Published on October 11, 2023, 7:41 pm
The 2023 Identity Security Threat Landscape Report from CyberArk has revealed some important findings based on a survey of 2,300 security professionals. The results are concerning and shed light on the current landscape of identity security threats.
According to the report:
– 68% of security professionals are worried about insider threats resulting from employee layoffs and churn.
– 99% expect some form of identity compromise due to financial cutbacks, geopolitical factors, cloud applications, and hybrid work environments.
– 74% are concerned about the loss of confidential data through employees, ex-employees, and third-party vendors.
These figures highlight the growing concerns around identity security and the need for effective solutions. One area that has been heavily discussed as a potential solution is digital identities.
Digital identities have long been seen as a way to enhance cybersecurity and reduce data loss. The idea revolves around assigning unique markers to individuals, such as biometric signatures or behavioral actions, which can then be digitized and associated with their identity. This approach aims to minimize authorization and authentication risks by creating a “trust and verify” model.
However, in an AI-driven world where malicious actors can leverage AI for attacks, the trust placed in digital identities is being challenged. AI-enabled attacks have the ability to learn about an IT system faster than humans can, allowing both technical and social engineering attacks to be tailored specifically to an individual or environment. This includes spearphishing campaigns based on extensive data sets gathered from various sources like social media posts or public surveillance systems.
As a result, digital identities that may have been reliable in a non-AI world are now at risk of being compromised. This raises questions about the reliability of trust in this digital age and highlights the need for rebuilding trust within digital identity systems.
Artificial intelligence also plays a significant role in identity verification solutions. These solutions utilize AI technology to improve access request time and manage large volumes of login attempts. However, AI introduces a variable element to identity trust. The rapid advancements in AI technology enable the creation of convincing digital replicas and deep fakes, blurring the lines between what is real and what is fake. As machine learning capabilities improve, they become increasingly susceptible to manipulation by biased programmers.
The combination of powerful monitoring technologies, increasing computational power, and data mining capabilities poses additional challenges. The more data that is gathered for security purposes, the greater our digital risk profile becomes, making it easier for malicious actors to create convincing digital avatars.
To address these challenges and limit the attack surface:
– Organizations can adopt a top-down approach by generating and holding only the necessary data, discouraging excessive data holds tied to individuals.
– Whitelisting access can be implemented as a bottom-up approach to limit access permissions and rebuild identity trust.
– A focus on risk management and prioritizing remediation efforts based on identified vulnerabilities helps optimize resources.
In conclusion, while there are risks associated with minimizing data collection and holding less data, it is essential in the age of abundant data to prioritize security over quantity. By doing so, organizations can reduce their susceptibility to data loss and maintain resilience in an ever-evolving threat landscape.
(Article inspired by the post “Artificial intelligence threats in identity management” appearing on Security Intelligence.)