Spectrum Sharing, Latency, and Security in 5G Networks with Application to IoT and Smart Grid

The surge of mobile devices, such as smartphones, and tables, demands additional capacity. On the other hand, Internet-of-Things (IoT) and smart grid, which connects numerous sensors, devices, and machines require ubiquitous connectivity and data security. Additionally, some use cases, such as automated manufacturing process, automated transportation, and smart grid, require latency as low as 1 ms, and reliability as high as 99.99\%. To enhance throughput and support massive connectivity, sharing of the unlicensed spectrum (3.5 GHz, 5GHz, and mmWave) is a potential solution. On the other hand, to address the latency, drastic changes in the network architecture is required. The fifth generation (5G) cellular networks will embrace the spectrum sharing and network architecture modifications to address the throughput enhancement, massive connectivity, and low latency. To utilize the unlicensed spectrum, we propose a fixed duty cycle based coexistence of LTE and WiFi, in which the duty cycle of LTE transmission can be adjusted based on the amount of data. In the second approach, a multi-arm bandit learning based coexistence of LTE and WiFi has been developed. The duty cycle of transmission and downlink power are adapted through the exploration and exploitation. This approach improves the aggregated capacity by 33\%, along with cell edge and energy efficiency enhancement. We also investigate the performance of LTE and ZigBee coexistence using smart grid as a scenario. In case of low latency, we summarize the existing works into three domains in the context of 5G networks: core, radio and caching networks. Along with this, fundamental constraints for achieving low latency are identified followed by a general overview of exemplary 5G networks. Besides that, a loop-free, low latency and local-decision based routing protocol is derived in the context of smart grid. This approach ensures low latency and reliable data communication for stationary devices. To address data security in wireless communication, we introduce a geo-location based data encryption, along with node authentication by k-nearest neighbor algorithm. In the second approach, node authentication by the support vector machine, along with public-private key management, is proposed. Both approaches ensure data security without increasing the packet overhead compared to the existing approaches

Data Leakage in Isolated Virtualized Enterprise Computing Systems

Virtualization and cloud computing have become critical parts of modern enterprise computing infrastructure. One of the benefits of using cloud infrastructure over in-house computing infrastructure is the offloading of security responsibilities. By hosting one’s services on the cloud, the responsibility for the security of the infrastructure is transferred to a trusted third party. As such, security of customer data in cloud environments is of critical importance. Side channels and covert channels have proven to be dangerous avenues for the leakage of sensitive information from computing systems. In this work, we propose and perform two experiments to investigate side and covert channel possibilities in virtual, enterprise environments. The first experiment is centered around the use of sensor data available via Intelligent Platform Management Interface, an open standard for out-of-band management often shipped with enterprise-level servers. We show how power-related sensors available with minimal user privilege over IPMI can be correlated with the levels of CPU stress of a virtual machine on a server. This leads to our second experiment, in which we demonstrate a power analysis approach for establishing a covert channel for the exfiltration of data from a network-isolated virtual machine on a server rack. By applying the concept of power analysis more broadly to the power consumption of an entire server rack, rather than individual hardware components, we find that basic patterns in system load can be clearly identified using signal processing techniques, demonstrating the potential for establishing a covert channel

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Algorithms for compression of high dynamic range images and video

The recent advances in sensor and display technologies have brought upon the High Dynamic Range (HDR) imaging capability. The modern multiple exposure HDR sensors can achieve the dynamic range of 100-120 dB and LED and OLED display devices have contrast ratios of 10^5:1 to 10^6:1. Despite the above advances in technology the image/video compression algorithms and associated hardware are yet based on Standard Dynamic Range (SDR) technology, i.e. they operate within an effective dynamic range of up to 70 dB for 8 bit gamma corrected images. Further the existing infrastructure for content distribution is also designed for SDR, which creates interoperability problems with true HDR capture and display equipment. The current solutions for the above problem include tone mapping the HDR content to fit SDR. However this approach leads to image quality associated problems, when strong dynamic range compression is applied. Even though some HDR-only solutions have been proposed in literature, they are not interoperable with current SDR infrastructure and are thus typically used in closed systems. Given the above observations a research gap was identified in the need for efficient algorithms for the compression of still images and video, which are capable of storing full dynamic range and colour gamut of HDR images and at the same time backward compatible with existing SDR infrastructure. To improve the usability of SDR content it is vital that any such algorithms should accommodate different tone mapping operators, including those that are spatially non-uniform. In the course of the research presented in this thesis a novel two layer CODEC architecture is introduced for both HDR image and video coding. Further a universal and computationally efficient approximation of the tone mapping operator is developed and presented. It is shown that the use of perceptually uniform colourspaces for internal representation of pixel data enables improved compression efficiency of the algorithms. Further proposed novel approaches to the compression of metadata for the tone mapping operator is shown to improve compression performance for low bitrate video content. Multiple compression algorithms are designed, implemented and compared and quality-complexity trade-offs are identified. Finally practical aspects of implementing the developed algorithms are explored by automating the design space exploration flow and integrating the high level systems design framework with domain specific tools for synthesis and simulation of multiprocessor systems. The directions for further work are also presented

Embedded computing systems design: architectural and application perspectives

Questo elaborato affronta varie problematiche legate alla progettazione e all'implementazione dei moderni sistemi embedded di computing, ponendo in rilevo, e talvolta in contrapposizione, le sfide che emergono all'avanzare della tecnologia ed i requisiti che invece emergono a livello applicativo, derivanti dalle necessità degli utenti finali e dai trend di mercato. La discussione sarà articolata tenendo conto di due punti di vista: la progettazione hardware e la loro applicazione a livello di sistema. A livello hardware saranno affrontati nel dettaglio i problemi di interconnettività on-chip. Aspetto che riguarda la parallelizzazione del calcolo, ma anche l'integrazione di funzionalità eterogenee. Sarà quindi discussa un'architettura d'interconnessione denominata Network-on-Chip (NoC). La soluzione proposta è in grado di supportare funzionalità avanzate di networking direttamente in hardware, consentendo tuttavia di raggiungere sempre un compromesso ottimale tra prestazioni in termini di traffico e requisiti di implementazioni a seconda dell'applicazione specifica. Nella discussione di questa tematica, verrà posto l'accento sul problema della configurabilità dei blocchi che compongono una NoC. Quello della configurabilità, è un problema sempre più sentito nella progettazione dei sistemi complessi, nei quali si cerca di sviluppare delle funzionalità, anche molto evolute, ma che siano semplicemente riutilizzabili. A tale scopo sarà introdotta una nuova metodologia, denominata Metacoding che consiste nell'astrarre i problemi di configurabilità attraverso linguaggi di programmazione di alto livello. Sulla base del metacoding verrà anche proposto un flusso di design automatico in grado di semplificare la progettazione e la configurazione di una NoC da parte del designer di rete. Come anticipato, la discussione si sposterà poi a livello di sistema, per affrontare la progettazione di tali sistemi dal punto di vista applicativo, focalizzando l'attenzione in particolare sulle applicazioni di monitoraggio remoto. A tal riguardo saranno studiati nel dettaglio tutti gli aspetti che riguardano la progettazione di un sistema per il monitoraggio di pazienti affetti da scompenso cardiaco cronico. Si partirà dalla definizione dei requisiti, che, come spesso accade a questo livello, derivano principalmente dai bisogni dell'utente finale, nel nostro caso medici e pazienti. Verranno discusse le problematiche di acquisizione, elaborazione e gestione delle misure. Il sistema proposto introduce vari aspetti innovativi tra i quali il concetto di protocollo operativo e l'elevata interoperabilità offerta. In ultima analisi, verranno riportati i risultati relativi alla sperimentazione del sistema implementato. Infine, il tema del monitoraggio remoto sarà concluso con lo studio delle reti di distribuzione elettrica intelligenti: le Smart Grid, cercando di fare uno studio dello stato dell'arte del settore, proponendo un'architettura di Home Area Network (HAN) e suggerendone una possibile implementazione attraverso Commercial Off the Shelf (COTS)

D11.2 Consolidated results on the performance limits of wireless communications

Deliverable D11.2 del projecte europeu NEWCOM#The report presents the Intermediate Results of N# JRAs on Performance Limits of Wireless Communications and highlights the fundamental issues that have been investigated by the WP1.1. The report illustrates the Joint Research Activities (JRAs) already identified during the first year of the project which are currently ongoing. For each activity there is a description, an illustration of the adherence and relevance with the identified fundamental open issues, a short presentation of the preliminary results, and a roadmap for the joint research work in the next year. Appendices for each JRA give technical details on the scientific activity in each JRA.Peer ReviewedPreprin