Last year, hackers made off with $951 million from the Bank of Bangladesh. The record-breaking cyber-heist was no anomaly. It was just one in a series of sophisticated cyber-attacks targeting the financial sector. In 2014, criminals stole account information from 83 million JP Morgan customers. And again last year, a single Russian bank suffered 69 separate DDoS attacks. Cyber-attacks against the financial sector are relentless.
And finance isn’t just hit more often than other industries. It’s hit harder. For banks, the average cost per record stolen is $221, well over the average of $158. Driven by the prospect of a huge payday, hackers reserve some of their most sophisticated attacks for banks and other high-profile financial organizations.
To detect advanced attacks like these, we use unsupervised machine learning to identify deviations from normal network activity. Crucially, this approach lets companies detect threats from the inside. At Darktrace, some of the biggest vulnerabilities we’ve found started with a careless employee. Nowhere is this activity more troubling than in the financial services sector.
For example, at a top US investment firm, we detected strange communications between a company desktop and a Chinese cloud service. These communications were deemed highly anomalous and a major deviation from that user’s normal behavior. The employee in question was using the cloud service for legitimate work reasons, but this service came with a host of hidden risks — namely, it was secretly transmitting login details to an unknown third party. The leaked information could have led to a debilitating attack.
These attacks are alarming, but in the future, attackers won’t just try to steal data; they’ll try to change it. Since financial services rely on public confidence, they’ll be disproportionately affected by data manipulation. For instance, by subtly tweaking bank account information, an attacker could destroy the very integrity of the bank’s data. The bank would lose all credibility if the attack went public. Similarly, an attack could alter the mathematical models that inform boardroom decisions at a Wall Street company, thus forcing them to make bad investments.
Between insider threats and sophisticated data manipulation, banks and other financial organizations are feeling the brunt of the ongoing cyber-war. To fight back, they have to arm themselves with similarly advanced security tools. Because when it comes to cyber security, banks are no longer ‘too big to fail’.
To learn more about the challenges facing financial institutions, check out Darktrace’s Industry Data Sheet on Financial Services.
Justin is one of the US’s leading cyber intelligence experts, and holds the position of Director for Cyber Intelligence & Analytics at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years of experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.