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Road side units (RSUs) can act as fog nodes to perform data aggregation at the edge of network, which can reduce communication overhead and improve the utilization of network resources. However, because the RSU is public infrastructure, this feature may bring data security and privacy risks in data aggregation. In this paper, we propose a secure multi-subinterval data aggregation scheme, named SMDA, with interval privacy preservation for vehicle sensing systems. Specifically, our scheme combines the 1 - R encoding theory and proxy re-encryption to protect interval privacy, this can ensure that the interval information is only known by the data center, and the RSU can classify the encrypted data without knowing the plaintext of the data and interval information. Meanwhile, our scheme employs the Paillier homomorphic encryption to accomplish data aggregation at the RSU, and the Identity-based batch authentication technology to solve authentication and data integrity. Finally, the security analysis and performance evaluations illustrate the safety and efficiency of our scheme. [ABSTRACT FROM AUTHOR]

Unlike traditional embedded systems that almost have only one criticality level, many complex embedded systems nowadays are mixed-critical and are more and more widely used. There has been a lot of research on mixed-criticality (MC) systems. In this paper, we present a survey on the MC systems on these research. First, we discuss the exaltation of the schedulability of MC systems. As improving schedulability may lead to quality-of-service (QoS) reduction of MS systems. Therefore, we investigate the approaches to solve this problem. Improving QoS of MS systems may inevitably increase the energy consumption. Then, we introduce the researches that take the energy efficiency as a design requirement of MC systems. Few MC systems regard fault-tolerance as the design requirement, thus, we extensively investigate fault-tolerance of MC systems. In addition, we introduce some of the main applications for MC systems. [ABSTRACT FROM AUTHOR]

By advances in cloud storage systems, users have access to the data saved in the cloud and can manipulate the data without limitation of time and place. As the data owner no longer possesses data physically, he is required to ensure the integrity of the data stored in the cloud with the public key given by public key infrastructure (PKI). Thus the security of PKI and certificates are essential. However, there are numerous security risks in the traditional PKI and it is complex to administer the certificates. Certificateless public key cryptography is used in this paper to solve these problems. We also use elliptic curve group to reduce computation overhead. In this paper, we design a certificateless public verification mechanism to check the integrity of data outsourced in the cloud and we further extend it to support a multiuser group by batch verification. Specifically, a public verifier who replaces the data owner to check the integrity in the proposed scheme does not require to manage any certificates during the verification process. Meanwhile, a verifier is not required to download the entire file for integrity checking. Theoretical analyses verify the security of our scheme and experimental results show its efficiency. [ABSTRACT FROM AUTHOR]

Event-driven wireless sensor networks (WSNs) are equipped with the sensor nodes which are able to capture the vital changes in the measurements and report them to the base station. Due to the nature of harsh and unattended environments, it is impossible to install sensor nodes manually. Therefore, a random deployment fashion such as by aircraft is required. However, with high probability, sensor nodes will not have uniform distribution in the environment which will cause “hole” in the network. In another issue, sensor nodes are limited in energy supply and transmission range, and thus an appropriate technique is essential to calculate energy efficient routes to relay data from the sensor nodes to the base station. In hierarchical routing category, clustering techniques attempt to partition the sensor nodes in the network to appropriate groups and select the cluster heads to contact with the base station directly. However, in large scale WSNs, most of the sensor nodes are far from the base station and cannot contact directly. Most of the clustering techniques do not consider how cluster heads can reach to the base station. In our research, A Delaunay triangulation approach is employed to detect holes in the network. Then, due to the overhead of clustering methods to define cluster areas, a virtual gridding scheme is applied to define cluster areas. To overcome uncertainties in the environment, a fuzzy logic-based approach is designed to select appropriate cluster heads and hop-nodes in a distributed manner. The experimental results prove the effectiveness and accuracy of our proposed model and applicability to large scale WSNs. [ABSTRACT FROM PUBLISHER]

How to improve both security and energy efficiency is one of the most prominent issues in wireless sensor networks (WSNs). In this paper, we present a trusted and energy efficient approach for cluster-based WSNs. The approach offers (i) trusted hardware module design; (ii) energy-efficient clustering algorithm; and (iii) network operation. In the cluster-based WSNs, every cluster head is equipped with a designed trusted hardware module (TM) to improve security. Then, for improving the energy efficiency of the network, a trusted hardware based energy efficient clustering (TEEC) algorithm is proposed to select appropriate cluster heads. In the network operation, we use TEEC algorithm to perform clustering and apply TMs to achieve security functions. The analysis shows that our approach does well in resisting the attacks such as data confidentiality attack, data integrity attack, and compromise node attack. In addition, experimental results show that the TEEC algorithm makes more balanced clusters with the variance value of loads around 50% and prolongs the life cycle of the network at least 10% compared to traditional methods. [ABSTRACT FROM AUTHOR]

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach. [ABSTRACT FROM AUTHOR]