
Bot detection methods that rely on deep packet inspection (DPI) can be foiled by encryption. Encryption, however, increases entropy. This paper investigates whether adding high-entropy detectors to an existing bot detection tool that uses DPI can restore some of the bot visibility. We present two high-entropy classifiers, and use one of them to enhance BotHunter. Our results show that while BotHunter misses about 50% of the bots when they employ encryption, our high-entropy classifier restores most of its ability to detect bots, even when they use encryption.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 23 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
