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Research Topic Description, including Problem Statement:
Widespread malware attacks on container repositories can impact on data integrity in national security applications. Third party access has been identified as a major contributor to the problem. ll1e plan is to employ a new cyber forensic tool in a zero-trust security environment to mitigate and reduce the ability of cyber intrusions that can alter and steal valuable data.
Successful mission operations depend on the ability of an organization to collect. manage, analyze, and secure its data. Traditional network frameworks have become less appealing because they rely on a “trust but verify” paradigm that does not stand up well against the advanced tools and techniques of modern cyber attackers. The Zero Trust Framework has emerged as a logical replacement because it represents a paradigm shift to a “high-level strategy that assumes that individuals, devices, and services cannot automatically be trusted.” It is essential that the IC be able to trust the data that it depends, which is often stored in data repositories, arguably, the most prominent means for data sharing around the globe. Hence, the repositories must be trustworthy and secure. Unfortunately, widespread malware attacks on data repositories have recently been reported, in some case, impacting data critical to national security. Third-party apps, a staple of how we interact with data and services in both cloud and mobile-driven environments have shown a number of potential risks and breaches that signal a growing and troubling trend.
Most of the recently recorded attacks on data repositories have largely been accomplished through “access” tokens that authorize the sharing of specific user account information. The latest attacks on data repositories seem to have a common thread, i.e., they come primarily through third party access provided by ( )Auth, the open standard for token-based authentication and authorization.
Through ( )Auth, request links, recipients can be deceived into illicit grants, e.g. consent phishing emails that can enable access to attackers via API resources. In these cases, targeted users unknowingly grant permissions that allow attackers to make API calls on their behalf through attacker-controlled apps. Unfortunately, access to cloud SaaS environments is obtained with relative ease due to end user-granted permissions occurring without much scrutiny. Permissions can be granted by end users simply via a permissions request submitted from the third-party app. Similar problems can also occur through browser extensions via application performance interfaces (APIs). These clear cases that remind us of the dangers of pushing for greater access without a parallel focus on security.
As a result. the focus of this proposal is to develop a new framework based on advanced cyber forensics and the zero trust security model to improve container security in applications critical in select NATO operations.
The objective is to examine the performance of a new cyber forensic tool, currently used in law enforcement, and if it can be extended to NATO-related applications through the use of a zero trust security model.
In this study, the emphasis is placed on an advanced forensic based cyber security framework aligned with a zero trust security model that relies more on data lineage, end-to-end metadata, and the use of machine learning tools and methodologies. Most of the current computer forensic software have weaknesses that by themselves make them ill-suited for certain types of analyses. Such shortcomings require cross-validation of findings, wherein machine learning tools and techniques can play an important role.
The results of this research are expected to provide mitigation strategies and insight into adversary efforts to compromise or steal valuable data in NATO operations. The study will serve as a foundation for future endeavors that identify cyber vulnerabilities and exploits used, as well as ways to counter and protect critical data from intrusions.
Example Approaches:
Intrusion Detection and Prevention, Cyber Forensics, SIEM
Relevance to the Intelligence Community:
- Develop/enhance near real-time cyber forensics.
Key Words: Zero Trust Framework, Cyber forensics, Machine Learning, Data Repositories, Containers
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