scholarly journals Research on OS fingerprinting Method for Real-time Traffic Analysis System

2011 ◽  
Vol 36 (5B) ◽  
pp. 443-450 ◽  
Author(s):  
Hyun-Shin Lee ◽  
Myung-Sup Kim
Keyword(s):  
Real Time ◽  
Traffic Analysis ◽  
Real Time Traffic ◽  
Fingerprinting Method ◽  
Analysis System

Vietnamese vehicles speed detection with video-based and deep learning for real-time traffic flow analysis system

2021 ◽  
Author(s):  
Phuoc Ha Quang ◽  
Phong Pham Thanh ◽  
Tuan Nguyen Van Anh ◽  
Son Vo Phi ◽  
Binh Le Nhat ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Traffic Flow ◽  
Flow Analysis ◽  
Real Time Traffic ◽  
Analysis System ◽  
Traffic Flow Analysis

Real-Time Traffic Analysis and Dynamic Passthrough Time for Lanes based on Density of Traffic

2020 ◽  
Vol V9 (02) ◽  
Author(s):  
Sujithra L.R ◽  
Vibin Kishore H ◽  
Swathi S ◽  
Pradeep Kumar G, Priya Darsini S ◽  
Keyword(s):  
Real Time ◽  
Traffic Analysis ◽  
Real Time Traffic

Real-time traffic analysis at night-time

2011 ◽  
Author(s):  
Jose M. Mossi ◽  
Alberto Albiol ◽  
Antonio Albiol ◽  
Valery Naranjo Ornedo
Keyword(s):  
Real Time ◽  
Traffic Analysis ◽  
Night Time ◽  
Real Time Traffic

Correlation based malicious traffic analysis system

2021 ◽  
Vol 25 (2) ◽  
pp. 195-200
Author(s):  
D. Arivudainambi ◽  
K.A. Varun Kumar ◽  
Suresh Chandra Satapathy
Keyword(s):  
Nearest Neighbor ◽  
Traffic Analysis ◽  
Classification Performance ◽  
Cyber Attacks ◽  
Traffic Classification ◽  
Traffic Data ◽  
The Past ◽  
Real Time Traffic ◽  
Analysis Scheme ◽  
Analysis System

Artificial intelligence methods have often been applied to carry out specific functions or errands in the cyber-defense realm. However, as adversary methods become more complex and difficult to divine, piecemeal efforts to understand cyber-attacks, and malware-based attacks in particular, are not providing sufficient means for malware analysts to understand the past, present and future distinctiveness of malware. Because, most of the malware communications take place-utilizing services. These services are completely anonymous and monitoring such services is a hard task. To address this issue, this paper proposes a novel traffic analysis scheme using correlation methods (non-parametric approach). Experiments are performed to validate the proposed approach on the real time traffic data collected over the period of 1 week. The experimental results confirm that the proposed method outperforms the existing state of the art traffic analysis schemes. The result also exhibits the traffic classification performance, which is analyzed by the decade old nearest neighbor method.

A Fast Connection Construction and Update Algorithm

2013 ◽  
Vol 712-715 ◽  
pp. 2506-2509
Author(s):  
Feng Liu
Keyword(s):  
Real Time ◽  
Heavy Traffic ◽  
Hash Table ◽  
Traffic Analysis ◽  
Internet Traffic ◽  
Research Area ◽  
The Internet ◽  
Traffic Flows ◽  
Real Time Traffic ◽  
Traffic Environment

In the research area of network security, we often need to analyze the Internet traffic in real time. But the Internet traffic is usually very heavy, so it is very hard for us to analysis each packet one by one. Alternatively, analyzing the Internet traffic on flow level is often employed. Before analyzing the traffic flows, how we can fast construct and update these flows is a key issue. To solve this issue, in this paper, we propose a fast connection construction and update algorithm. Firstly, we define bidirectional flows as connection. Then, we use hash table to store the connection records and use this connection construction and update algorithm to ensure that these connection records can to be stored in memory in heavy traffic environment to achieve real-time traffic analysis. At last, the experiments show that the algorithm we proposed is efficient and can meet the traffic analysis need.

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