[BreachExchange] Extending cybersecurity to fraud analytics

[Audrey McNeil]

https://gcn.com/articles/2016/06/16/cyberattack-vs-fraud.aspx

Information security leaders often defend against cyber threats by focusing
on traditional IT tools and techniques -- firewalls, intrusion detection
and prevention systems, malware detection and analysis and the like. As
organizations have locked down systems with more sophisticated
defense-in-depth technical controls, adversaries have evolved to take
advantage of information systems by impersonating regular users. While
there are some similarities between cybersecurity and fraud, traditional
cybersecurity monitoring and analytics must evolve in order to identify the
fraudulent use of IT systems that may otherwise go unnoticed.

Two recent high-profile incidents at federal agencies illustrate the
difference between a traditional cybersecurity event and criminal activity
based on fraud. In 2015, the Office of Personnel Management disclosed two
separate but related cybersecurity incidents in which background
investigation records and personnel data for millions of current and former
federal employees had been stolen. This sophisticated attack involved
stealing credentials and gaining unauthorized access to the OPM network
after planting malware and creating a backdoor for data exfiltration. This
intrusion into OPM’s systems and networks – which fits the pattern of
nation-state activity and the mold of a traditional cybersecurity incident
-- resulted in likely the most damaging network intrusion and data breach
in U.S. history.

Also in 2015, the IRS disclosed an incident involving its Get Transcript
web application in which taxpayer data for hundreds of thousands of
citizens was potentially exposed.  However, unlike the OPM incident, no IRS
systems or networks were actually compromised. Rather, criminals used
information they had already obtained from other outside sources to
impersonate taxpayers. They used the Get Transcript application as it was
designed to obtain transcripts of taxpayer returns from prior years. While
the result was similar in that sensitive information made it into the hands
of criminals, this was not a cybersecurity attack detectable via
traditional tools or techniques. No malware was involved, there was no
system or network intrusion and any taxpayer data returned to fraudsters
was done so as if they were the actual taxpayer using the system as
designed.

While improvements to traditional cybersecurity defenses can combat the
type of attack seen against OPM, those same techniques will not prevent or
detect fraud and the misuse of systems as seen in the IRS event. Detecting
fraud requires a different mindset and a different type of analyst. Even
highly-skilled cybersecurity analysts who can reverse-engineer malware and
analyze network packets will be unable to detect fraudulent activity in
which no malware or network compromise occurs. Similarly, neither network
defense tools such as firewalls, intrusion detection systems or anti-virus
(nor the security events generated by these tools) will detect or identify
the type of attack seen against the IRS Get Transcript application. These
tools rely on identifying known malicious files or defined signatures of
traffic attempting to exploit known system or network vulnerabilities.
Detecting and preventing fraud, on the other hand, requires an in-depth
knowledge of the expected user activity and behaviors that will not be part
of common signature sets from security vendors.

Both types of attacks take advantage of IT's inherent struggle between
usability and security. In the case of the OPM breach, the background
investigation and personnel systems provided an online repository and
workflow for processing this critical information. The IRS Get Transcript
application used an authentication mechanism intended to be strong enough
to validate taxpayer identities while offering convenience and minimizing
the taxpayer burden.

There is no silver bullet technology or capability that can prevent or
detect fraud. Organizations must start by establishing a baseline of normal
and valid user activities for their systems. By first understanding the
intricacies of the business and expected user behavior, organizations can
begin to identify atypical behavior. This analysis may include session
rates or lengths, transaction velocity, geographic location and time or
date anomalies.

Fraud analytics must be supported by individuals with specialized
backgrounds in mathematics, data modeling and statistics in order to be
effective. Once thresholds for relevant behaviors have been identified, it
may be possible to leverage traditional security information and event
management tools for correlation, monitoring and reporting of fraud from
new data sources. If existing tools cannot support fraud analytics,
specialized fraud detection technologies or external services may be added
to the overall organizational security architecture.

Fraud analytics requires a change in mindset from traditional cybersecurity
monitoring, but it must still be a coordinated effort by the IT team or an
extension of traditional security operations center teams. With the right
skillsets and level of attention on fraud analytics, organizations can
further advance their overall cybersecurity capabilities to detect and
ultimately prevent the new fraud and impersonation techniques criminals are
more frequently using to bypass traditional enterprise cybersecurity
defenses.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.riskbasedsecurity.com/pipermail/breachexchange/attachments/20160617/ca829244/attachment.html>