CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties

The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels. This article presents an overview of the CONTREX European project, its main innovative technology (extension of a model based design approach, functional and extra-functional analysis with executable models and run-time management) and the final results of three industrial use-cases from different domain (avionics, automotive and telecommunication).The work leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2011 under grant agreement no. 611146

CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties

The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. The paper presents the CONTREX European project and its preliminary results. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels

PORTING OF FREERTOS ON A PYTHON VIRTUAL MACHINE FOR EMBEDDED AND IOT DEVICES

The fourth industrial revolution, The Industry 4.0, puts emphasis on the need of “Smart” and “Connected” objects through the use of services provided by Internet of Things, cyber-physical systems and cloud computing to optimize the cost, development time and remote connectivity. Development of highly scalable and flexible IoT applications is the need of time. These solutions require connectivity, less development time, time-to-market and at the same time offers a high performance and great reliability. Zerynth, a small company, provides its full stack for IoT solutions. Zerynth Virtual Machine is the core component among other components in stack which allow the programmers to code in python or hybrid C/Python coding with multithreaded Real Time OS with negligible memory footprint. The Python layer, Application Layer, is totally agnostic of underlying RTOS and hardware abstraction layer. This layered software architecture of Zerynth VM makes it totally compatible with new Industry 4.0 standard. The Hardware abstraction layer, VHAL, abstracts the hardware features of supported MCU and its peripherals while RTOS layer, VOSAL, uses the features of underlying Real Time OS. Zerynth VM can be ported with different Real Time OS and various hardware platforms depending upon the application’s cost, features and other relevant parameters. Configuring Kinetis MCU (MK64FN1M0VDC12) with existing VM became the first objective of my thesis. This configuration covers from scratch the clock, boot loading and peripheral support. Since previous version of Zerynth VM had a support of only Chibi2 OS which has certain dependency on the hardware layer underneath so this became another objective to separate the Chibi2 OS from VHAL layer for total independence. Finally, Porting of FreeRTOS on Zerynth VM with Hexiwear MCU as target board could a make a room for another RTOS hence enhancing the features and support of currently available VM. This thesis report describes all porting steps, procedures and testing methodologies starting from configuring a new hardware platform Hexiwear to FreeRTOS porting on Zerynth V

Security and trust in cloud computing and IoT through applying obfuscation, diversification, and trusted computing technologies

Cloud computing and Internet of Things (IoT) are very widely spread and commonly used technologies nowadays. The advanced services offered by cloud computing have made it a highly demanded technology. Enterprises and businesses are more and more relying on the cloud to deliver services to their customers. The prevalent use of cloud means that more data is stored outside the organization’s premises, which raises concerns about the security and privacy of the stored and processed data. This highlights the significance of effective security practices to secure the cloud infrastructure. The number of IoT devices is growing rapidly and the technology is being employed in a wide range of sectors including smart healthcare, industry automation, and smart environments. These devices collect and exchange a great deal of information, some of which may contain critical and personal data of the users of the device. Hence, it is highly significant to protect the collected and shared data over the network; notwithstanding, the studies signify that attacks on these devices are increasing, while a high percentage of IoT devices lack proper security measures to protect the devices, the data, and the privacy of the users. In this dissertation, we study the security of cloud computing and IoT and propose software-based security approaches supported by the hardware-based technologies to provide robust measures for enhancing the security of these environments. To achieve this goal, we use obfuscation and diversification as the potential software security techniques. Code obfuscation protects the software from malicious reverse engineering and diversification mitigates the risk of large-scale exploits. We study trusted computing and Trusted Execution Environments (TEE) as the hardware-based security solutions. Trusted Platform Module (TPM) provides security and trust through a hardware root of trust, and assures the integrity of a platform. We also study Intel SGX which is a TEE solution that guarantees the integrity and confidentiality of the code and data loaded onto its protected container, enclave. More precisely, through obfuscation and diversification of the operating systems and APIs of the IoT devices, we secure them at the application level, and by obfuscation and diversification of the communication protocols, we protect the communication of data between them at the network level. For securing the cloud computing, we employ obfuscation and diversification techniques for securing the cloud computing software at the client-side. For an enhanced level of security, we employ hardware-based security solutions, TPM and SGX. These solutions, in addition to security, ensure layered trust in various layers from hardware to the application. As the result of this PhD research, this dissertation addresses a number of security risks targeting IoT and cloud computing through the delivered publications and presents a brief outlook on the future research directions.Pilvilaskenta ja esineiden internet ovat nykyään hyvin tavallisia ja laajasti sovellettuja tekniikkoja. Pilvilaskennan pitkälle kehittyneet palvelut ovat tehneet siitä hyvin kysytyn teknologian. Yritykset enenevässä määrin nojaavat pilviteknologiaan toteuttaessaan palveluita asiakkailleen. Vallitsevassa pilviteknologian soveltamistilanteessa yritykset ulkoistavat tietojensa käsittelyä yrityksen ulkopuolelle, minkä voidaan nähdä nostavan esiin huolia taltioitavan ja käsiteltävän tiedon turvallisuudesta ja yksityisyydestä. Tämä korostaa tehokkaiden turvallisuusratkaisujen merkitystä osana pilvi-infrastruktuurin turvaamista. Esineiden internet -laitteiden lukumäärä on nopeasti kasvanut. Teknologiana sitä sovelletaan laajasti monilla sektoreilla, kuten älykkäässä terveydenhuollossa, teollisuusautomaatiossa ja älytiloissa. Sellaiset laitteet keräävät ja välittävät suuria määriä informaatiota, joka voi sisältää laitteiden käyttäjien kannalta kriittistä ja yksityistä tietoa. Tästä syystä johtuen on erittäin merkityksellistä suojata verkon yli kerättävää ja jaettavaa tietoa. Monet tutkimukset osoittavat esineiden internet -laitteisiin kohdistuvien tietoturvahyökkäysten määrän olevan nousussa, ja samaan aikaan suuri osuus näistä laitteista ei omaa kunnollisia teknisiä ominaisuuksia itse laitteiden tai niiden käyttäjien yksityisen tiedon suojaamiseksi. Tässä väitöskirjassa tutkitaan pilvilaskennan sekä esineiden internetin tietoturvaa ja esitetään ohjelmistopohjaisia tietoturvalähestymistapoja turvautumalla osittain laitteistopohjaisiin teknologioihin. Esitetyt lähestymistavat tarjoavat vankkoja keinoja tietoturvallisuuden kohentamiseksi näissä konteksteissa. Tämän saavuttamiseksi työssä sovelletaan obfuskaatiota ja diversifiointia potentiaalisiana ohjelmistopohjaisina tietoturvatekniikkoina. Suoritettavan koodin obfuskointi suojaa pahantahtoiselta ohjelmiston takaisinmallinnukselta ja diversifiointi torjuu tietoturva-aukkojen laaja-alaisen hyödyntämisen riskiä. Väitöskirjatyössä tutkitaan luotettua laskentaa ja luotettavan laskennan suoritusalustoja laitteistopohjaisina tietoturvaratkaisuina. TPM (Trusted Platform Module) tarjoaa turvallisuutta ja luottamuksellisuutta rakentuen laitteistopohjaiseen luottamukseen. Pyrkimyksenä on taata suoritusalustan eheys. Työssä tutkitaan myös Intel SGX:ää yhtenä luotettavan suorituksen suoritusalustana, joka takaa suoritettavan koodin ja datan eheyden sekä luottamuksellisuuden pohjautuen suojatun säiliön, saarekkeen, tekniseen toteutukseen. Tarkemmin ilmaistuna työssä turvataan käyttöjärjestelmä- ja sovellusrajapintatasojen obfuskaation ja diversifioinnin kautta esineiden internet -laitteiden ohjelmistokerrosta. Soveltamalla samoja tekniikoita protokollakerrokseen, työssä suojataan laitteiden välistä tiedonvaihtoa verkkotasolla. Pilvilaskennan turvaamiseksi työssä sovelletaan obfuskaatio ja diversifiointitekniikoita asiakaspuolen ohjelmistoratkaisuihin. Vankemman tietoturvallisuuden saavuttamiseksi työssä hyödynnetään laitteistopohjaisia TPM- ja SGX-ratkaisuja. Tietoturvallisuuden lisäksi nämä ratkaisut tarjoavat monikerroksisen luottamuksen rakentuen laitteistotasolta ohjelmistokerrokseen asti. Tämän väitöskirjatutkimustyön tuloksena, osajulkaisuiden kautta, vastataan moniin esineiden internet -laitteisiin ja pilvilaskentaan kohdistuviin tietoturvauhkiin. Työssä esitetään myös näkemyksiä jatkotutkimusaiheista

Defense in Depth of Resource-Constrained Devices

The emergent next generation of computing, the so-called Internet of Things (IoT), presents significant challenges to security, privacy, and trust. The devices commonly used in IoT scenarios are often resource-constrained with reduced computational strength, limited power consumption, and stringent availability requirements. Additionally, at least in the consumer arena, time-to-market is often prioritized at the expense of quality assurance and security. An initial lack of standards has compounded the problems arising from this rapid development. However, the explosive growth in the number and types of IoT devices has now created a multitude of competing standards and technology silos resulting in a highly fragmented threat model. Tens of billions of these devices have been deployed in consumers\u27 homes and industrial settings. From smart toasters and personal health monitors to industrial controls in energy delivery networks, these devices wield significant influence on our daily lives. They are privy to highly sensitive, often personal data and responsible for real-world, security-critical, physical processes. As such, these internet-connected things are highly valuable and vulnerable targets for exploitation. Current security measures, such as reactionary policies and ad hoc patching, are not adequate at this scale. This thesis presents a multi-layered, defense in depth, approach to preventing and mitigating a myriad of vulnerabilities associated with the above challenges. To secure the pre-boot environment, we demonstrate a hardware-based secure boot process for devices lacking secure memory. We introduce a novel implementation of remote attestation backed by blockchain technologies to address hardware and software integrity concerns for the long-running, unsupervised, and rarely patched systems found in industrial IoT settings. Moving into the software layer, we present a unique method of intraprocess memory isolation as a barrier to several prevalent classes of software vulnerabilities. Finally, we exhibit work on network analysis and intrusion detection for the low-power, low-latency, and low-bandwidth wireless networks common to IoT applications. By targeting these areas of the hardware-software stack, we seek to establish a trustworthy system that extends from power-on through application runtime

Evaluation of Edge AI Co-Processing Methods for Space Applications

The recent years spread of SmallSats offers several new services and opens to the implementation of new technologies to improve the existent ones. However, the communication link to Earth in order to process data often is a bottleneck, due to the amount of collected data and the limited bandwidth. A way to face this challenge is edge computing, which supposedly discards useless data and fasten up the transmission, and therefore the research has moved towards the study of COTS architectures to be used in space, often organized in co-processing setups. This thesis considers AI as application use case and two devices in a controller-accelerator configuration. It proposes to investigate the performances of co-processing methods such as simple parallel, horizontal partitioning and vertical partitioning, for a set of different tasks and taking advantage of different pre-trained models. The actual experiments regard only simple parallel and horizontal partitioning mode, and they compare latency and accuracy results with single processing runs on both devices. Evaluating the results task-by-task, image classification has the best performance improvement taking advantage of horizontal partitioning, with a clear accuracy improvement, as well as semantic segmentation, which shows almost stable accuracy and potentially higher throughput with smaller models input sizes. On the other hand, object detection shows a drop in performances, especially accuracy, which could maybe be improved with more specifically developed models for the chosen hardware. The project clearly shows how co-processing methods are worth of being investigated and can improve system outcomes for some of the analyzed tasks, making future work about it interesting

Energy-efficient Transitional Near-* Computing

Studies have shown that communication networks, devices accessing the Internet, and data centers account for 4.6% of the worldwide electricity consumption. Although data centers, core network equipment, and mobile devices are getting more energy-efficient, the amount of data that is being processed, transferred, and stored is vastly increasing. Recent computer paradigms, such as fog and edge computing, try to improve this situation by processing data near the user, the network, the devices, and the data itself. In this thesis, these trends are summarized under the new term near-* or near-everything computing. Furthermore, a novel paradigm designed to increase the energy efficiency of near-* computing is proposed: transitional computing. It transfers multi-mechanism transitions, a recently developed paradigm for a highly adaptable future Internet, from the field of communication systems to computing systems. Moreover, three types of novel transitions are introduced to achieve gains in energy efficiency in near-* environments, spanning from private Infrastructure-as-a-Service (IaaS) clouds, Software-defined Wireless Networks (SDWNs) at the edge of the network, Disruption-Tolerant Information-Centric Networks (DTN-ICNs) involving mobile devices, sensors, edge devices as well as programmable components on a mobile System-on-a-Chip (SoC). Finally, the novel idea of transitional near-* computing for emergency response applications is presented to assist rescuers and affected persons during an emergency event or a disaster, although connections to cloud services and social networks might be disturbed by network outages, and network bandwidth and battery power of mobile devices might be limited