanced with some form of AI, but relied on what employees had taught them. No one could have predicted such a dramatic shift in behavior, but systems that were trained to alert on unexpected behavior like a sudden rush of remote connections floundered.
Security analysts were unable to keep up with the constant stream of false positives. Threat hunting is time-consuming for teams under typical network conditions. The pandemic exacerbated this challenge.
Bad actors had been standing by, waiting for an event that would impact thousands of global networks all at once.
Cybersecurity of the Future Will Rely on Better AI
As companies examine their security systems, the question they’ll need to answer isn’t “Should we bring AI on board,” but rather “What kind and how much AI do we need?”
A recent WhiteHat Security survey revealed that more than 70 percent of respondents cited AI-based tools as contributing to more efficiency. More than 55 percent of mundane tasks have been replaced by AI, freeing up analysts for other departmental tasks.
Still, not all enterprises or employees are excited by the prospect of bringing more AI on board, especially AI that requires less intervention. This is an understandable response — employees worry that AI will replace their jobs.
AI Alone Isn’t the Answer
Multitalented human employees are not only part of the self-learning AI solution, they are integral. Respondents to the WhiteHat survey cited the importance of creativity and experience as critical for adequate security.
A combined approach appears to be the likeliest reliable cybersecurity approach going forward. Security teams that incorporate AI to handle mundane tasks and reduce overarching issues like false positives and focus on the human element will fare better.
Third-wave self-supervised AI platforms handle unusual network activity with more nuance. When the shift to remote work hit these networks, self-learning AI quickly reestablished a “new normal.” Instead of triggering hundreds or thousands of false positives, these systems rapidly adjusted and started looking for behavior that didn’t mean the new frame of reference.
In the meantime, security analysts could focus on shoring up vulnerabilities created by the pandemic in other ways.
Human Qualities Are Critical for Cybersecurity Success
Creative problem solving has never been as crucial for teams facing the unprecedented challenges of today. Qualities like intuition and experience-based decision-making are invaluable, and even the most advanced AI cannot replace them.
What machines can do is augment the important, nuanced work that human security professionals do. Talented security analysts waste time sifting through false positives and handling many other mundane tasks while keeping a constant eye on the network.
Tools that reduce manual interventions also reduce errors and improve employee satisfaction.
Machines will never be able to entirely replicate or take over the work security professionals do, so it’s essential for companies to look for security platforms that underscore the talents of human security analysts. Security teams that view AI as one part of a complete, multi-faceted approach will benefit the most from these improvements.
Is It Time to Evolve Your Security Approach?
Future-facing companies must evaluate their ability to weather the cybersecurity emergencies of tomorrow. Typical AI-enhanced platforms can help but are fundamentally limited. Without a complete understanding of your network’s baseline and how it can change in response to unexpected events, no security platform can detect every threat.
MixMode’s third-wave AI solution develops an accurate, evolving baseline of network behavior and then responds smartly to aberrations and unexpected network behavior.
Reach out to our client service team today to set up a demo.
MixMode Articles You Might Like:
Our Q2 Top Cybersecurity Insights
NTA and NDR: The Missing Piece
The Problem with Relying on Log Data for Cybersecurity
The (Recent) History of Self-Supervised Learning
Guide: The Next Generation SOC Tool Stack – The Convergence of SIEM, NDR and NTA
Redefining the Definition of “Baseline” in Cybersecurity
MixMode CTO Responds to Self-Supervised AI Hopes
Why Training Matters – And How Adversarial AI Takes Advantage of It
*** This is a Security Bloggers Network syndicated blog from MixMode authored by Ana Mezic. Read the original post at: https://mixmode.ai/blog/why-the-future-of-cybersecurity-needs-both-humans-and-ai-working-together/