# CEKER: A Generalizable LLM Framework for Literature Analysis with a Case Study in Unikernel Security

arXiv: https://arxiv.org/abs/2412.10904 · HTML: https://mlsanity.com/paper/2412.10904/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 36 references that are in the map.
- First posted on arXiv 14 Dec 2024.

## Builds on (most cited first, 9 of 9)

- [Artificial Intelligence for Literature Reviews: Opportunities and Challenges](https://mlsanity.com/paper/2402.08565/) (2024)
- [Automated Literature Review Using NLP Techniques and LLM-Based Retrieval-Augmented Generation](https://mlsanity.com/paper/2411.18583/) (2024)
- [Cutting Through the Clutter: The Potential of LLMs for Efficient Filtration in Systematic Literature Reviews](https://mlsanity.com/paper/2407.10652/) (2024)
- [Are Unikernels Ready for Serverless on the Edge?](https://mlsanity.com/paper/2403.00515/) (2024)
- [SWARM-SLR -- Streamlined Workflow Automation for Machine-actionable Systematic Literature Reviews](https://mlsanity.com/paper/2407.18657/) (2024)
- [Isolating Real-Time Safety-Critical Embedded Systems via SGX-based Lightweight Virtualization](https://mlsanity.com/paper/1909.09486/) (2019)
- [A Security Perspective on Unikernels](https://mlsanity.com/paper/1911.06260/) (2019)
- [The Endokernel: Fast, Secure, and Programmable Subprocess Virtualization](https://mlsanity.com/paper/2108.03705/) (2021)
- [A Survey of Unikernel Security: Insights and Trends from a Quantitative Analysis](https://mlsanity.com/paper/2406.01872/) (2024)

## Abstract (arXiv)

Literature reviews are a critical component of formulating and justifying new research, but are a manual and often time-consuming process. This research introduces a novel, generalizable approach to literature analysis called CEKER which uses a three-step process to streamline the collection of literature, the extraction of key insights, and the summarized analysis of key trends and gaps. Leveraging Large Language Models (LLMs), this methodology represents a significant shift from traditional manual literature reviews, offering a scalable, flexible, and repeatable approach that can be applied across diverse research domains. A case study on unikernel security illustrates CEKER's ability to generate novel insights validated against previous manual methods. CEKER's analysis highlighted reduced attack surface as the most prominent theme. Key security gaps included the absence of Address Space Layout Randomization, missing debugging tools, and limited entropy generation, all of which represent important challenges to unikernel security. The study also revealed a reliance on hypervisors as a potential attack vector and emphasized the need for dynamic security adjustments to address real-time threats.