User-Centric Secure Data Sharing: Exploration of Concepts and Values

Data we handle and generate when using Internet-based services reveals information on our behavior and values. Access control to this data most often lies in the hands of service or storage providers. With regard to the value ladenness of data sharing in particular, we propose to shift the focus back to the user by introducing the concept of User-Centric Secure Data Sharing (UC-SDS). The UC-SDS approach aims at combining technologies and methodologies from the fields of secure data sharing, secure data outsourcing and value-oriented design. In this paper, we discuss design alternatives using the example of car telemetry data, considering their value interdependencies with particular emphasis on the legal context. Our work indicates that through combination of available building blocks, a higher level of user-centricity in access control is possible than we are used to today

Secure Intelligent Vehicular Network Including Real-Time Detection of DoS Attacks in IEEE 802.11P Using Fog Computing

VANET (Vehicular ad hoc network) has a main objective to improve driver safety and traffic efficiency. Intermittent exchange of real-time safety message delivery in VANET has become an urgent concern, due to DoS (Denial of service), and smart and normal intrusions (SNI) attacks. Intermittent communication of VANET generates huge amount of data which requires typical storage and intelligence infrastructure. Fog computing (FC) plays an important role in storage, computation, and communication need. In this research, Fog computing (FC) integrates with hybrid optimization algorithms (OAs) including: Cuckoo search algorithm (CSA), Firefly algorithm (FA) and Firefly neural network, in addition to key distribution establishment (KDE), for authenticating both the network level and the node level against all attacks for trustworthiness in VANET. The proposed scheme which is also termed “Secure Intelligent Vehicular Network using fog computing” (SIVNFC) utilizes feedforward back propagation neural network (FFBP-NN). This is also termed the firefly neural, is used as a classifier to distinguish between the attacking vehicles and genuine vehicles. The proposed scheme is initially compared with the Cuckoo and FA, and the Firefly neural network to evaluate the QoS parameters such as jitter and throughput. In addition, VANET is a means whereby Intelligent Transportation System (ITS) has become important for the benefit of daily lives. Therefore, real-time detection of all form attacks including hybrid DoS attacks in IEEE 802.11p, has become an urgent attention for VANET. This is due to sporadic real-time exchange of safety and road emergency message delivery in VANET. Sporadic communication in VANET has the tendency to generate enormous amount of message. This leads to the RSU (roadside unit) or the CPU (central processing unit) overutilization for computation. Therefore, it is required that efficient storage and intelligence VANET infrastructure architecture (VIA), which include trustworthiness is desired. Vehicular Cloud and Fog Computing (VFC) play an important role in efficient storage, computations, and communication need for VANET. This dissertation also utilizes VFC integration with hybrid optimization algorithms (OAs), which also possess swarm intelligence including: Cuckoo/CSA Artificial Bee Colony (ABC) Firefly/Genetic Algorithm (GA), in additionally to provide Real-time Detection of DoS attacks in IEEE 802.11p, using VFC for Intelligent Vehicular network. Vehicles are moving with certain speed and the data is transmitted at 30Mbps. Firefly FFBPNN (Feed forward back propagation neural network) has been used as a classifier to also distinguish between the attacked vehicles and the genuine vehicle. The proposed scheme has also been compared with Cuckoo/CSA ABC and Firefly GA by considering Jitter, Throughput and Prediction accuracy

Secure data sharing for vehicular ad-hoc networks using cloud computing

During the last decade, researchers and developers have been attracted to Vehicular Ad-hoc Network (VANET) research area due to its significant applications, including efficient traffic management, road safety, and entertainment. Several resources such as communication, onboard unit, storage, computing, and endless battery are embedded in the vehicles, which are used for enhancing Intelligent Transportation Systems (ITSs). One of the crucial challenges for VANETs is to securely share an important information among vehicles. In some cases, the data owner is also not available and unable to control the data sharing process, i.e., sharing data with a new user or revoking the existing user. In this paper, we present a new method to address the data sharing problem and delegate the management of data to a Trusted Third Party (TPA) based on bilinear pairing technique. To achieve this goal, we use a cloud computing, as the mainstream platform of utility computing paradigm, to store the huge amount of data and perform the re-encryption process securely