Cyberattacks have become so common that there’s one every 39 seconds.
Sensitive data has always been a prime target of cybercriminals. “During the first quarter of 2023, more than six million data records were exposed worldwide through data breaches,” says a Statista report. Attackers tend to target high-value data such as payment details, PII, healthcare records, authentication credentials, insurance records, and more.
Data breaches are an expensive problem. Based on IBM’s cost of a data breach report, the global average cost of a data breach in 2023 was $4.45 million. The actual cost of a data breach amounts to more than just money lost to ransom, the cost of investigating the breach, or the revenue lost due to business downtime. Additional expenses include fines related to regulatory compliance violations, legal and audit fees, the fall of stock prices for publicly listed companies, and customer retention costs due to reputational damage.
While organizations are doing their best to adopt effective strategies to protect sensitive data, there’s no 100% foolproof cybersecurity system.
More and more organizations are acknowledging the fact that they are far more vulnerable to sophisticated attacks than ever before. The risk to business continuity and increase in the cost of data breaches have forced mature organizations to focus on bringing their cyber risk scores down to acceptable levels and minimizing the impact of a data breach.
Time matters
“Time is the new currency in cybersecurity both for the defenders and the attackers…early detection and fast response can significantly reduce the impact of a breach.”
IBM’s Cost of a Data Breach Report 2023
According to IBM’s Cost of a Data Breach Report 2023, the average data breach life cycle is 322 days—meaning it takes that long for organizations to identify and contain an active breach. This period usually gives attackers enough time to get away with their plan and access sensitive data and client records. The close relationship between response time and a data breach is a critical factor that can define the impact and severity of a data breach on an organization.
Take the case of one of the biggest breaches to date, the Equifax data breach. Hackers exfiltrated sensitive data of more than 148 million consumers—40% of the American population. Equifax had failed to patch a known vulnerability, making it easier for the attackers to enter its system. While the breach was discovered on July 29, 2017, it’s believed that the breach had occurred much earlier, possibly as early as May 2017. But Equifax made the public disclosure only on Sept. 7, more than a month after its discovery. This delay in detection and response gave attackers plenty of time to exfiltrate sensitive data. And this cost the company dearly. Equifax was fined $700 million for the breach. The Equifax data breach is a perfect example of the grave effects of a delayed response time.
In the business world, time is money. The same is true in the case of a data breach. A shorter mean time to detect (MTTD) means less time for cybercriminals to steal or tamper with sensitive data. And a faster response means better chances of controlling the damage caused by the breach. Both these factors can indirectly help reduce the total cost of a data breach. This means every second after a breach starts is pivotal and can directly determine the impact of the breach.
AI and automation can help
The good news is that AI and automation can be helpful in preventing and mitigating data breaches. IBM’s report shows that organizations that used both AI and automation reduced the data breach life cycle by 108 days. In fact, “organizations that deployed security AI and automation extensively saw, on average, nearly $1.8 million lower data breach costs than organizations that didn’t deploy these technologies.”
AI-based solutions can be a powerful instrument to curb data breaches. AI has the power to monitor and analyze large volumes of transactional data to detect fraudulent activities, anomalies, and unusual behavior. The implementation of AI-driven fraud detection systems can help banks save around $10 billion annually according to a study by Juniper Research. Automation, on the other hand, can help reduce data breach detection time and ensure quick incident response.
A survey by Capgemini Research Institute reports that 75% of cybersecurity executives use AI in network security, and another survey by BlackBerry found that “the majority (82%) of IT decision-makers plan to invest in AI-driven cybersecurity in the next two years and almost half (48%) plan to invest before the end of 2023.”
Being prepared
Preventing a breach might be implausible, but how an organization navigates its response to a breach is significant. Conducting regular security audits to ensure security measures are up to date, investing in a swift breach response system, and providing employees security awareness training can help organizations be better prepared. Additionally, investing in the right data security tools, leveraging AI and automation, and implementing Zero Trust principles can help reduce the time taken to detect and respond to a data breach, or even keep it from happening in the first place.
Breaches can be an expensive problem. However, with the right mindset, tools, and technology, IT teams can respond quickly to contain a breach and minimize its damaging consequences.
