اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدA Trusted and Privacy-preserving Internet of Mobile Energy
89
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The rapid growth in distributed energy sources on power grids leads to increasingly decentralised energy management systems for the prediction of power supply and demand and the dynamic setting of an energy price signal. Within this emerging smart grid paradigm, electric vehicles can serve as consumers, transporters, and providers of energy through two-way charging stations, which highlights a critical feedback loop between the movement patterns of these vehicles and the state of the energy grid. This paper proposes a vision for an Internet of Mobile Energy (IoME), where energy and information flow seamlessly across the power and transport sectors to enhance the grid stability and end user welfare. We identify the key challenges of trust, scalability, and privacy, particularly location and energy linking privacy for EV owners, for realising the IoME vision. We propose an information architecture for IoME that uses scalable blockchain to provide energy data integrity and authenticity, and introduces one-time keys for public EV transactions and a verifiable anonymous trip extraction method for EV users to share their trip data while protecting their location privacy. We present an example scenario that details the seamless and closed loop information flow across the energy and transport sectors, along with a blockchain design and transaction vocabulary for trusted decentralised transactions. We finally discuss the open challenges presented by IoME that can unlock significant benefits to grid stability, innovation, and end user welfare.
قيم البحث
اقرأ أيضاً
With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for real-time data processing and analysis has emerged as an essential pre-requite for customers satisfaction. In this direction, Mobile Edge Com
puting (MEC) provides seamless services with reduced latency, enhanced mobility, and improved location awareness. Since MEC has evolved from Cloud Computing, it inherited numerous security and privacy issues from the latter. Further, decentralized architectures and diversified deployment environments used in MEC platforms also aggravate the problem; causing great concerns for the research fraternity. Thus, in this paper, we propose an efficient and lightweight mutual authentication protocol for MEC environments; based on Elliptic Curve Cryptography (ECC), one-way hash functions and concatenation operations. The designed protocol also leverages the advantages of discrete logarithm problems, computational Diffie-Hellman, random numbers and time-stamps to resist various attacks namely-impersonation attacks, replay attacks, man-in-the-middle attacks, etc. The paper also presents a comparative assessment of the proposed scheme relative to the current state-of-the-art schemes. The obtained results demonstrate that the proposed scheme incurs relatively less communication and computational overheads, and is appropriate to be adopted in resource constraint MEC environments.
With an enormous range of applications, Internet of Things (IoT) has magnetized industries and academicians from everywhere. IoT facilitates operations through ubiquitous connectivity by providing Internet access to all the devices with computing cap
abilities. With the evolution of wireless infrastructure, the focus from simple IoT has been shifted to smart, connected and mobile IoT (M-IoT) devices and platforms, which can enable low-complexity, low-cost and efficient computing through sensors, machines, and even crowdsourcing. All these devices can be grouped under a common term of M-IoT. Even though the positive impact on applications has been tremendous, security, privacy and trust are still the major concerns for such networks and an insufficient enforcement of these requirements introduces non-negligible threats to M-IoT devices and platforms. Thus, it is important to understand the range of solutions which are available for providing a secure, privacy-compliant, and trustworthy mechanism for M-IoT. There is no direct survey available, which focuses on security, privacy, trust, secure protocols, physical layer security and handover protections in M-IoT. This paper covers such requisites and presents comparisons of state-the-art solutions for IoT which are applicable to security, privacy, and trust in smart and connected M-IoT networks. Apart from these, various challenges, applications, advantages, technologies, standards, open issues, and roadmap for security, privacy and trust are also discussed in this paper.
This paper describes a new architecture for transient mobile networks destined to merge existing and future network architectures, communication implementations and protocol operations by introducing a new paradigm to data delivery and identification
. The main goal of our research is to enable seamless end-to-end communication between mobile and stationary devices across multiple networks and through multiple communication environments. The architecture establishes a set of infrastructure components and protocols that set the ground for a Persistent Identification Network (PIN). The basis for the operation of PIN is an identification space consisting of unique location independent identifiers similar to the ones implemented in the Handle system. Persistent Identifiers are used to identify and locate Digital Entities which can include devices, services, users and even traffic. The architecture establishes a primary connection independent logical structure that can operate over conventional networks or more advanced peer-to-peer aggregation networks. Communication is based on routing pools and novel protocols for routing data across several abstraction levels of the network, regardless of the end-points current association and state...
Privacy and security-related concerns are growing as machine learning reaches diverse application domains. The data holders want to train with private data while exploiting accelerators, such as GPUs, that are hosted in the cloud. However, Cloud syst
ems are vulnerable to attackers that compromise the privacy of data and integrity of computations. This work presents DarKnight, a framework for large DNN training while protecting input privacy and computation integrity. DarKnight relies on cooperative execution between trusted execution environments (TEE) and accelerators, where the TEE provides privacy and integrity verification, while accelerators perform the computation heavy linear algebraic operations.
Location-based queries enable fundamental services for mobile road network travelers. While the benefits of location-based services (LBS) are numerous, exposure of mobile travelers location information to untrusted LBS providers may lead to privacy b
reaches. In this paper, we propose StarCloak, a utility-aware and attack-resilient approach to building a privacy-preserving query system for mobile users traveling on road networks. StarCloak has several desirable properties. First, StarCloak supports user-defined k-user anonymity and l-segment indistinguishability, along with user-specified spatial and temporal utility constraints, for utility-aware and personalized location privacy. Second, unlike conventional solutions which are indifferent to underlying road network structure, StarCloak uses the concept of stars and proposes cloaking graphs for effective location cloaking on road networks. Third, StarCloak achieves strong attack-resilience against replay and query injection-based attacks through randomized star selection and pruning. Finally, to enable scalable query processing with high throughput, StarCloak makes cost-aware star selection decisions by considering query evaluation and network communication costs. We evaluate StarCloak on two real-world road network datasets under various privacy and utility constraints. Results show that StarCloak achieves improved query success rate and throughput, reduced anonymization time and network usage, and higher attack-resilience in comparison to XStar, its most relevant competitor.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
