布隆过滤器是安全和隐私的坏选择吗?

Ripon Patgiri, Sabuzima Nayak, Naresh Babu Muppalaneni
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引用次数: 13

摘要

今天,数以百万计的设备向服务器发出数十亿个网络请求。所有这些请求包都需要进行安全扫描。因此,为了保证网络安全和隐私,需要对数据包进行过滤和重复数据删除。在过滤的情况下,布隆过滤器数据结构是最好的选择。Bloom Filter是一种用于成员过滤的概率数据结构,它能够使用较小的内存占用来过滤大量数据。然而,由于其假阳性和假阴性问题,布隆过滤器在许多应用中并不受欢迎。目前,许多网络安全和隐私技术都在实现布隆过滤器。本文讨论了关于布隆过滤器的各种事实。我们主张布隆过滤器是网络安全和隐私的第一层防御。此外,我们讨论了布隆过滤器如何提供更好的安全性,以抵御各种网络攻击。
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Is Bloom Filter a Bad Choice for Security and Privacy?
Today, millions of devices produce billions of network requests to the servers. All these request packets need to be scanned for security. Hence, providing network security and privacy requires filtering and deduplication of packets. In case of filtering, Bloom Filter data structure is the best alternative. Bloom Filter is a probabilistic data structure for membership filtering and it is capable of filtering massive amounts of data using a small memory footprint. However, Bloom Filter is not popular in many applications due to its false positive and false negative issues. Currently, many network security and privacy techniques are implementing Bloom Filter. In this paper, we discuss various facts on Bloom Filter. We advocate that Bloom Filter is the first layer of defence for network security and privacy. Furthermore, we discuss how Bloom Filter provides better security against various network attacks.
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