From Phishing to Predictive Analytics – How AI Cybersecurity Can Better Protect Businesses.

In 2023 IBM released their findings based on research data to measure the impacts and costs of Data Breaches. The report by IBM Security titled, Cost of a Data Breach Report 2023, studied 553 organizations impacted by data breaches across 16 countries and 17 industries. The report examined the breaches’ root causes and short and long-term impacts. The research by IBM Security concluded that the average cost of a breach is $4.45 million, an increase of 2.3% in 2022 and 15% from the 2020 average of 3.86 million. 

Taking the initiative of this growing threat, many organizations invested heavily to address these vulnerabilities by increasing security investments towards incident response planning and texting, employee training, and threat detection and response technologies. While the report centers around increased costs and other obstacles toward returning to normal business function, IBM Security also highlights steps taken by companies to limit losses and other damages.  Of these investments security AI and and automation assisted in reducing costs, minimizing time to respond, and helping contain and isolate breaches from compounding damages. The report states, “Organizations that used these capabilities extensively within their approach experienced, on average, a 108-day shorter time to identify and contain the breach. They also reported USD 1.76 million lower data breach costs compared to organizations that didn’t use security AI and automation capabilities.” 

Minimizing losses and costs, cutting off breaches from furthering into other systems and databases, and expediating critical response times are just some of the primary benefits of today’s Artificial Intelligence technologies when applied to business cybersecurity. As 2024 promises greater expansion of interest in the field, we will explore more ways in which Artificial Intelligence is protecting our businesses and empowering infrastructures to best protect themselves. 

Greater Reliance by Big Tech for advanced detection

Furthering the trend, Big Tech is discovering the benefits of AI-powered solutions in terms of efficiency, and growth, and allowing users to understand active threats as they occur. Examples of these applications range across varying industries including the financial and public sectors. Google and Microsoft created new models to process threat intelligence data for greater detection and the collection of first-party data relating to these attacks. Microsoft has also added GPT4 to analyze threat signals and summarize within Microsoft Security Copilot with a user-facing review. PayPal also leverages AI to learn from its transaction data in real time, enhancing capabilities to flag any irregularities. MasterCard is also adopting similar technologies that learn from analyzing legitimate and fraudulent transactions. These benefits afford greater confidence within these systems, saving on further costs ranging beyond detection and costs. 

Top performing use cases for Cybersecurity

The Aberdeen Strategy & Research study, The State of AI in 2023, found that the top three use cases for AI in cybersecurity include: 

• Patten Recognition: lowering false positives, filtering noise, and saving on response times for analysts. 
• Process Automation: correlating data from multiple sources, providing analysis without assumptions of causality, enabling faster triage by cybersecurity professionals.
• Predictions: identifying vulnerabilities and prioritizing updates and preventative measures. 

AI applies what it has learned to recognize what actions are needed to be taken. Leveraging behavioral analysis, signature-based anomaly detection, and automated classifications, AI can simplify the menial nature of manual compliance tasks while also meeting standard regulations for compliance, data privacy, cybersecurity, as well as other delicate considerations based on the industry in question. Other benefits that save costs include streamlined workflows and authentication solutions that provide both user convenience and heightened protections. 

Addressing a New Era of Phishing Schemes

When Phishing relies more on the human factor, mistakes within the content such as broken links, misspellings, or poor design could tip off users of a scam on a more routine scale. These mistakes also empowered spam filters to better alert users of phishing attempts on top of messaging that would trigger a sketchy feeling among users. AI can work to create content that is in-depth, grammatically correct, and properly designed to appear legitimate and persuasive. Phishing and Social engineering attacks are expected to approach a new dawn with the usage of AI systems. Combined, these methods form a “spear phishing” attack where sensitive data such as social media credentials and files can be obtained to spoof an identity and make the message and messenger appear as legit as possible. 

Technology companies are finding ways to develop algorithms and machine learning methods that can defend and detect these new threats at scale to meet rising demand. Data analysis and machine behavior can also understand what methods of messaging users prefer, allowing for greater detection of phishing attempts solely on the first-party data of the user. 

Addressing the Human Factor – The Next Step

Advances in cybersecurity technologies bring many opportunities for creating a safer internet for users. Cyberattackers in 2024 will continue to go after the human factor, especially with increased credibility, more accurate and relevant content, and other social engineering practices designed to gain access and credentials to critical infrastructures. While these new investments are needed for a safer future, investing in cybersecurity training amongst your workforce is still recommended to prevent cyberattacks and breaches in data on the most common scale. For more information on upskilling your employees and finding top-level talent for your organization’s needs, please visit www.thrivedx.com