AI has transitioned from a mere trend to becoming an indispensable tool in combating cyberattacks. According to a report by Verified Marketing Research, the market size for AI in cybersecurity reached 7.58 billion dollars in 2022 and is projected to surge to 80.83 billion by 2030. Using AI is particularly beneficial for under-resourced organizations seeking enhanced protection for their data and operations.
Leveraging AI to Promote Cybersecure Organizations
According to an IBM study, cyber incident responders often find themselves outnumbered, with 68% stating that they commonly respond to multiple incidents simultaneously. Therefore, maintaining cybersecurity becomes more challenging when responders lack 100% visibility over these incidents. After all, it’s virtually impossible for human responders to be everywhere at once.
In contrast, AI can swiftly analyze massive volumes of data, detect various types of cyberattacks, and contribute significantly to the fight against them. This capability is especially critical considering the multitude of challenges faced in cybersecurity, such as the scarcity of skilled security professionals, numerous attack vectors, multiple devices and identities within organizations, a vast attack surface, and insufficient training and awareness among employees.
How Does AI Promote Cybersecure Organizations in a Threat-Prone Landscape?
1. Analyzing Massive Amounts of Data
AI can analyze vast quantities of data in a significantly shorter time frame than humans. AI’s processing power and speed enable it to quickly identify patterns, anomalies, and potential threats with exceptional efficiency. This capability enables organizations to respond swiftly and proactively to emerging cyber threats.
2. Detection of Complex and Evolving Threats
Cyberattacks are becoming increasingly sophisticated, employing advanced techniques and constantly evolving tactics. AI algorithms can quickly adapt to new attack patterns, identifying novel threats and vulnerabilities that might go unnoticed by human analysts.
3. Automation and Real-Time Response
Human responders in cybersecurity are limited by their capacity to handle multiple incidents simultaneously. Conversely, AI can automate repetitive tasks, allowing human analysts to focus on more complex and strategic aspects of cybersecurity. Moreover, AI-driven systems can provide real-time responses, instantly flagging and mitigating potential threats as they emerge. This proactive approach reduces response times and minimizes the impact of cyberattacks.
By leveraging the power of AI, organizations can bolster their cybersecurity defenses, stay one step ahead of cybercriminals, and protect sensitive data from evolving cyber threats.
AI-Driven Cybersecurity in the Real World
The Balbix Security Cloud Platform leverages AI-powered analysis to deliver vulnerability management, proactive breach control, and real-time risk predictions.
Similarly, Commodities trader ED&F Man Holdings sought help from Cognito, an AI-based threat detection and response platform. Cognito collects and enriches network metadata with unique security insights, employing machine-learning techniques to detect and prioritize attacks in real-time. ED&F Man Holdings benefited from Cognito’s ability to detect and block man-in-the-middle attacks, halt a crypto mining scheme, and uncover command-and-control malware that had remained hidden for years.
Challenges of AI-Driven Cybersecurity
While AI-driven cybersecurity offers numerous benefits, it also faces challenges that require attention and consideration.
AI Data Manipulation
AI systems rely on historical data patterns for analysis. Hackers can manipulate training data, introduce biases, and compromise the efficiency of AI models. Additionally, cyber attackers can deliberately target AI systems by injecting poisonous data to alter their behavior for malicious intent.
Malicious actors can employ AI techniques to develop intelligent malware capable of adapting and evading even the most advanced cybersecurity software, posing a significant threat to organizations.
Limited Amounts of Data
For AI to operate effectively in cybersecurity, it requires extensive, high-quality training data across the enterprise system. Insufficient or biased data can undermine the accuracy and reliability of AI systems, resulting in false positives, a false sense of security, and undetected threats that could lead to substantial losses.
Join the Conversation at DCA Series 8 WebForum
This year’s WebForum will focus on “Securing the Future: Exploring the Synergy of AI and Traditional Cybersecurity in a Threat-Prone World.”
Our panel of cybersecurity experts and leaders will engage in discussions covering various topics, including:
- Introduction to AI in Cybersecurity and the current state of the threat landscape
- AI-driven threat intelligence
- Addressing the capacity gap: building cybersecurity expertise in Africa
- Policy and regulatory frameworks for AI and Cybersecurity in Africa
- Addressing ethical and legal implications
Join us on October 27th, 2023, to be part of this informative and engaging conversation!
Sources: Computer Weekly, IBM, Verified Market Research