International Symposium Mobile Internet Security 

About: International Symposium Mobile Internet Security is an academic conference. The conference publishes majorly in the area(s): Authentication & Encryption. Over the lifetime, 42 publications have been published by the conference receiving 59 citations.

An SDN-Based Secure Mobility Model for UAV-Ground Communications

Abstract: Multi-UAV collaborative networks provide with the opportunity to exploit civil, chemical, biological, radiological, nuclear and geographical reconnaissance, survey, management, and control. For the collaborative network formation, coverage is of prime paramountcy. Alongside coverage, possession of information and communication security is withal a major challenge. The coverage quandary can be resolved by a perspicacious selection of UAV waypoints. But the security paradigm which can be an effect of faulty node, intrusion or even choice of erroneous communication channels needs to be taken care of through efficacious strategies. Consequently, both a specialized UAV mobility model and a security mechanism are required in order to establish prosperous collaborative networks. In this article, an SDN-based secure mobility model is proposed which takes into account the topological density and restricts the UAV and ground node (Wireless Sensor Networks (WSNs)) transmissions to authenticity. Significant gains are observed for throughput, coverage, and latency by establishing a simulated network between multiple UAVs and WSN motes.

User Keystroke Authentication Based on Convolutional Neural Network

Abstract: Biometric authentication technology has become an important measure to protect user information security. Among them, keystroke authentication technology has attracted the attention of many researchers because of its low cost and high benefit. In recent years, various methods such as statistical methods and integrated models have been increasingly used in user keystroke authentication and have achieved relatively good results. However, few people try to convert keystroke data into images and tap spatial information between keystroke data. In this paper, we used a new way to convert keystroke data into images, then we use a binary model based on a Convolutional Neural Network (CNN) for each genuine user and try to import the transformed images into the CNN model. In this way, we can dig out the “spatial information” of keystroke features, which is the advantage over other models, and this method is first proposed for keystroke behavior authentication. In addition, we have also tried data augmentation, relu activation functions and dropout methods to reduce overfitting. In the end, we got an accuracy of 96.8%, which is about 10% higher than the previous work.

Improved Security Schemes for Efficient Traffic Management in Vehicular Ad-Hoc Network

Abstract: With day to day exponential increase in the number of private vehicles, it is essential to communicate useful travel information for road travellers to plan their travel ahead. One of the recent technologies that aid in real time and faster communication is Vehicular Ad-hoc Network (VANET). There are several useful information that can be transmitted across the smart vehicle users of VANET infrastructure. The useful information may be related to vehicular traffic, safety measures or entertainment which requires authenticity, confidentiality, anonymity and availability. This paper proposes a secure scheme for such information in order to provide an improved road traffic management applications of VANET. In specific, the proposed model mainly focuses on: (i) a decision scheme to analyse the road traffic situation (ii) using Video Image processing based infrastructure coupled with VANET (VIMPROS-V) to enumerate and authenticate the information communicated during critical traffic situation. The proposed model is applied for real time Traffic Congestion (TraCo) estimation application and tested by simulating similar traffic conditions corresponding to a real time traffic video.

Assessment of Computer Network Resilience Under Impact of Cyber Attacks on the Basis of Stochastic Networks Conversion

Abstract: The paper suggests an approach to computer network resilience assessment under exposure of cyber attacks, based on analytical attack modeling using the method of stochastic networks transformations. The network resilience assessment methodology and main stages of the proposed method for analytical modeling of cyber attacks are studied. It is shown how the proposed method can be used to generate the reference analytical model of the computer attack. Experimental evaluation of the proposed method for analytical modeling of attacks and developed methodology for assessing resilience of the network under exposure of cyber attacks showed high adequacy of the obtained results and high efficiency of their calculation.

Analysis of Attack Actions on the Railway Infrastructure Based on the Integrated Model

Abstract: In this paper we present analysis of attack actions on the railway infrastructure based on the integrated model. The novelty of the presented solution is in combination of the component-based approach, which is used to detect attack vectors based on the presence of vulnerabilities, the semi-natural model, which is used to model vulnerabilities exploitation, the simulation model, which is used to analyze attack scenarios that are affecting timetable planning process and the analytical model, which is used to analyze multi-step attack scenarios. The integrated model also contains the model of attacker, which distinguish them by type of access to the railway infrastructure as well as by level of capabilities and resources. The integrated model is used due to the fact that none of the listed approaches can effectively analyze all classes of attacks, while combining these approaches allows one to represent various aspects of the investigated object and provides the ability for attack actions effective analysis. The proposed solution has a strong focus on security, which determines the main contribution to the research field. The objective of the proposed model is to increase the security of critical infrastructure by improving the quality of attack actions analysis. The correctness of the proposed model is validated by various application examples.