A common belief in designing deep autoencoders (AEs), a type of unsupervised neural network, is that bottleneck required to prevent learning the identity function. Learning function renders AEs useless for anomaly detection. In this work, we challenge limiting and investigate value non-bottlenecked AEs. The can be removed two ways: (1) overparameterising latent layer, (2) introducing skip conne...

One of the most important methods to solve traffic congestion is to detect the incident state of a roadway. This paper describes the development of a method for road traffic monitoring aimed at the acquisition and analysis of remote sensing imagery. We propose a strategy for road extraction, vehicle detection and incident detection from remote sensing imagery using techniques based on neural ne...

This paper analyzes the properties of packet interarrival time (PIT) distribution fimctions of network segments including bottlenecks. In order to show the correlation between bottleneck behavior and packet interarrival time distribution, the alteration of probability distribution f~~nc t ion (PDF) is observed through simulations including tighter and tighter bottleneck connections. The process...

In this paper we evaluate four different metrics for non intrusive bottleneck detection based on TCP counters. Three using a reference and one being reference free. This work is based on the full TCP statistics recorded on five days over the last one and a half year within the live core network of a mobile network operator in Austria. We used two of the datasets, which had a known bottleneck in...

A new low-complexity approach to intrusion detection called "bottleneck verification" was developed which can find novel attacks with low false alarm rates. Bottleneck verification is a general approach to intrusion detection designed specifically for systems where there are only a few legal "bottleneck" methods to transition to a higher privilege level and where it is relatively easy to determ...

Bottleneck detection in manufacturing is the key to improving production efficiency and stability in order to improve capacity. Yet common bottleneck detection methods in industry and academia lack either accuracy or practicability, or both, for dynamic systems. The new methodology is conducted by the observation of processes and inventories. Blocked processes and full inventories indicate a do...

As computer networks and associated infrastructures become ever more important to the nation’s commerce and communication, it is becoming exceedingly critical that these networks be managed effectively. Current techniques, which rely on manual or log based analysis, are too slow and ineffective to handle the explosive growth of network infrastructures. We have developed visualization techniques...