Ing. Yelena Trofimova, Ph.D.

Publikace

Decentralized Evaluation of Trust in Ad Hoc Networks using Neural Networks

Rok
2022
Publikováno
2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). USA: IEEE Computer Society, 2022. p. 30-35. ISSN 2160-4894. ISBN 978-1-6654-6975-3.
Typ
Stať ve sborníku
Anotace
Trust is an essential concept in ad hoc network security. Creating and maintaining trusted relationships between nodes is a challenging task. This paper proposes a decentralized method for evaluating trust in ad hoc networks. The method uses neural networks and local information to predict the trust of neighboring nodes. The method was compared with the original centralized version, showing that even without global information knowledge, the method has, on average, 97% accuracy in classification and 94% in regression problem. An important contribution of this paper is overcoming the main limitation of the original method, which is the centralized evaluation of trust. Moreover, the decentralized method output is a perfect fit to use as an input to enhance routing in ad hoc networks.

Enhancing Reactive Ad Hoc Routing Protocols with Trust

Rok
2022
Publikováno
Future Internet. 2022, 14(1), ISSN 1999-5903.
Typ
Článek
Anotace
In wireless ad hoc networks, security and communication challenges are frequently addressed by deploying a trust mechanism. A number of approaches for evaluating trust of ad hoc network nodes have been proposed, including the one that uses neural networks. We proposed to use packet delivery ratios as input to the neural network. In this article, we present a new method, called TARA (Trust-Aware Reactive Ad Hoc routing), to incorporate node trusts into reactive ad hoc routing protocols. The novelty of the TARA method is that it does not require changes to the routing protocol itself. Instead, it influences the routing choice from outside by delaying the route request messages of untrusted nodes. The performance of the method was evaluated on the use case of sensor nodes sending data to a sink node. The experiments showed that the method improves the packet delivery ratio in the network by about 70%. Performance analysis of the TARA method provided recommendations for its application in a particular ad hoc network.

Are Encypted Protocols Really a Guarantee of Privacy?

Rok
2021
Publikováno
Proceedings of 20th European Conference on Cyber Warfare and Security ECCWS 2021. Academic Conferences International Limited Reading, 2021. p. 130-138. 20. vol. 1. ISBN 978-1-912764-99-0.
Typ
Stať ve sborníku
Anotace
Most internet traffic is being encrypted by application protocols that should guarantee users' privacy and anonymity of data during the transmission. Our team has developed a unique system that can create a specific pattern of traffic and further analyze it by using machine learning methods. We investigated the possibility of identifying the network video streams encrypted within the HTTPS protocol and explored that it is possible to identify a particular content with a certain probability. Our paper provides a methodology and results retrieved from the real measurements. As the testing data set, we used the streams coming from the popular platform Youtube. Our results confirm that it is possible to identify encrypted video streams via their specific traffic imprints, although it should not be possible due to the used encryption.

Performance Analysis of Neural Network Approach for Evaluation of Trust in Ad-Hoc Networks

Rok
2021
Publikováno
11th International Conference on Advanced Computer Information Technologies (ACIT). IEEE (Institute of Electrical and Electronics Engineers), 2021. p. 691-695. ISBN 978-1-6654-1854-6.
Typ
Stať ve sborníku
Anotace
With the world becoming more mobile and dynamic each year, the application of ad-hoc networks has broadened. Ad-hoc networks do not have a predefined infrastructure; each node serves as a router, bringing security challenges. Trust and trustworthiness mechanisms are among the most common methods for ensuring security in an ad-hoc network. In [1], we proposed a method for the evaluation of trust in ad-hoc networks. This paper aims to describe the method formally and analyze its performance. The original paper showed that neural networks could do trust estimation with an average 98% accuracy of the classification and 94% of the regression problem. This paper aims to investigate the capabilities of our method under malicious conditions. The analysis could also provide insight for tuning trust parameters, such as the threshold of trust. Furthermore, this paper presents a mathematical model behind the problem to show that the neural network approach is reasonable.

Application of neural networks for decision making and evaluation of trust in ad-hoc networks

Rok
2017
Publikováno
13th International Wireless Communications and Mobile Computing Conference(IWCMC). IEEE, 2017. p. 371-377. ISSN 2376-6492. ISBN 978-1-5090-4372-9.
Typ
Stať ve sborníku
Anotace
In this paper, we demonstrate that neural networks (NNs) are capable of trust estimation and evaluation in ad-hoc networks. The concept of trust in distributed systems arose from the notion of social trust. By the trust problem, we understand the problem of measuring the confidence in the fact that individual nodes behave correctly. We model trust in ad-hoc networks using the packet delivery ratio (PDR) metric. We have developed a method to apply NNs for solving the trust problem in ad-hoc networks. We have conducted a series of simulation experiments and measured the quality of our new method. The results show in average 98% accuracy of the classification and 94% of the regression problem. An important contribution of our research is a verification of the hypothesis that synthetic generation of ad-hoc network traffic in a simulator is sufficient for training of a NN that is then capable to accurately estimate trust in an ad-hoc network.