56,177 research outputs found

    Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications

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    Social Virtual Reality based Learning Environments (VRLEs) such as vSocial render instructional content in a three-dimensional immersive computer experience for training youth with learning impediments. There are limited prior works that explored attack vulnerability in VR technology, and hence there is a need for systematic frameworks to quantify risks corresponding to security, privacy, and safety (SPS) threats. The SPS threats can adversely impact the educational user experience and hinder delivery of VRLE content. In this paper, we propose a novel risk assessment framework that utilizes attack trees to calculate a risk score for varied VRLE threats with rate and duration of threats as inputs. We compare the impact of a well-constructed attack tree with an adhoc attack tree to study the trade-offs between overheads in managing attack trees, and the cost of risk mitigation when vulnerabilities are identified. We use a vSocial VRLE testbed in a case study to showcase the effectiveness of our framework and demonstrate how a suitable attack tree formalism can result in a more safer, privacy-preserving and secure VRLE system.Comment: Tp appear in the CCNC 2019 Conferenc

    On the security of software-defined next-generation cellular networks

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    In the recent years, mobile cellular networks are ndergoing fundamental changes and many established concepts are being revisited. Future 5G network architectures will be designed to employ a wide range of new and emerging technologies such as Software Defined Networking (SDN) and Network Functions Virtualization (NFV). These create new virtual network elements each affecting the logic of the network management and operation, enabling the creation of new generation services with substantially higher data rates and lower delays. However, new security challenges and threats are also introduced. Current Long-Term Evolution (LTE) networks are not able to accommodate these new trends in a secure and reliable way. At the same time, novel 5G systems have proffered invaluable opportunities of developing novel solutions for attack prevention, management, and recovery. In this paper, first we discuss the main security threats and possible attack vectors in cellular networks. Second, driven by the emerging next-generation cellular networks, we discuss the architectural and functional requirements to enable appropriate levels of security

    Data mining based cyber-attack detection

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