A systematic review of secure coded caching
- URL: http://arxiv.org/abs/2603.11145v1
- Date: Wed, 11 Mar 2026 17:21:07 GMT
- Title: A systematic review of secure coded caching
- Abstract summary: Caching allows content to be delivered to users in peak and off-peak times.<n>Security and privacy of cache placement, user demand, and content delivery are paramount.<n>We evaluate existing schemes in terms of the security provided and the cost of this security provision.<n>As a result, we identify and prioritise open security and privacy challenges for the future.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: In a content delivery network (CDN), resources are strained during peak-time and underutilised in off-peak times when supplying digital content to users. Caching can help balance this. At the off-peak time some content is delivered to users' local caches. During peak time, the use of cached data to serve users' requests relieves strain on the network by reducing repeated transfer of popular content. In \emph{coded caching}, the cache content placement is designed in conjunction with the delivery techniques to optimise network throughput. Since dissemination of information, as well as the delivery of entertainment, is reliant on CDNs, the security and privacy of cache placement, user demand, and content delivery, are paramount. In much of the literature in \emph{secure coded caching}, security is built on top of solutions that have efficiency in mind, and most current proposals focus on the security of individual parts of the process. A lack of a unifying network model also makes it difficult to compare or combine solutions. In this survey we analyse the security and privacy requirements of secure coded caching, and evaluate existing schemes in terms of the security provided and the cost of this security provision. We also review the techniques used to achieve secure coded caching and analyse their limitations. In addition, we contextualise secure coded caching in the landscape of other secure content delivery primitives. As a result, we identify and prioritise open security and privacy challenges for the future.
Related papers
- Decouple and Cache: KV Cache Construction for Streaming Video Understanding [53.55135022958052]
Streaming video understanding requires processing unbounded video streams with limited memory and computation.<n>We propose Decoupled Streaming Cache(DSCache), a training-free cache construction mechanism that adapts pretrained offline models to streaming settings.<n> Experiments on Streaming Video QA benchmarks demonstrate DSCache's state-of-the-art performance, with an average 2.5% accuracy gains over prior methods.
arXiv Detail & Related papers (2026-05-03T13:02:44Z) - Breaking Diffusion with Cache: Exploiting Approximate Caches in Diffusion Models [1.399348653165494]
We introduce a prompt stealing attack using the cache, where an attacker can recover existing cached prompts based on cache hit prompts.<n>We introduce a poisoning attack that embeds the attacker's logos into the previously stolen prompt, to render them in future user prompts that hit the cache.<n>These attacks are all performed remotely through the serving system, which indicates severe security vulnerabilities in approximate caching.
arXiv Detail & Related papers (2025-08-28T04:46:44Z) - Auditing Prompt Caching in Language Model APIs [77.02079451561718]
We investigate the privacy leakage caused by prompt caching in large language models (LLMs)<n>We detect global cache sharing across users in seven API providers, including OpenAI.<n>We find evidence that OpenAI's embedding model is a decoder-only Transformer, which was previously not publicly known.
arXiv Detail & Related papers (2025-02-11T18:58:04Z) - Efficient Inference of Vision Instruction-Following Models with Elastic Cache [76.44955111634545]
We introduce Elastic Cache, a novel strategy for efficient deployment of instruction-following large vision-language models.
We propose an importance-driven cache merging strategy to prune redundancy caches.
For instruction encoding, we utilize the frequency to evaluate the importance of caches.
Results on a range of LVLMs demonstrate that Elastic Cache not only boosts efficiency but also notably outperforms existing pruning methods in language generation.
arXiv Detail & Related papers (2024-07-25T15:29:05Z) - A Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and Challenges [23.242281571096782]
Caching content at the edge network is a popular and effective technique widely deployed to alleviate the burden of network backhaul.<n>There has been some controversy over privacy violations in caching content at the edge network.
arXiv Detail & Related papers (2024-05-03T04:27:32Z) - Caching Contents with Varying Popularity using Restless Bandits [0.3093890460224435]
We study the problem of content caching at the wireless edge(i.e. base stations) to minimize the discounted cost incurred over infinite horizon.
Using these structural results, we prove the indexability of the problem, and use Whittle index policy to minimize the discounted cost.
arXiv Detail & Related papers (2022-10-31T16:24:45Z) - Deep Reinforcement Learning and Permissioned Blockchain for Content
Caching in Vehicular Edge Computing and Networks [2.3966513096296547]
High mobility of vehicles and dynamic wireless channel condition make it challenge to design an optimal content caching policy.
Deep Reinforcement Learning (DRL) is an emerging technique to solve the problem with high-dimensional and time-varying features.
In this paper, we integrate DRL and permissioned blockchain into vehicular networks for intelligent and secure content caching.
arXiv Detail & Related papers (2020-11-17T06:04:21Z) - Caching Placement and Resource Allocation for Cache-Enabling UAV NOMA
Networks [87.6031308969681]
This article investigates the cache-enabling unmanned aerial vehicle (UAV) cellular networks with massive access capability supported by non-orthogonal multiple access (NOMA)
We formulate the long-term caching placement and resource allocation optimization problem for content delivery delay minimization as a Markov decision process (MDP)
We propose a Q-learning based caching placement and resource allocation algorithm, where the UAV learns and selects action with emphsoft $varepsilon$-greedy strategy to search for the optimal match between actions and states.
arXiv Detail & Related papers (2020-08-12T08:33:51Z) - Reinforcement Learning for Caching with Space-Time Popularity Dynamics [61.55827760294755]
caching is envisioned to play a critical role in next-generation networks.
To intelligently prefetch and store contents, a cache node should be able to learn what and when to cache.
This chapter presents a versatile reinforcement learning based approach for near-optimal caching policy design.
arXiv Detail & Related papers (2020-05-19T01:23:51Z) - A Non-Stationary Bandit-Learning Approach to Energy-Efficient
Femto-Caching with Rateless-Coded Transmission [98.47527781626161]
We study a resource allocation problem for joint caching and transmission in small cell networks.
We then formulate the problem as to select a file from the cache together with a transmission power level for every broadcast round.
In contrast to the state-of-the-art research, the proposed approach is especially suitable for networks with time-variant statistical properties.
arXiv Detail & Related papers (2020-04-13T09:07:17Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.