Design and evaluation of deep packet inspection system: a case study

IET Networks ◽  
2012 ◽  
Vol 1 (1) ◽  
pp. 2-9 ◽  
Author(s):  
M.-Y. Liao ◽  
C.-S. Yang ◽  
M.-Y. Luo ◽  
P.-C. Wu ◽  
C.-H. Chen ◽  
...  
2018 ◽  
Vol 1 (2) ◽  
pp. 79-85
Author(s):  
I Putu Agus Eka Pratama ◽  
Putu Adhika Dharmesta

Deep Packet Inspection (DPI) is a technique commonly used by network administrator to be able to monitor in detail the flow of data in the form of data packets that occur at that moment. This data stream will produce an information that can be used for network management purposes. One example of a case study that can be done with this technique is the intranet that is available in Information Technology major Udayana University’s. Deep Packet Inspection Technique is done with purpose to identifying the initial slowing down of network speed on Information Technology major Udayana University’s.


2010 ◽  
Vol 8 (3) ◽  
pp. 310-322 ◽  
Author(s):  
Andrew McStay

As online advertising moves to the centre-stage of advertisers’ media spend, now surpassing television and press in the UK, it is argued here that critique of advertising practice should pay more careful attention to systems of feedback-oriented production and data-based audience management and creation. This paper thus progresses and updates Dallas Smythe’s (1977) audience-as-commodity argument by examining developments in online behavioural advertising, particularly in regards to the potential for advertising facilitated by deep-packet inspection (DPI) that has caused consternation to technologically savvy consumers, privacy activists and the European Commission. Utilising the case study of Phorm that received national media attention in the UK and policy-maker attention in Europe, this paper highlights key features of DPI-based advertising, non-personally identifiable profiling and their implications for contemporary commercial autopoietic feedback relationships.


2021 ◽  
Vol 7 (1) ◽  
pp. 132-140
Author(s):  
V. Fitsov

Deep packet inspection systems on communication networks are used to identify the application generating a specific traffic flow. The issues related to modeling and design of deep packet inspection systems remain poorly understood. In this paper, a software technique for evaluating the effectiveness of the hardware composition of the servers of the deep packet inspection system is presented, using a mathematical model of such a system and software search methods. The description of the program search by the maximum element method and the Hook - Jeeves method is given. A modernization of the Hook-Jeeves method for a monotonically decreasing function is proposed. Comparison of the methods by the number of search steps is performed.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1637 ◽  
Author(s):  
Wenguang Song ◽  
Mykola Beshley ◽  
Krzysztof Przystupa ◽  
Halyna Beshley ◽  
Orest Kochan ◽  
...  

In this paper, to solve the problem of detecting network anomalies, a method of forming a set of informative features formalizing the normal and anomalous behavior of the system on the basis of evaluating the Hurst (H) parameter of the network traffic has been proposed. Criteria to detect and prevent various types of network anomalies using the Three Sigma Rule and Hurst parameter have been defined. A rescaled range (RS) method to evaluate the Hurst parameter has been chosen. The practical value of the proposed method is conditioned by a set of the following factors: low time spent on calculations, short time required for monitoring, the possibility of self-training, as well as the possibility of observing a wide range of traffic types. For new DPI (Deep Packet Inspection) system implementation, algorithms for analyzing and captured traffic with protocol detection and determining statistical load parameters have been developed. In addition, algorithms that are responsible for flow regulation to ensure the QoS (Quality of Services) based on the conducted static analysis of flows and the proposed method of detection of anomalies using the parameter Hurst have been developed. We compared the proposed software DPI system with the existing SolarWinds Deep Packet Inspection for the possibility of network traffic anomaly detection and prevention. The created software components of the proposed DPI system increase the efficiency of using standard intrusion detection and prevention systems by identifying and taking into account new non-standard factors and dependencies. The use of the developed system in the IoT communication infrastructure will increase the level of information security and significantly reduce the risks of its loss.


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