860 research outputs found
Dense Moving Fog for Intelligent IoT: Key Challenges and Opportunities
As the ratification of 5G New Radio technology is being completed, enabling
network architectures are expected to undertake a matching effort. Conventional
cloud and edge computing paradigms may thus become insufficient in supporting
the increasingly stringent operating requirements of
\emph{intelligent~Internet-of-Things (IoT) devices} that can move unpredictably
and at high speeds. Complementing these, the concept of fog emerges to deploy
cooperative cloud-like functions in the immediate vicinity of various moving
devices, such as connected and autonomous vehicles, on the road and in the air.
Envisioning gradual evolution of these infrastructures toward the increasingly
denser geographical distribution of fog functionality, we in this work put
forward the vision of dense moving fog for intelligent IoT applications. To
this aim, we review the recent powerful enablers, outline the main challenges
and opportunities, and corroborate the performance benefits of collaborative
dense fog operation in a characteristic use case featuring a connected fleet of
autonomous vehicles.Comment: 7 pages, 5 figures, 1 table. The work has been accepted for
publication in IEEE Communications Magazine, 2019. Copyright may be
transferred without notice, after which this version may no longer be
accessibl
Machine learning and blockchain technologies for cybersecurity in connected vehicles
Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified
A Threat Model for Vehicular Fog Computing
Vehicular Fog Computing (VFC) facilitates the deployment of distributed, latency-aware services, residing between smart vehicles and cloud services. However, VFC systems are exposed to manifold security threats, putting human life at risk. Knowledge on such threats is scattered and lacks empirical validation. We performed an extensive threat assessment by reviewing literature and conducting expert interviews, leading to a comprehensive threat model with 33 attacks and example security mitigation strategies, among others. We thereby synthesize and extend prior research; provide rich descriptions for threats; and raise awareness of physical attacks that underline importance of the cyber-physical manifestation of VFC
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