If you consider aberrant traffic hit rates ones that are more or equal to two standard deviations away from the mean

odd_http_traffic_patterns.r

# Massage your data into a data frame that provides access by Hour and URI
traffic.df <- parse.log("access.log") #parse.log is left as an exercise for the reader

# Aggregate
uri.hits <- ddply(traffic.df, .(Hour, URI), summarise, Hits=length(URI), .parallel = TRUE)
uri.stats <- ddply(uri.hits, .(URI), summarise, Mean=mean(Hits), Variance=sd(Hits), Total=sum(Hits), .parallel = TRUE)
uri.stats <- join(uri.hits, uri.stats, c("URI"))

# Find two std dev away from mean
uri.bad <- subset(uri.stats, Variance > 0)
uri.bad$Deviations <- (uri.bad$Hits - uri.bad$Mean) / uri.bad$Variance
uri.bad <- subset(uri.bad, Deviations >= 2)
uri.bad <- uri.bad[with(uri.bad, order(-Deviations)), ]