2,389 research outputs found
Authentication enhancement in command and control networks: (a study in Vehicular Ad-Hoc Networks)
Intelligent transportation systems contribute to improved traffic safety by facilitating real time communication between vehicles. By using wireless channels for communication, vehicular networks are susceptible to a wide range of attacks, such as impersonation, modification, and replay. In this context, securing data exchange between intercommunicating terminals, e.g., vehicle-to-everything (V2X) communication, constitutes a technological challenge that needs to be addressed. Hence, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. In this challenging scenario, physical (PHY)-layer authentication has gained popularity, which involves leveraging the inherent characteristics of wireless channels and the hardware imperfections to discriminate between wireless devices. However, PHY-layerbased authentication cannot be an alternative to crypto-based methods as the initial legitimacy detection must be conducted using cryptographic methods to extract the communicating terminal secret features. Nevertheless, it can be a promising complementary solution for the reauthentication problem in VANETs, introducing what is known as âcross-layer authentication.â This thesis focuses on designing efficient cross-layer authentication schemes for VANETs, reducing the communication and computation overheads associated with transmitting and verifying a crypto-based signature for each transmission. The following provides an overview of the proposed methodologies employed in various contributions presented in this thesis.
1. The first cross-layer authentication scheme: A four-step process represents this approach: initial crypto-based authentication, shared key extraction, re-authentication via a PHY challenge-response algorithm, and adaptive adjustments based on channel conditions. Simulation results validate its efficacy, especially in low signal-to-noise ratio (SNR) scenarios while proving its resilience against active and passive attacks.
2. The second cross-layer authentication scheme: Leveraging the spatially and temporally correlated wireless channel features, this scheme extracts high entropy shared keys that can be used to create dynamic PHY-layer signatures for authentication. A 3-Dimensional (3D) scattering Doppler emulator is designed to investigate the schemeâs performance at different speeds of a moving vehicle and SNRs. Theoretical and hardware implementation analyses prove the schemeâs capability to support high detection probability for an acceptable false alarm value †0.1 at SNR â„ 0 dB and speed †45 m/s.
3. The third proposal: Reconfigurable intelligent surfaces (RIS) integration for improved authentication: Focusing on enhancing PHY-layer re-authentication, this proposal explores integrating RIS technology to improve SNR directed at designated vehicles. Theoretical analysis and practical implementation of the proposed scheme are conducted using a 1-bit RIS, consisting of 64 Ă 64 reflective units. Experimental results show a significant improvement in the Pd, increasing from 0.82 to 0.96 at SNR = â 6 dB for multicarrier communications.
4. The fourth proposal: RIS-enhanced vehicular communication security: Tailored for challenging SNR in non-line-of-sight (NLoS) scenarios, this proposal optimises key extraction and defends against denial-of-service (DoS) attacks through selective signal strengthening. Hardware implementation studies prove its effectiveness, showcasing improved key extraction performance and resilience against potential threats.
5. The fifth cross-layer authentication scheme: Integrating PKI-based initial legitimacy detection and blockchain-based reconciliation techniques, this scheme ensures secure data exchange. Rigorous security analyses and performance evaluations using network simulators and computation metrics showcase its effectiveness, ensuring its resistance against common attacks and time efficiency in message verification.
6. The final proposal: Group key distribution: Employing smart contract-based blockchain technology alongside PKI-based authentication, this proposal distributes group session keys securely. Its lightweight symmetric key cryptography-based method maintains privacy in VANETs, validated via Ethereumâs main network (MainNet) and comprehensive computation and communication evaluations.
The analysis shows that the proposed methods yield a noteworthy reduction, approximately ranging from 70% to 99%, in both computation and communication overheads, as compared to the conventional approaches. This reduction pertains to the verification and transmission of 1000 messages in total
Modern computing: Vision and challenges
Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
SCALING UP TASK EXECUTION ON RESOURCE-CONSTRAINED SYSTEMS
The ubiquity of executing machine learning tasks on embedded systems with constrained resources has made efficient execution of neural networks on these systems under the CPU, memory, and energy constraints increasingly important. Different from high-end computing systems where resources are abundant and reliable, resource-constrained systems only have limited computational capability, limited memory, and limited energy supply. This dissertation focuses on how to take full advantage of the limited resources of these systems in order to improve task execution efficiency from different aspects of the execution pipeline. While the existing literature primarily aims at solving the problem by shrinking the model size according to the resource constraints, this dissertation aims to improve the execution efficiency for a given set of tasks from the following two aspects. Firstly, we propose SmartON, which is the first batteryless active event detection system that considers both the event arrival pattern as well as the harvested energy to determine when the system should wake up and what the duty cycle should be. Secondly, we propose Antler, which exploits the affinity between all pairs of tasks in a multitask inference system to construct a compact graph representation of the task set for a given overall size budget. To achieve the aforementioned algorithmic proposals, we propose the following hardware solutions. One is a controllable capacitor array that can expand the systemâs energy storage on-the-fly. The other is a FRAM array that can accommodate multiple neural networks running on one system.Doctor of Philosoph
Toward an active CMOS electronics-photonics platform based on subwavelength structured devices
The scaling trend of microelectronics over the past 50 years, quantified by Mooreâs Law, has faced insurmountable bottlenecks, necessitating the use of optical communication with its high bandwidth and energy efficiency to further improve computing performance.
Silicon photonics, compatible with CMOS platform manufacturing, presents a promising means to achieve on-chip optical links, employing highly sensitive microring resonator devices that demand electronic feedback and control due to fabrication variations. Achieving the full potential of both technologies requires tight integration to realize the ultimate benefits of both realms of technology, leading to the convergence of microelectronics and photonics.
A promising approach for achieving this convergence is the monolithic integration of electronics and photonics on CMOS platforms. A critical milestone was reached in 2015 with the demonstration of the first microprocessor featuring photonic I/O (Chen et al, Nature 2015), accomplished by integrating transistors and photonic devices on a single chip using a monolithic CMOS silicon-on-insulator (SOI) platform (GlobalFoundries 45RFSOI, 45 nm SOI process) without process modifications, thus known as the "zero-change" approach. This dissertation focuses on leveraging the fabrication capabilities of advanced monolithic electronic-photonic 45 nm CMOS platforms, specifically high-resolution lithography and small feature size doping implants, to realize photonic devices with subwavelength features that could potentially provide the next leap in integrated optical links performance, beyond microring resonator based links.
Photonic crystal (PhC) nanobeam cavities can support high-quality resonance modes while confining light in a small volume, enhancing light-matter interactions and potentially enabling ultimate efficiencies in active devices such as modulators and photodetectors. However, PhC cavities have been overshadowed by microring resonators due to two challenges. First, their fabrication demands high lithography resolution, which excludes most standard SOI photonic platforms as viable options for creating these devices. Secondly, the standing-wave nature of PhC nanobeam cavities complicates their integration into wavelength-division multiplexing (WDM) optical links, causing unwanted reflections when coupled evanescently to a bus waveguide.
In this work, we present PhC nanobeam cavities with the smallest footprint, largest intrinsic quality factor, and smallest mode volume to be demonstrated to date in a monolithic CMOS platform. The devices were fabricated in a 45 nm monolithic electronicsâphotonics CMOS platform optimized for silicon photonics, GlobalFoundries 45CLO, exhibiting a quality factor in excess of 100,000 the highest among fully cladded PhC nanobeam cavities in any SOI platform. Furthermore to eliminate reflections, we demonstrate an approach using pairs of PhC nanobeam cavities with opposite spatial mode symmetries to mimic traveling-wave-like ring behavior, enabling efficient and seamless WDM link integration. This concept was extended to realize a reflectionless microring resonator unit with two microrings operating as standing-wave cavities. Using this scheme with standing-wave microring resonators could lead to an optimum geometry for microring modulators with interdigitated p-n junctions in terms of modulation efficiency in a manner that allows for straightforward WDM cascading.
This work also presents the first demonstration of resonant-structure-based modulators in the GlobalFoundries 45CLO platform. We report the first-ever demonstration of a PhC modulator in a CMOS platform, featuring a novel design with sub-wavelength contacts on one side allowing it to benefit from the "reflection-less"' architecture. Additionally, we also report the first demonstration of microring modulators. The most efficient devices exhibited electro-optical bandwidths up to 30 GHz, and 25 Gbps non-return-to-zero (NRZ) on-off-keyed (OOK) modulation with 1 dB insertion loss and 3.1 dB extinction ratio.
Finally, as the complexity of silicon photonic systems-on-a-chip (SoC) increases to enable new applications such as low-energy data links, quantum optics, and neuromorphic computing, the need for in-situ characterization of individual components becomes increasingly important. By combining Near-field scanning optical microscopy (NSOM) with a flip-chip post-processing technique, this dissertation demonstrates a method to non-invasively perform NSOM scans of a photonic device within a large-scale CMOS-photonic circuit, without interfering with the performance and packaging of the photonics and electronics, making it a valuable tool for future development of high performance photonic circuits and systems
Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target simulations and modelling of physical phenomena, current needs require in addition data analytics (DA) and artificial intelligence (AI) tasks. However, the development of these workflows is hampered by the lack of proper programming models and environments that support the integration of HPC, DA, and AI, as well as the lack of tools to easily deploy and execute the workflows in HPC systems. To progress in this direction, this paper presents use cases where complex workflows are required and investigates the main issues to be addressed for the HPC/DA/AI convergence. Based on this study, the paper identifies the challenges of a new workflow platform to manage complex workflows. Finally, it proposes a development approach for such a workflow platform addressing these challenges in two directions: first, by defining a software stack that provides the functionalities to manage these complex workflows; and second, by proposing the HPC Workflow as a Service (HPCWaaS) paradigm, which leverages the software stack to facilitate the reusability of complex workflows in federated HPC infrastructures. Proposals presented in this work are subject to study and development as part of the EuroHPC eFlows4HPC project.This work has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 955558. The JU receives support from the European Unionâs Horizon 2020 research and innovation programme and Spain, Germany, France, Italy, Poland, Switzerland and Norway. In Spain, it has received complementary funding from MCIN/AEI/10.13039/501100011033, Spain and the European Union NextGenerationEU/PRTR (contracts PCI2021-121957, PCI2021-121931, PCI2021-121944, and PCI2021-121927). In Germany, it has received complementary funding from the German Federal Ministry of Education and Research (contracts 16HPC016K, 6GPC016K, 16HPC017 and 16HPC018). In France, it has received financial support from Caisse des dĂ©pĂŽts et consignations (CDC) under the action PIA ADEIP (project Calculateurs). In Italy, it has been preliminary approved for complimentary funding by Ministero dello Sviluppo Economico (MiSE) (ref. project prop. 2659). In Norway, it has received complementary funding from the Norwegian Research Council, Norway under project number 323825. In Switzerland, it has been preliminary approved for complimentary funding by the State Secretariat for Education, Research, and Innovation (SERI), Norway. In Poland, it is partially supported by the National Centre for Research and Development under decision DWM/EuroHPCJU/4/2021. The authors also acknowledge financial support by MCIN/AEI /10.13039/501100011033, Spain through the âSevero Ochoa Programme for Centres of Excellence in R&Dâ under Grant CEX2018-000797-S, the Spanish Government, Spain (contract PID2019-107255 GB) and by Generalitat de Catalunya, Spain (contract 2017-SGR-01414). Anna Queralt is a Serra HĂșnter Fellow.With funding from the Spanish government through the âSevero Ochoa Centre of Excellenceâ accreditation (CEX2018-000797-S)
2023-2024 Graduate School Catalog
You and your peers represent more than 67 countries and your shared scholarship spans 140 programs - from business administration and biomedical engineering to history, horticulture, musical performance, marine science, and more. Your ideas and interests will inform public health, create opportunities for art and innovation, contribute to the greater good, and positively impact economic development in Maine and beyond
Systematic approach for the test data generation and validation of ISC/ESC detection methods
Various methods published in recent years for reliable detection of battery faults (mainly internal short circuit (ISC)) raise the question of comparability and cross-method evaluation, which cannot yet be answered due to significant differences in training data and boundary conditions. This paper provides a Monte Carlo-like simulation approach to generate a reproducible, comprehensible and large dataset based on an extensive literature search on common assumptions and simulation parameters. In some cases, these assumptions are quite different from field data, as shown by comparison with experimentally determined values. Two relatively simple ISC detection methods are tested on the generated dataset and their performance is evaluated to illustrate the proposed approach. The evaluation of the detection performance by quantitative measures such as the Youden-index shows a high divergence with respect to internal and external parameters such as threshold level and cell-to-cell variations (CtCV), respectively. These results underline the importance of quantitative evaluations based on identical test data. The proposed approach is able to support this task by providing cost-effective test data generation with incorporation of known factors affecting detection quality
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