AI + Automation Boost Security Performance
Business leaders are constantly looking for the best ways to succeed by coupling technology with strategy and talent; yet, with the frequency and number of cyber security incidents taking place on the daily, it’s challenging to align business and security strategies.
Thanks to the pandemic, the shift to digitalization accelerated, increasing both opportunities and risks. And everything generates data. So much so in fact, that by 2025, we will generate over 463 exabytes globally each day. To further illustrate just how connected and dependent on Edge and IoT we’ll be, reports show that by 2030, 90% of people over the age of 6 will be digitally active.
And you guessed it, all of this increases the overall attack surface for organizations. More threat vectors emerge, from naive suppliers to disgruntled employees, data exfiltration to DDoS to ransomware. To make matters worse, the issue doesn’t stop with new threat vectors. The other danger lies in the increased level of sophistication and evolution of techniques, procedures, and tactics that cyber attackers are employing, with some already using artificial intelligence and automation to look for weaknesses and deploy greater, more effective attacks.
New vulnerabilities are prompting business leaders to come to terms with their digital footprints and figure out the best approach to deal with the complexities and uncertainties of cybersecurity. To exacerbate the situation, more often than not, security teams are understaffed, overwhelmed, underfunded, and sometimes even underskilled to deal with cybersecurity in the way it deserves.
The new reality demands a new cybersecurity approach
Cyber security should not be reactive, it should be preventive and proactive. Forward-looking organizations must opt for better approaches that include AI-powered threat management, automation, and advanced network visibility to drive improved productivity and insights.
The AI-powered automation approach to cybersecurity directly addresses the main security disruptors that can put your organization at risk, including:
- New and expanding attack vectors
- Adaptive-multi-variant threats
- Lack of visibility from third-party providers
- Lack of insights across different data types
- Automated attacks
- Information overload for disparate data sources
- Cyber skills gap
Combining AI and automation to fight cybercrime
To successfully adopt AI and automation as part of your cybersecurity strategy, you must first learn about how both technologies are being used to support security operations and quantify their impact on cybersecurity performance.
A recent survey shows that the majority of organizations, across the globe and representing most industries, are adopting AI plus automation in their security operations. For instance, we see that 64% of respondents have implemented AI for security and 29% are considering it.
What does that mean for your organization? Well, AI is poised to soon become an universal capability that all organizations must possess. Those who fail to adopt AI plus automation are jeopardizing their security and will most likely struggle to keep up with modern cybersecurity demands, and even suffer at the hands of increasing speed and volume of security events.
Why is AI + automation so effective?
Getting right to the point, AI and automation are a match made in heaven because they advance visibility and productivity: combining accuracy, speed, precision, volume, and efficiency with deep reinforcement learning and other means that iterate and analyze until they get to the best insights.
It’s no wonder over 93% of organizations are interested in adopting AI and automation to boost their security operations. We envision three ways in which AI can disrupt cybersecurity for the better:
- Machine learning helps find patterns, keep track of new assets and services, and improve the way AI models work. For instance, Deep Reinforcement Learning, a subset of Machine Learning, helps with data analysis, scenario modeling, and predicting where new attacks will come from.
- Natural language processing can be used to mine text data sources, improve threat intelligence, and add to knowledge resources.
- Automation can help organize tasks that take a lot of time, speed up response times, and lighten the load on human analysts.
With the help of AI-generated insights, automation tools that are driven by AI can identify threats by user, device, or location and then take the right steps to notify and escalate them while human experts decide how to investigate and fix the problem. When these capabilities are in place, cybersecurity analysts can focus on solving more complicated problems that require human judgment.
Some of the universal benefits of coupling AI and automation include:
- Less time is needed to find, respond to, and get over incidents
- Improved governance and compliance for security.
- Less analyst's tiredness, helping them make better, more informed decisions faster and with fewer mistakes.
- Reduced costs of cybersecurity by at least 15%, highlighting that processes for protection, prevention, detection, and response are more efficient and productive as a whole.
- Cuts to data breach costs by at least 18%, which shows that the detection and response processes are working better.
- Increased return on security investment (ROSI) by 40% or more.
Additionally, implementing automated and AI-driven Edge security at the point of access will protect against zero-day threats, malware, and other vulnerabilities. When pairing AI with automation, companies gain better performance, whether in terms of speed, insights, flexibility, or scalability.
AI can look at both structured and unstructured data sources. It can also combine internal and external data with threat intelligence services and open source intelligence to get a full picture of the situation and the threats in it. This makes it faster for cybersecurity analysts to find, respond to, and recover from incidents.
In the end, AI and automation create better places to work by letting analysts get back to solving hard problems that require human judgment, and in turn, it enhances overall governance and compliance by facilitating more effective and efficient review and remediation protocols. Automation helps with fatigue and improves the ability to make better decisions—faster and virtually error-free.
Using AI-powered automation proactively instead of reactively
As stated earlier, the number of remote employees and cloud-based applications expands the attack surface and creates more entry points for cyber attackers to exploit. For instance, cyber criminals are increasingly using IoT devices to create new threat vectors such as opportunistic phishing or coordinated ransomware campaigns.
Earning the trust of your customers, partners, and stakeholders is crucial, so it’s important to prioritize the proactive reduction of risks, data protection, and intellectual property. AI and automation help break down operational silos and improve visibility across an organization’s digital estate, covering data, users, network, devices, applications, workloads, and even partner interactions within the environment.
With advanced network visibility, you gain understanding of where the most sensitive data resides, who has access, what they’re doing in your digital estate, and which entry points are more vulnerable. AI and automation give you control over data privacy and regulatory compliance, helping you monitor and control access of highly sensitive information.
These are three of the top use cases for AI and automation to help protect and prevent your Edge and IoT infrastructures:
Advanced network visibility. Traditional security policies of organizations don't pick up on unauthorized devices, which makes it hard to find them. AI can learn the context, environment, and behaviors of specific asset types, network services, and endpoints. Companies can then limit access to authorized devices and stop access to unauthorized and unmanaged devices.
Threat intelligence for early detection. AI-powered vulnerability assessments can help find devices that aren't set up right so that administrators can get rid of or fix them. Active vulnerability scanning in operational technology (OT) environments can make systems unstable, but organizations can do passive monitoring with AI and automation. AI can also help prioritize patching vulnerabilities by giving clients information about exploits that can be used as weapons. This lets clients manage vulnerabilities based on the risks they pose.
Automated incident response. Security AI plus automation automates the collection, integration, and analysis of data from hundreds or even thousands of control points by combining system logs, network flows, endpoint data, cloud API calls, and user behaviors. Organizations can add to their existing telemetry with endpoint detection and response across layers, as well as threat intelligence and alerts. These elements let security operations teams fully understand the context of security anomalies, set priorities, and make sure that high-impact threats get enough resources to investigate. Artificial intelligence and deep reinforcement learning can suggest ways to fix problems based on a wide range of factors, such as situational variables, historical precedents, or threat intelligence sources.
To stay up to date with the increasingly sophisticated and devastating threats in today's increasingly digital world, AI plus automation are a must-have for every company that takes cybersecurity seriously. Business leaders should realize that in the fast-paced world of AI, they have to move quickly to stay one step ahead of potential cyber attackers and not just stand by until something happens.
To fight the evolving cyber threats of today and the future, artificial intelligence and automation will need to be integrated into every facet of the ideal future cybersecurity system.
AI EdgeLabs is an advanced and autonomous cybersecurity AI platform that equips security teams with threat intelligence software to protect, detect, and remediate risks in real time with the highest precision against malware, DDoS, botnets, and more, at the Edge and IoT/OT layers.