Preventing Data Exfiltration with Anti Data-Exfiltration (ADX that Workstm)
In shocking findings, the majority of cybersecurity professionals admit they are not confident in their ability to prevent data loss.
In a recent paid survey, conducted by Ostermann Research, over 250 data security experts were asked if they could confidently defend the networks they are responsible for from attacks designed to exfiltrate data.
An astounding sixty percent lack confidence in the ability of their security tools to prevent data loss.
This is not due to a lack of awareness.
The data loss problem has been an increasingly growing concern in the world of IT. Of the participants, nearly three-quarters of them recognized the importance of preventing data loss–up from a mere thirty-nine percent in a similar survey a year ago.
As the risk of data loss continues to rise due to a full range of dangers–from insider threats to ransomware attacks–security professionals today are deeply concerned about addressing this problem.
The Failure of Traditional DLP
It seems however that most of the current tools out there, are just not cutting it.
Often clients will complain about configuration complexity, despite the users being seasoned IT experts. Similarly, demanding maintenance, complex deployment even after the platform is set up, are all commonly heard in the DLP space.
Then there’s simply the issue of efficacy.
If a DLP system can’t detect malicious activity, are produces so many false positives that real threats from false alarms become indistinguishable, then the platform can’t perform its job.
This has led many companies into a struggling-in-the-dark scenario where huge amounts of enterprise resources, in both money and manpower, are spent on burdensome systems that do not deliver in the real world.
Some in the cyber industry have begun calling for a new approach to DLP, one that can account for the emerging threats to enterprise data. The term ADX (Anti-Data Exfiltration) or SDX (Stop Data Exfiltration) has become a bit of a buzzword in the IT world as of late. In the ADX / SDX model, systems would deploy active measures to detect and block the ‘kill-chain’ of deceptive malware and prevent the attacking program from executing its commands on the system. This method, the advocates say, is the only one that can defend against ever-advancing cyber threats that have already proved too elusive for most contemporary tools–the dreaded polymorphic attack being one such example.
While the efforts to improve the state of DLP are commendable, this innovative method being put forward is not “new” at all.
At the heart of ADX is the rejection of automated, passive frameworks for protecting data. Since these systems essentially wait for the activity to match predetermined indicators, they cannot keep pace with the offensive tools being deployed by modern cybercriminals.
GTB’s DLP that Workstm is ADX / SDX that Workstm
But it is this very proactive approach that has been the basis for all of GTB’s platforms for years.
GTB’s DLP That Works is already delivering everything the ADX advocates are calling for. Using AI-powered technology, the program learns the network its protecting over time, allowing it to constantly increase its defensive accuracy. With Smart DLP, false positives are virtually eliminated, ensuring that managing DLP will not disrupt business operations or siphon off critical IT resources.
They are highly impressed with GTB’s all-in-one DLP solution and its ability to discover, classify, detect, and protect companies from threats in a seamless manner.”
If you have sensitive information on your enterprise, you need GTB –
if for no other reason than that you’ll sleep much better knowing your data is protected.
Peter Stephenson, SC Magazine
We see GTB’s platform as a direct response to address this problem, and we feel it is a best-in-class solution.
Nov. 16, 2022 lkin
For these reasons, GTB is a top choice among those who take data protection seriously and is used by major players across industries, including finance, healthcare, defense contractors, and government.