Recent studies estimate that peer-to-peer (p2p) traffic comprises 40-70% of today’s Internet traffic [1]. Surprisingly, the impact of p2p traffic on anomaly detection has not been investigated. In this paper, we collect and use a labeled dataset containing diverse network anomalies (portscans, TCP floods, UDP floods, at varying rates) and p2p traffic (encrypted and unencrypted with BitTorrent, ...

Intrusion detection systems (IDS) have a vital role in protecting computer networks and information systems. In this paper, we propose a method for identifying abnormal traffic behaviour based on entropy and support vector machine. Main challenge is to distinguish between normal traffic and attack traffic since there is no major difference between normal and attack traffic. Our objective is to ...

The Command and Control communication of a botnet is evolving into sophisticated covert communication. Techniques as encryption, steganography, and recently the use of social network websites as a proxy, impede conventional detection of botnet communication. In this paper we propose detection of covert communication by passive hostexternal analysis of causal relationships between traffic flows ...

Wireless sensor network (WSN) has emerged as a promising technology thanks to the recent advances in electronics, networking, and information technologies. However, there is still a great deal of additional research required before it finally becomes a mature technology. This article concentrates on three factors which are holding back the development of WSNs. Firstly, there is a lack of traffi...

Network attacks often employ scanning to locate vulnerable hosts and services. Unimpeded scanning can lead to the subversion of an entire vulnerable population in a matter of minutes. Fast and accurate detection of local scanners is key to contain a spreading epidemic in its early stage. Existing scan detection schemes can detect fast scanners whose behavior can be clearly delineated from that ...

In this paper, we discuss the validity of the multi-scale gamma model and characterize the differences in host-level application traffic with this model by using a real traffic trace collected on a 150-Mbps transpacific link. First, we investigate the dependency of the model (parameters α and β, and fitting accuracy ) on time scale Δ, then find suitable time scales for the model. Second, we ins...

With the development of social economy and city urbanization, city road traffic network has developed rapidly, great convenience for people's travel, but also led to a sharp increase in traffic demand. The direct consequence is the rapid expansion of traffic flow, traffic-jam, the city has becoming increasingly serious, frequent traffic accidents. The worsening traffic environment has become a ...

It is important to know the road traffic density real time especially in mega cities for signal control and effective traffic management. In recent years, video monitoring and surveillance systems have been widely used in traffic management. Hence, traffic density estimation and vehicle classification can be achieved using video monitoring systems. In most vehicle detection methods in the liter...

Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, we present a Chinese traffic sign detection algorithm base...

This study was carried out to analyze the variations of Benzene, Toluene, and para- Xylene (BTp-X) present in the urban air of Delhi. These pollutants can enter into the human body through various pathways like inhalation, oral and dermal exposure posing adverse effects on human health. Keeping in view of the above facts, six different locations of Delhi were selected for the study during summe...