How Does Artificial Intelligence Find the Bad Guys 10X Faster Than Traditional Methods? Enterprises perform cyber threat hunting by proactively searching through networks, endpoints, applications and datasets to hunt malicious and risky activities that existing security tools have not flagged. Unlike the passive cyber risks detection approach, the threat hunting process is proactive. It uses intelligence on collected data to identify and mitigate potential threats before the bad guys attack.
As businesses invest in powerful tools to hunt attacks, adversaries innovate new tactics that allow them to burrow their way into systems while avoiding detection for weeks or months. It is vital to augment traditional security monitoring methods with proactive artificial intelligence (AI) driven threat hunting tools, to root out infiltrators faster and before they access sensitive information.
In the current world, organizations are integrating technology, such as cloud services, mobile computing, the internet of things (IoT), 5G and blockchain in all business areas, changing how they operate and deliver value to customers. This increased digital transformation has resulted in rising cybercrime and cyberattacks, which complicate threat hunting activities. Attacks are becoming increasingly prevalent and sophisticated across businesses of all sizes in virtually every vertical market.
Weak threat hunting capabilities have resulted in losses of $17,700 every minute due to phishing attacks alone. Sixty-three percent of companies revealed that their data was potentially compromised within the last year due to a hardware-level threats. The average cost to an enterprise for a cyberattack is $3.92 million.
Other than the direct impacts of data breaches, organizations face penalization due to non-compliance fines in case of personal information loss. New cyber protection laws, such as the General Data Protection Regulation (GDPR) in Europe and Payment Card Industry Data Security Standard (PCI DSS), increase cyber incident costs even more.
Traditional threat hunting technologies rely too heavily on past data and lack a mechanism to improvise and learn how to discover emerging threats. Conventional firewalls, intrusion detection & prevention systems and antivirus programs cannot keep up with the new tactics and tools hackers use to exfiltrate sensitive information.
At the same time, organizations have many threat detection tools in their cybersecurity stack. Such proliferation leads to more alerts than a security team can reasonably handle. An article from Dark Reading states that the average Security Operations Center (SOC) team receives more than 10,000 alerts each day from threat monitoring solutions.
As enterprises rely more on digital technologies for all their operations, they need reliable threat hunting solutions to respond to a growing attack surface. Integrating AI and machine learning (ML) in tools and controls can bring some much needed visibility to real threats lurking within a company’s infrastructure.
As enterprises rely more on digital technologies for all their operations, they need reliable threat hunting solutions to respond to a growing attack surface. Integrating AI and machine learning (ML) in tools and controls can bring some much needed visibility to real threats lurking within a company’s infrastructure.
Unlike human security experts, machines do no rest or require sleep. Instead, AI-driven threat hunting systems persistently provide round-the-clock monitoring. The solutions do what developers design them to do. They super-correlate billions of events in a day, something that traditional security tools are not equipped to handle.
Here's why AI is a game-changer in finding the bad guys before they attack.
1. AI Improves Vulnerability Management
According to Wikipedia a computer vulnerability is a weakness which can be exploited by a threat actor, such as an attacker, to cross privilege boundaries (i.e. perform unauthorized actions) within a computer system. To exploit a vulnerability, an attacker must have at least one applicable tool or technique that can connect to a system weakness. In this frame, vulnerabilities are also known as the attack surface.
The United States Computer Emergency Readiness Team (US-CERT) revealed that 17,447 exposures were recorded in 2020. Officials published 4,168 high-severity vulnerabilities, 10,710 medium-severity vulnerabilities and 2,569 low-severity vulnerabilities last year, marking the fourth consecutive year with a record number of security weaknesses reported.
Managing thousands of emerging exposures with limited cybersecurity skills and legacy technologies is hugely problematic. Fortunately, installing AI- and ML-driven threat hunting tools proactively detect potential vulnerabilities in systems before bad guys exploit them. These solutions combine multiple factors including threat intelligence where the system monitors hacker discussions on the dark web, hacker behavior patterns, reputation and network traffic. An AI-based security tool analyzes these factors and uses the output to determine when and how a threat will target a vulnerable system.
2. AI-Driven Tools Detect Threats Quickly
Let us take an example of a commonly used cyberattack method, phishing – where cybercriminals deliver payloads using fraudulent emails, a form of social engineering. Today, social engineering attacks are incredibly prevalent, with 97 percent of employees unable to recognize a sophisticated phishing or spam email when compared to a legitimate one. It is astonishing to note that spear-phishing, a popular form of attack, causes 95 percent of all attacks targeting enterprise networks.
With an AI-powered threat hunting solution, organizations can track thousands of active social engineering sources and respond up to ten times faster than human analysts can. AI-based security products scan phishing threats globally in real-time, reliably discerning between falsified and legitimate websites.
3. Fewer False Positives
An AI-based system learns from past data and mistakes in real-time. This continuous improvement results in much less time spent by company security analysts tracking down alerts that are either inaccurate or meaningless. IBM recently noted that AI security solutions can reduce false positives by 50 to 90 percent while increasing detection speed. Ultimately, the process shrinks the window of compromise for a system, helping to measurably minimize any adverse impact.
4. Behavioral Analytics
A promising enhancement of AI in threat hunting is the technology's behavioral analytics capabilities. AI learns and creates behavioral patterns by analyzing how employees use company systems, online services and endpoints. For instance, an AI-driven solution can learn from users' typical login times, IP addresses, scrolling patterns and typing styles. The tool develops insights from such behavior and determines regular normal traffic. When the AI-driven solution discovers unusual activity that differs from standard patterns, it flags the traffic as suspicious and can inform the security team immediately while automatically blocking any potential harm to the business.
An AI-driven system is up and running 24 hours a day, 7 days a week monitoring everything from unusual large online purchases shipped to a new address, to a spike in data being downloaded from a sensitive server, to a change in user credentials from a strange IP address.
Securus360 provides an all-inclusive network security monitoring platform that delivers threat visibility across the entire infrastructure of a company, including servers, endpoints, network infrastructure, cloud instances and end-user behavior, all on a single pane of glass.
The award-winning, AI-driven, cloud-native technology combines machine learning, security automation and human intelligence to create a high speed and high touch cyber defense solution that proactively hunts, detects and helps neutralize advanced threats before they can impact your business.
Besides leveraging AI to find and neutralize the bad guys, the system is complemented with an SOC team of over 1,000 cyber warriors to monitor and analyze anomalies across company networks all day, everyday. The integrated service provides complete visibility to threats across IT infrastructure in real-time, eliminating the blind spots that bad actors exploit.