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About 270 papers for “Cache pollution”

Integrated Cache Scheduling Replacement Algorithm to Reduce Cache Pollution

Kavita Kalambe, Sunita Rawat, Nilesh Korde et al. · International Journal of Recent Technology and Engineering (IJRTE) · 2019

Cache memory management has recently become one of the most crucial research topics in the area of high performance computing. The cache memory has gained popularity due to its capability to offer faster access compared to main memory so processor can access data directly through cache very efficiently. As processor execution speed is faster than accessing memory so the goal is to keep programs rapidly accessible for processing. Cache memory helps not only to access data quickly but also improves the performance of the system. Various cache management policies have been developed to improve the performance of the system. In this paper we focus the issues related with the existing replacement policies and present a new algorithm to overcome these issues. In this paper, we proposed Integrated Cache Scheduling Replacement Algorithm (ICSRA) that will remove the object on the basis of integration of all the parameters like size, frequency and recency if the cache is full. This algorithm consider all size of object to replace with the condition of frequency and timestamp parameter to reduce the cache pollution [1]. Cache pollution means the cache unnecessary waste its space by holding such an object which is no longer be accessed. ICSRA helps to enhance the utilization of cache memory in an efficient manner as well as maximize the cache hit ratio to improve the performance of the system. A detailed classification has also been included based on different parameters which are depending on the analysis of the existing techniques.

Cited by 0Open access

Internet Cache Pollution Attacks and Countermeasures

Yan Gao, Leiwen Deng, Aleksandar Kuzmanovic et al. · 2006

Proxy caching servers are widely deployed in today's Internet. While cooperation among proxy caches can significantly improve a network's resilience to denial-of-service (DoS) attacks, lack of cooperation can transform such servers into viable DoS targets. In this paper, we investigate a class of pollution attacks that aim to degrade a proxy's caching capabilities, either by ruining the cache file locality, or by inducing false file locality. Using simulations, we propose and evaluate the effects of pollution attacks both in Web and peer-to- peer (p2p) scenarios, and reveal dramatic variability in resilience to pollution among several cache replacement policies. We develop efficient methods to detect both false-locality and locality-disruption attacks, as well as a combination of the two. To achieve high scalability for a large number of clients/requests without sacrificing the detection accuracy, we leverage streaming computation techniques, Le., bloom filters. Evaluation results from large-scale simulations show that these mechanisms are effective and efficient in detecting and mitigating such attacks. Furthermore, a squid-based implementation demonstrates that our protection mechanism forces the attacker to launch extremely large distributed attacks in order to succeed.

Cited by 51

Cache-Poll: Containing Pollution in Non-Inclusive Caches Through Cache Partitioning

Lucía Pons, Julio Sahuquillo, Salvador Petit et al. · RiuNet (Politechnical University of Valencia) · 2022

Current server processors have redistributed the cache hierarchy space over previous generations. The private L2 cache has been made larger and the shared last level caches (LLC) smaller but designed as non-inclusive to reduce the number of replicated blocks. As a result, the new organization shrinks the per-core cache area.

Cited by 2Open access

Reducing cache pollution in time-shard systems

Daisy T. Paul · DSpace@MIT (Massachusetts Institute of Technology) · 2001

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.

Cited by 0Open access

A Novel Cache Replacement Scheme against Cache Pollution Attack in Content-Centric Networks

Ying Liu, Ting Zhi, Haidong Xi et al. · 2019

In-network cache is a key service of content-centric networks. As an instance of content-centric networks, Named Data Networking (NDN) uses the traditional Least Recently Used (LRU) and Least Frequently Used (LFU) cache replacement strategy, which will cause large storage redundancy. Besides, as the content cache pollution attack may degrade the performance of the cache mechanisms and increase the content retrieval latency, a robust cache mechanism is especially required. To solve these problems, in this paper we propose a new intra-network cache replacement strategy, which integrates evaluating the popularity of caching contents and the betweenness of the nodes in the network topology. This strategy realizes the best performance of cache replacement in the network by weighing the importance of each node and the cache content popularity within the domain. Finally, the simulation results show that the new cache replacement strategy proposed in this paper can achieve a higher cache hit rate and less average hops than the LRU and the LFU cache replacement strategy in the NDN network.

Cited by 15

Detection of cache pollution attacks using randomness checks

Hyundo Park, Indra Widjaja, Heejo Lee · 2012

The Internet plays an increasing role in content dissemination as user-generated contents have exploded recently. Cache servers have been deployed to bypass bottlenecks in the network so that contents can be delivered to end users more efficiently. With caches becoming more embedded in the networks, emerging threats follow naturally. A cache pollution attack is one of the most serious threats on caching networks including the current Internet and emerging caching networks such as Content Centric Networking (CCN). In this paper, we propose a detection approach against cache pollution attacks using randomness checks of a matrix. We apply an effective filtering approach and a statistical sequential analysis for detecting low-rate attacks. The results of our experiments show that our approach can detect a cache pollution attack with attack rate of only a few percent of the overall rate.

Cited by 45

Gini impurity based NDN cache pollution attack defence mechanism

Vishwa Pratap Singh, R. L. Ujjwal · Journal of Information and Optimization Sciences · 2020

Name Data Network (NDN) is a futuristic Internet architecture that delivers content based on strategically chosen names and caches content on intermediate routers in the content-delivery path, which is used to fulfill future requests for the same data. In-network caching significantly improves network throughput but also makes NDN vulnerable to revamp security attacks such as cache poisoning, cache pollution, and cache snooping. In this paper, we focused on content pollution attack, in which the attacker disrupts the cache locality by intelligently crafted fake requests. This paper introduce monitor metrics for quantitative anomaly detection of requests and proposed a scheme based on Gini Impurity to detect network under cache pollution attack. The paper also proposed an Interest throttling mechanism based on trust to reinforce network under cache pollution attacks. The proposed scheme is evaluated through various experiments on NdnSIM simulator.

Cited by 5

Reducing Cache Pollution of Threaded Prefetching by Controlling Prefetch Distance

Yan Huang, Zhimin Gu, Jie Tang et al. · 2012

Threaded prefetching based on Chip Multiprocessor (CMP) issues memory requests for data needed later by the main computation, and therefore may lead to increased stress on limited shared cache space and bus bandwidth. In our earlier work, we had proposed an effective threaded prefetching technique that selects proper prefetch distance for specific application to improve the timeliness of prefetching. In this paper, we first estimate the upper limit of prefetch distance for specific application in our proposed threaded prefetching technique, and then analyze the effect of increasing prefetch distance on shared cache pollution. Our experimental evaluations indicated that the bounded range of effective prefetch distance can be determined using our method, and the shared cache pollution can be reduced by controlling prefetch distance in our proposed threaded prefetching technique.

Cited by 5

Mitigating the cache data pollution by using branch path tracking

Song-He Liu, Huansheng Song, Qi Shu-Min et al. · 2012

“Memory Wall” is one of the most important problems which must be solved for designing high performance processors. Efficient and intelligent cache system is key component of processor's memory system. We notice that cache pollution caused by the speculative execution of memory accessing instructions in predictive path may affect the cache and processor performance seriously. Based on the analyses of the impacts of speculative execution and cache data pollution to processor performance, this paper proposes a cache pollution control technique by using branch paths tracking, which is called Contra. Firstly, we construct a branch paths tracking table to follow the cache data written by memory accessing instructions in speculative branch paths. Then, processing of storage, accessing and replacement to these data are particularly controlled in order to mitigate influence of data pollution to cache system and processor performance. Simulation result indicates that, Contra technique eliminates cache pollution and upgrades performance effectively. Relative to the baseline architecture, D-Cache hit rate increases from 0.03% to 6.69%, average 1.80%. Improvement of IPC ranges from 0.01% to 6.60%, average 2.56%.

Cited by 0

A Survey on Mitigation of Cache Pollution Attacks in NDN

Najam Saqib, Sani Isnain · Acta Technica Jaurinensis · 2025

Named Data Networking (NDN) improves data retrieval by using in-network caching, but this advantage makes it susceptible to cache pollution attacks, where malicious or irrelevant content fills caches and reduces network efficiency. This paper reviews several mitigation techniques for these attacks, grouping them into proactive, reactive, and collaborative approaches. Each strategy is assessed based on its scalability, detection accuracy, and overall impact on network performance. While some progress has been made, existing methods often struggle in large, dynamic environments, where they tend to be computationally expensive and lack adaptability. The survey identifies key research gaps, such as the need for real-time, adaptive solutions that can operate without compromising network performance. It also highlights the potential for using AI and machine learning to enhance detection accuracy and reduce false positives. Future research should focus on developing scalable, decentralized systems to strengthen the security and efficiency of NDN’s caching mechanisms.

Cited by 0Open access

Improving NDN Resilience: A Novel Mitigation Mechanism Against Cache Pollution Attack

Abdelhak Hidouri, Haifa Touati, Mohamed Hadded et al. · SPIRE - Sciences Po Institutional REpository · 2024

Cache Pollution Attacks (CPA) are a growing concern in Named Data Networking (NDN) due to their potential to disrupt network services and compromise data integrity. While several defence mechanisms have been developed, they often struggle to keep up with the evolving nature of such attacks. This paper introduces a cutting-edge approach for detecting and mitigating CPA in NDN, utilizing Deep Reinforcement Learning (DRL). By employing a DRL framework, we leverage the power of deep neural networks to learn complex patterns within network traffic. Our DRL algorithm is designed to analyze the intricate dynamics of NDN environments and make informed decisions about cache management to protect against CPA. The agent’s learning process involves continuous interaction with the network, allowing it to adapt to CPA attack vectors and evolving NDN network conditions. The DRL-based mitigation mechanism is evaluated using the official NDNSim simulation environment. The results show that the DRL agent effectively identifies and mitigates CPA with high accuracy, thereby improving the Cache Hit Ratio, while incurring an acceptable increase in memory usage.

Cited by 1Open access

Enhancing the Malloc System with Pollution Awareness for Better Cache Performance

Xiaofei Liao, Rentong Guo, Hai Jin et al. · IEEE Transactions on Parallel and Distributed Systems · 2016

Cache pollution, by which weak-locality data unduly replaces strong-locality data, may notably degrade application performance in a shared-cache multicore machine. This paper presents NightWatch, a cache management subsystem that provides general, transparent and low-overhead pollution control to applications. NightWatch is based on the observation that data within the same memory chunk or chunks within the same allocation context often share similar locality property. NightWatch embodies this observation by online monitoring current cache locality to predict future behavior and restricting potential cache polluters proactively. We have integrated NightWatch into two popular allocators, tcmalloc and ptmalloc2. Experiments with SPEC CPU2006 show that NightWatch improves application performance by up to 45 percent (18 percent on average), with an average monitoring overhead of 0.57 percent (up to 3.02 percent).

Cited by 5

Moving Target Defense Against Cache Pollution Attacks in MEC-based Metaverse

Wei Chen, Jiqiang Liu, Tao Zhang et al. · 2025

To realize metaverse services, achieving low latency is essential. Caching content on nodes closer to the users in mobile edge computing (MEC) networks serves as an effective strategy to meet this demand. However, the cache strategy usually leads to cache pollution attack (CPA). CPA causes the edge nodes to be overwhelmed with unpopular content, which results in users not being able to access content from the edge nodes, thus making the latency increase again and affecting the metaverse service. Although existing defense strategies work, they are mostly reactive and suffer from untimely defense. Considering this problem, we divide user-node connections into actual request connection (ARC) and logical cache connection (LCC) and propose a proactive defense policy that selects LCC by analyzing group ARC in each time slot. By shuffling LCC, the policy selects the appropriate node for the content to be cached to achieve attack content aggregation. We model the connection change process as a Markov decision process (MDP), which is then solved by deep reinforcement learning (DRL). Through numerical simulation experiments, the proposed algorithm outperforms the reactive defense strategy.

Cited by 0Open access

Intelligent Cache Pollution Attacks Detection for Edge Computing Enabled Mobile Social Networks

Qichao Xu, Zhou Su, Kuan Zhang et al. · IEEE Transactions on Emerging Topics in Computational Intelligence · 2019

With the rapid advances of wireless technologies and popularization of smart mobile devices, edge-enabled mobile social networks (MSNs) have emerged as a promising network paradigm for mobile users to deliver, share, and exchange contents with each other. By leveraging edge caching technology, various content services can be provided to mobile users for improving their quality of experience (QoE). However, edge caching is vulnerable to cache pollution attacks (CPAttacks) with the result of disruptive content delivery. To tackle this problem, we propose a hidden Markov model (HMM) based CPAttack detection scheme in edge-enabled MSNs. Specifically, we first present the CPAttack model based on observations of attacking behaviors. According to the CPAttack model, the caching state of the edge device is characterized by two parameters-content request rate and cache missing rate. Then, with observation sequence constructed by caching states, we develop an HMM-based detection algorithm to distinguish the CPAttack in the approximately time-invariant content request process. To deal with the lack of training data and dynamic of caching states, an adaptive HMM (AHMM) based algorithm is designed to detect the CPAttack in the time-varying content request process. The simulation results demonstrate that the proposed scheme can efficiently improve edge devices' abilities to sense the CPAttack.

Cited by 21