197,920 research outputs found
Joachim von Watt, M. Dr : Consul Reipubl. Sangallensis. 1526
Porträt des Reformators Joachim VadianLaur Halder sc
CrypSH: A Novel IoT Data Protection Scheme Based on BGN Cryptosystem
The Internet of Things (IoT) is an emerging paradigm and has penetrated deeply into our daily life. Due to the seamless connections of the IoT devices with the physical world through the Internet, the IoT applications use the cloud to store and provide ubiquitous access to collected data. Sharing of data with third party services and other users incurs potential risks and leads to unique security and privacy concerns, e.g., data breaches. Existing cryptographic solutions are inapt for resource-constrained IoT devices, because of their significant computational overhead. To address these concerns, we propose a data protection scheme to store the encrypted IoT data in a cloud, while still allowing query processing over the encrypted data. Our proposed scheme features a novel encrypted data sharing scheme based on Boneh-Goh-Nissim (BGN) cryptosystem, with revocation capabilities and in-situ key updates. We perform exhaustive experiments on real datasets, to assess the feasibility of the proposed scheme on the resource constrained IoT devices. The results show the feasibility of our scheme, together with the ability to provide a high level of security. The results also show that our scheme significantly reduces the computation, storage and energy overheads than the best performed scheme in the state-of-the-art
Don't hesitate to share! A novel IoT data protection scheme based on BGN cryptosystem
In cloud-based Internet of Things (IoT), sharing of data with third-party services and other users, inherently incurs potential risk and leads to unique security and privacy concerns. Existing cryptographic solutions ensure the security of IoT data, but due to their significant computational overhead, most of them are not suitable for resource-constrained IoT devices. To address these concerns, we propose a data protection system to store encrypted IoT data in a cloud while still allowing query processing over the encrypted data. More importantly, our proposed system features a novel encrypted data sharing scheme based on Boneh-Goh-Nissim (BGN) cryptosystem, with revocation capabilities and in-situ key update. We perform exhaustive experiments on real datasets, primarily to assess the feasibility of the proposed system on resource-constrained IoT devices. We next measure the computation overhead, storage overhead and throughput. The experimental results show that our system is not only feasible, but also provides a high level of security. Furthermore, the results show that our system is 34% more computationally faster, requires 25% less storage and 15% more throughput than the best performed system in the state-of-the-art
Dynamic Super Round Based Distributed Task Scheduling for UAV Networks
Networks of Unmanned Aerial Vehicles (UAVs) are emerging in many application domains, e.g., military surveillance. To perform collaborative tasks, the involved UAVs exchange several types of information, e.g., sensor data and commands. The major question here is how to schedule the tasks under dynamic traffic flows to provide network services. Existing solutions use the Round-Robin Strategy (RRS), where the tasks are scheduled statistically by dividing the time into fixed-length rounds. However, the RRS wastes significant network and device resources due to task scheduling in each round. This paper proposes DROVE – a novel clustering approach that allows the UAVs for dynamic task scheduling. However, determining the task scheduling is crucial, as it significantly affects several network parameters, e.g., throughput. Therefore, we devise the problem of distributed task scheduling under dynamic traffic flow scenarios to optimize the throughput. We propose a clustering task scheduling algorithm to serve dynamic traffic flows. Particularly, we integrate the dynamic traffic flows into the Lyapunov drift analysis framework, and determine the throughput optimality of our proposed scheduling algorithm. We perform extensive simulations to validate the effectiveness of DROVE. The results show that DROVE outperforms the state-of-the-art solutions in terms of energy consumption, clustering overhead, throughput, end-to-end delay, flow success rate and packet drop rate. </p
Fine Grained Access Control for Relational Databases by Abstract Interpretation
In this paper, we propose an observation-based fine grained access control (OFGAC) mechanism where data are made accessible at various level of abstraction according to their sensitivity level. In this setting, unauthorized users are not able to infer the exact content of the data cell containing confidential information, while they are allowed to get partial information out of it, according to their access rights. The traditional fine grained access control (FGAC) can be seen as a special case of the OFGAC framework
DISC: A novel distributed on-demand clustering protocol for internet of multimedia things
Internet of Multimedia Things (IoMT) are receiving significant attention due to a wide variety of applications, e.g., wildlife habitat monitoring, but they are often highly resource constrained. Compared to Internet of Things, preserving battery power of nodes, and maximizing the lifespan of IoMT are more critical and challenging as sensed data are mostly image/video instead of simple scalar. Recent studies have shown that clustering is an efficient solution to reduce energy consumption. In clusters, the role of each node changes to reduce energy consumption, thereby, prolonging lifespan. In this paper, we address the lifespan maximization problem in IoMT by designing a clustering protocol where clusters are formed dynamically. Specifically, we analyze and solve an optimization problem aiming to maximize the lifespan by reducing the energy consumption among cluster heads. Based on the analysis, we propose a novel DIStributed on-demand Clustering (DISC) protocol. Our cluster head election procedure is not periodic, but adaptive, based on the dynamism of the occurrence of events. This on-demand execution of DISC aims to significantly reduce computation and message overheads. We validate the performance of DISC through extensive experiments. Experimental results show that DISC is 25% more energy balanced and achieves 32% more lifespan as compared to two state-of-the-art solutions
Secure over-the-air software updates in connected vehicles: A survey
Current trends forecast that Over-the-Air (OTA) software updates will be highly significant for future connected vehicles. The OTA update will enable upgrading the vehicle functionalities or bug fixations in the embedded software installed on its Electronic Control Units (ECUs) remotely. The introduction of OTA updates in the automotive industry has brought many advantages for both the Original Equipment Manufacturer (OEM) and the driver/owner. However, in terms of security, OTA updates are highly critical as they need complete access to the in-vehicle communication network. This survey highlights and discusses OTA software updates in the automotive sector, mainly from the security perspective. The major objective of this survey is to deliver a comprehensive outline of various research directions and approaches in OTA update technologies in vehicles. At first, we discuss the connected vehicle technology and then integrate the relationship of OTA update features with the connected vehicle. We further discuss both promising and secure OTA update approaches, that have gained a lot of attention recently. Furthermore, we present a comprehensive comparative study of the existing OTA update approaches on the basis of strengths, weaknesses and evaluation setup. The survey also focuses on the existing vehicle features that support OTA updates, and customer satisfaction and usability. Finally, we identify possible future research directions of OTA updates for automobiles, particularly in the area of security
Secure over-the-air software update for connected vehicles
Current trends forecast that Over-the-Air (OTA) software updates will be highly significant for future connected vehicles. The OTA software updates will enable upgrading vehicle functionalities or bug fixations in embedded software installed on electronic control units remotely. However, in terms of security, OTA updates are highly critical as they need complete access to the in-vehicle communication network. Furthermore, scheduling OTA software updates at a massive scale over a cellular network is highly challenging. This paper proposes STRIDE, a novel technique for secure and scalable software updates using cloud through cellular network. STRIDE ensures end-to-end security using ciphertext-policy attribute-based encryption. To enable fast and reliable distribution of update package, we then propose a software update scheduling algorithm to serve dynamic traffic flow. Particularly, we integrate dynamic traffic flow with the Lyapunov-drift analysis framework, and establish throughput optimality of our proposed scheduling algorithm. We evaluate the performance of STRIDE through extensive experiments. Experimental results show that STRIDE reduces more than 52% computation and storage overheads, 60% propagation delay and increases throughput by 35% than the state-of-the-art solutions, in addition to enjoying the stronger security properties
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