The growth of global digitization is so vast that cyber threats are beginning to outpace human scale or capability. The enterprise attack surface is massive and continuously growing in direct proportion to cloud computing, sophisticated networking, system portability, online transactions, coordinated networks, and interlinked servers. As a response to this unprecedented pace, cybersecurity tools reinforced with Artificial Intelligence (AI) have emerged. But can AI in cybersecurity solutions really help mitigate breaches and reinforce your cybersecurity defenses?
We know cyber attackers are using AI to perform distributed denial of service (DDoS) attacks. These incidents have taught network security officials that AI in cybersecurity and in the digital ecosystems will help identify vulnerable spots, especially if they deal with big data and strategies accordingly.
Use of AI in cybersecurity
AI gathers data and applies logic to find connections between risks, such as infected files, strange IP (Internet Protocol) addresses, and cyber threats posed by individuals from within the organization, former employees, partners, etc. These AI-gathered, logical and data-driven insights are real-time or near real-time, therefore cybersecurity specialists can respond to risks of cyberattacks and vulnerabilities up to 60 times faster.
Moreover, machine learning in cybersecurity has also added greater value. As a combination, AI and machine learning (ML) have become a preferred combination for scrutinizing information and network security threats, making it easier to analyze big data and malware trends. Examples of ML and AI in cybersecurity includes: cybersecurity experts can detect and study malware ranging from zero-day vulnerabilities, risk behavior, phishing, and malicious code downloads. The combined efforts AI and ML helps to proactively report any deviation from the previously reported hacker mannerism or established hacking norms. Further, this also ensures cybersecurity professionals continuously update their strategies to safeguard against other risks.
Why do organizations prefer artificial intelligence in cybersecurity?
Rule-based detection systems to handle any false positive results during attacks
Big data analysis with constant security update analysis
IT security monitoring
Efficient threat handling
Retrieving affected systems along with root cause analysis
Threat forecasting and trend analysis
Deep analysis of threat incidents and investigation
Read more about: Deploying IT security governance to address cyber threats
What is unique about using artificial intelligence in cybersecurity?
One major advantage of using AI in cybersecurity is that it continuously evolves, and self-updates based on ongoing data and information analysis. Also, these AI-infused systems are iterative, dynamic, and get smarter with every quantum of data analyzed.
The management of an organization’s cybersecurity is beyond human capacity alone. Effective management requires advanced technologies to cover vast attack surfaces and keep a check on the thousands of connected devices, systems, servers, and networks. Therefore, the use of AI in cybersecurity is umpteen. These AI-backed cybersecurity tools independently gather data across enterprise information systems and send alerts about potential cyber vulnerabilities. The gathered data is analyzed and used to perform correlation tests for pattern analysis across millions of signals relevant to the enterprise attack surface. Any cybersecurity strategy built on these data-driven analytics is expected to be much more efficient and cost-effective.
What is the difference between artificial intelligence and data analytics?
As mentioned before, AI is iterative or self-learning and evolves along with analysis and data reading. Data analytics is a static process that involves examining large data sets and presenting its conclusions using specialized systems and software. It is not iterative or self-learning. Therefore, embedding artificial intelligence in cybersecurity solutions offers a more proactive approach and a constantly evolving feature.
Major benefits of implementing AI into cybersecurity
The integration of artificial intelligence and cybersecurity allows human teams to improve their enterprise- and domain-specific knowledge. This is important as cyber attackers have different attack formats based on industry, company size, operational capacity, etc.
- AI-enabled cybersecurity offers the security team a data repository and an inventory of all the devices, users, and applications present within the enterprise information system. This enables better categorization and management of inventory.
- Hackers follow not only industry-specific trends but also economic, social, political, and even religious trends. The latest is COVID-19 cyber threats. The use of a in cybersecurity also extends in understanding these trends. AI-based cybersecurity systems study the various hacking patterns among large data sets through deep learning, neural networks, and natural language processing. Once the hacking trend is realized, it helps in understanding the potential threat, and its impact, and supports the development of a proactive strategy.
- The identification of cybersecurity threats and vulnerabilities helps organizations strategize and implement feasible actions and better allocate human resources. Example of AI in cybersecurity includes: organizations use AI-enabled bots and other voice assistants to reduce labor costs on mundane and repetitive jobs, instead of allocating skilled labor to these less strategic responsibilities. Studies anticipate that AI-powered voice assistant adoption in mobile will reach 8 billion by 2024 as against 4.2 billion in 2020.1
- An average enterprise receives ~200,000 cyber threats every day.2 This number is so huge that a team of cybersecurity specialists would never be able to separate the complexity of each of these threats and efficiently handle this volume. Artificial intelligence in cybersecurity offers quicker prioritization and response to security alerts, meaning that out of 100,000 security alerts raised, it can project which has the highest risk and deal with them first. This creates faster response times, accurate root-cause analysis, and better insights. According to Accenture, AI can improve the productivity of any enterprise by ~40% if it is implemented and integrated well with the required skill set.3
Artificial intelligence and machine learning can have a substantial impact on reducing cyberattack risks but not all organizations know where to begin to implement these technologies. CAI delivers cutting-edge cybersecurity solutions, skills, and expertise to public and private organizations. We provide end-to-end, customized cybersecurity services that include assessment, governance, planning, management, and administration. Fill out the form to speak with a cybersecurity expert today!
- Laricchia, Federica. “Number of Voice Assistants in Use Worldwide 2019-2024.” Statista, March 14, 2022. https://www.statista.com/statistics/973815/worldwide-digital-voice-assistant-in-use/. ↩
- Limited, Cyber Management Alliance. “Home - Cyber Security Training: Cyber Management Alliance.” Home - Cyber Security Training | Cyber Management Alliance. http://www.cm-alliance.com/. ↩
- Purdy, Mark, and Paul Daugherty. “How AI Boosts Industry Profits and Innovation - Accenture.” Accenture. Accenture, 2017. https://www.accenture.com/fr-fr/_acnmedia/36dc7f76eab444cab6a7f44017cc3997.pdf. ↩