AI Data Consumption and Analysis are a Cybersecurity Force Multiplier

AI’s capacity to consume, assimilate and use massive datasets from numerous resources is the driving force behind significant advancements in most industries. AI-driven technologies provide deeper data insights to improve health care outcomes and optimize operational processes in manufacturing, for example. AI technologies to improve security outcomes are also being deployed to detect and prevent cyberattacks. While these AI use cases differ in their procedures and goals, the common denominator is the value of leveraging data intelligence.

Digital Data is King

The phrase “data is king” is often used to describe the importance of data in marketing. Data intelligence is the foundation of virtually every digitally enabled organization across many disciplines. Data is the key to unlocking insights that help organizations make better decisions and improve their bottom line. Data analytics is the power behind automation processes that streamline workloads, speed results and provide greater accuracy. Consider gold. It is a strong currency used for investment and commerce and a precious metal used to create objects of beauty. It is a precious commodity that offers tremendous versatility.

Data analytics offers the same valuable diversity. Businesses use data intelligence to:

1. Inform and improve decision-making
2. Revamp and refine operations
3. Create new streams of revenue

In Cybersecurity, Data Equals Threat Intelligence

Data is increasingly valuable to organizations seeking to maximize their security intelligence. Security leaders are placing an increased, permanent focus on the value of data intelligence as fundamental to their digital transformation and cybersecurity posture.

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Security teams are leveraging data analytics to improve cybersecurity posture by enhancing these processes:

• Identifying and mitigating vulnerabilities
• Detecting and responding to threats
• Improving incident response times
• Enhancing security awareness training

Collecting and analyzing data from various sources allows organizations to gain insights into their security posture and make informed decisions for improvements. AI’s capability to consume billions of data artifacts improves cybersecurity outcomes by automating incident response, streamlining threat hunting and analyzing attack patterns for proactive defense measures. The ability to continually learn and advance knowledge makes AI a valuable security team member.

The six primary benefits of AI for cybersecurity are:

1. Digests massive amounts of data and learns by expanding its intelligence over time
2. Correlates data to identify and validate security incidents
3. Learns about and analyzes users with behavioral analytics
4. Takes automated action to prioritize, synchronize and deliver traffic activity and actions more efficiently and effectively
5. Produces more consistent results because it is not influenced by emotions and other conditions that affect human decision-making and responses
6. Eliminates duplicated processes that waste time and effort

AI’s Capabilities are Available for Both Beneficial and Malicious Intent

Cybercriminals are using AI to create smarter and more accurate attacks. Capitalizing on AI’s ability to grow in knowledge as it consumes data, threat actors use data collected from previous attempts to predict vulnerabilities or spot changes in victims’ data security.

In response, corporate defenders are using AI to protect against cybercriminals by investing in cybersecurity solutions with integrated AI technology. From endpoint security extended detection and response (EDR) to vulnerability assessments, penetration testing and privileged access management (PAM), AI enables cybersecurity teams to scale their protection capabilities effectively while orchestrating and automating time-consuming, repetitive and complicated response actions.

AI algorithms can analyze code and network infrastructure to discover vulnerabilities like weak passwords, misconfigurations and outdated software versions. Suspicious files and activities that might indicate the presence of malware can be quickly identified. Further, AI-driven solutions can monitor and analyze network traffic patterns for anomalous activity. Security teams are empowered to develop better defense strategies by generating and testing different attack scenarios.

These enhanced processes allow cybersecurity teams to handle large volumes of threats in more relevant time frames with less human intervention and better results. AI can provide insights into potential attack surfaces, allowing businesses to be more knowledgeable about their weaknesses and tighten their security controls.

Harnessing the Power of AI-Driven Cybersecurity

The integration of natural language processing and machine learning capabilities within AI is picking up steam with the global artificial intelligence in cybersecurity market size expected to expand at a compound annual growth rate (CAGR) of 24.3% from 2022 to 2030.

The continuing escalation in cyberattacks by malicious actors are now equally armed with AI advantages over commercial businesses, defense and government agencies. This emphasizes the need for defenders to fight AI-enabled foes with AI-enabled cybersecurity solutions. The challenge faced by companies trying to ensure effective cyberprotections will be appropriating the power of AI at a pace that meets or surpasses the threat strategies of cybercriminals.

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Lydia Zhang

Lydia Zhang is president and co-founder of Ridge Security. She holds an impressive entrepreneurial-focused resume that includes 20 years of leadership roles in network and cybersecurity. Lydia leads a Silicon Valley cybersecurity startup that develops automated penetration testing with the goal of delivering innovative security technologies to all. Prior to founding Ridge Security, Zhang held senior vice president and product management roles at Hillstone Networks and Cisco Systems. She holds a double Masters, MA and MS, from USC, and a degree from Tsinghua University in Biomedical Engineering.

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