A Survey of Trustworthy Computing on Mobile & Wearable Systems

Mobile and wearable systems have generated unprecedented interest in recent years, particularly in the domain of mobile health (mHealth) where carried or worn devices are used to collect health-related information about the observed person. Much of the information - whether physiological, behavioral, or social - collected by mHealth systems is sensitive and highly personal; it follows that mHealth systems should, at the very least, be deployed with mechanisms suitable for ensuring confidentiality of the data it collects. Additional properties - such as integrity of the data, source authentication of data, and data freshness - are also desirable to address other security, privacy, and safety issues. Developing systems that are robust against capable adversaries (including physical attacks) is, and has been, an active area of research. While techniques for protecting systems that handle sensitive data are well-known today, many of the solutions in use today are not well suited for mobile and wearable systems, which are typically limited with respect to power, memory, computation, and other capabilities. In this paper we look at prior research on developing trustworthy mobile and wearable systems. To survey this topic we begin by discussing solutions for securing computing systems that are not subject to the type of strict constraints associated with mobile and wearable systems. Next, we present other efforts to design and implement trustworthy mobile and wearable systems. We end with a discussion of future directions

Distributed IoT Attestation via Blockchain (Extended Version)

The growing number and nature of Internet of Things (IoT) devices makes these resource-constrained appliances particularly vulnerable and increasingly impactful in their exploitation. Current estimates for the number of connected things commonly reach the tens of billions. The low-cost and limited computational strength of these devices can preclude security features. Additionally, economic forces and a lack of industry expertise in security often contribute to a rush to market with minimal consideration for security implications. It is essential that users of these emerging technologies, from consumers to IT professionals, be able to establish and retain trust in the multitude of diverse and pervasive compute devices that are ever more responsible for our critical infrastructure and personal information. Remote attestation is a well-known technique for building such trust between devices. In standard implementations, a potentially untrustworthy prover attests, using public key infrastructure, to a verifier about its configuration or properties of its current state. Attestation is often performed on an ad hoc basis with little concern for historicity. However, controls and sensors manufactured for the Industrial IoT (IIoT) may be expected to operate for decades. Even in the consumer market, so-called smart things can be expected to outlive their manufacturers. This longevity combined with limited software or firmware patching creates an ideal environment for long-lived zero-day vulnerabilities. Knowing both if a device is vulnerable and if so when it became vulnerable is a management nightmare as IoT deployments scale. For network connected machines, with access to sensitive information and real-world physical controls, maintaining some sense of a device\u27s lifecycle would be insightful. In this paper, we propose a novel attestation architecture, DAN: a distributed attestation network, utilizing blockchain to store and share device information. We present the design of this new attestation architecture, and describe a virtualized simulation, as well as a prototype system chosen to emulate an IoT deployment with a network of Raspberry Pi, Infineon TPMs, and a Hyperledger Fabric blockchain. We discuss the implications and potential challenges of such a network for various applications such as identity management, intrusion detection, forensic audits, and regulatory certification

RIPencapsulation: Defeating IP Encapsulation on TI MSP Devices

Internet of Things (IoT) devices sit at the intersection of unwieldy software complexity and unprecedented attacker access. This unique position comes with a daunting security challenge: how can I protect both proprietary code and confidential data on a device that the attacker has unfettered access to? Trusted Execution Environments (TEEs) promise to solve this challenge through hardware-based separation of trusted and untrusted computation and data. While TEEs do an adequate job of protecting secrets on desktop-class devices, we reveal that trade-offs made in one of the most widely-used commercial IoT devices undermine their TEE's security. This paper uncovers two fundamental weaknesses in IP Encapsulation (IPE), the TEE deployed by Texas Instruments for MSP430 and MSP432 devices. We observe that lack of call site enforcement and residual state after unexpected TEE exits enable an attacker to reveal all proprietary code and secret data within the IPE. We design and implement an attack called RIPencapsulation, which systematically executes portions of code within the IPE and uses the partial state revealed through the register file to exfiltrate secret data and to identify gadget instructions. The attack then uses gadget instructions to reveal all proprietary code within the IPE. Our evaluation with commodity devices and a production compiler and settings shows that -- even after following all manufacturer-recommended secure coding practices -- RIPencapsultaion reveals, within minutes, both the code and keys from third-party cryptographic implementations protected by the IPE.Comment: 13 pages, 3 figures, 6 table

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

Lightweight Protocols and Applications for Memory-Based Intrinsic Physically Unclonable Functions on Commercial Off-The-Shelve Devices

We are currently living in the era in which through the ever-increasing dissemination of inter-connected embedded devices, the Internet-of-Things manifests. Although such end-point devices are commonly labeled as ``smart gadgets'' and hence they suggest to implement some sort of intelligence, from a cyber-security point of view, more then often the opposite holds. The market force in the branch of commercial embedded devices leads to minimizing production costs and time-to-market. This widespread trend has a direct, disastrous impact on the security properties of such devices. The majority of currently used devices or those that will be produced in the future do not implement any or insufficient security mechanisms. Foremost the lack of secure hardware components often mitigates the application of secure protocols and applications. This work is dedicated to a fundamental solution statement, which allows to retroactively secure commercial off-the-shelf devices, which otherwise are exposed to various attacks due to the lack of secure hardware components. In particular, we leverage the concept of Physically Unclonable Functions (PUFs), to create hardware-based security anchors in standard hardware components. For this purpose, we exploit manufacturing variations in Static Random-Access Memory (SRAM) and Dynamic Random-Access Memory modules to extract intrinsic memory-based PUF instances and building on that, to develop secure and lightweight protocols and applications. For this purpose, we empirically evaluate selected and representative device types towards their PUF characteristics. In a further step, we use those device types, which qualify due to the existence of desired PUF instances for subsequent development of security applications and protocols. Subsequently, we present various software-based security solutions which are specially tailored towards to the characteristic properties of embedded devices. More precisely, the proposed solutions comprise a secure boot architecture as well as an approach to protect the integrity of the firmware by binding it to the underlying hardware. Furthermore, we present a lightweight authentication protocol which leverages a novel DRAM-based PUF type. Finally, we propose a protocol, which allows to securely verify the software state of remote embedded devices

Systems Support for Trusted Execution Environments

Cloud computing has become a default choice for data processing by both large corporations and individuals due to its economy of scale and ease of system management. However, the question of trust and trustoworthy computing inside the Cloud environments has been long neglected in practice and further exacerbated by the proliferation of AI and its use for processing of sensitive user data. Attempts to implement the mechanisms for trustworthy computing in the cloud have previously remained theoretical due to lack of hardware primitives in the commodity CPUs, while a combination of Secure Boot, TPMs, and virtualization has seen only limited adoption. The situation has changed in 2016, when Intel introduced the Software Guard Extensions (SGX) and its enclaves to the x86 ISA CPUs: for the first time, it became possible to build trustworthy applications relying on a commonly available technology. However, Intel SGX posed challenges to the practitioners who discovered the limitations of this technology, from the limited support of legacy applications and integration of SGX enclaves into the existing system, to the performance bottlenecks on communication, startup, and memory utilization. In this thesis, our goal is enable trustworthy computing in the cloud by relying on the imperfect SGX promitives. To this end, we develop and evaluate solutions to issues stemming from limited systems support of Intel SGX: we investigate the mechanisms for runtime support of POSIX applications with SCONE, an efficient SGX runtime library developed with performance limitations of SGX in mind. We further develop this topic with FFQ, which is a concurrent queue for SCONE's asynchronous system call interface. ShieldBox is our study of interplay of kernel bypass and trusted execution technologies for NFV, which also tackles the problem of low-latency clocks inside enclave. The two last systems, Clemmys and T-Lease are built on a more recent SGXv2 ISA extension. In Clemmys, SGXv2 allows us to significantly reduce the startup time of SGX-enabled functions inside a Function-as-a-Service platform. Finally, in T-Lease we solve the problem of trusted time by introducing a trusted lease primitive for distributed systems. We perform evaluation of all of these systems and prove that they can be practically utilized in existing systems with minimal overhead, and can be combined with both legacy systems and other SGX-based solutions. In the course of the thesis, we enable trusted computing for individual applications, high-performance network functions, and distributed computing framework, making a <vision of trusted cloud computing a reality

Sixth International Joint Conference on Electronic Voting E-Vote-ID 2021. 5-8 October 2021

This volume contains papers presented at E-Vote-ID 2021, the Sixth International Joint Conference on Electronic Voting, held during October 5-8, 2021. Due to the extraordinary situation provoked by Covid-19 Pandemic, the conference is held online for second consecutive edition, instead of in the traditional venue in Bregenz, Austria. E-Vote-ID Conference resulted from the merging of EVOTE and Vote-ID and counting up to 17 years since the _rst E-Vote conference in Austria. Since that conference in 2004, over 1000 experts have attended the venue, including scholars, practitioners, authorities, electoral managers, vendors, and PhD Students. The conference collected the most relevant debates on the development of Electronic Voting, from aspects relating to security and usability through to practical experiences and applications of voting systems, also including legal, social or political aspects, amongst others; turning out to be an important global referent in relation to this issue. Also, this year, the conference consisted of: · Security, Usability and Technical Issues Track · Administrative, Legal, Political and Social Issues Track · Election and Practical Experiences Track · PhD Colloquium, Poster and Demo Session on the day before the conference E-VOTE-ID 2021 received 49 submissions, being, each of them, reviewed by 3 to 5 program committee members, using a double blind review process. As a result, 27 papers were accepted for its presentation in the conference. The selected papers cover a wide range of topics connected with electronic voting, including experiences and revisions of the real uses of E-voting systems and corresponding processes in elections. We would also like to thank the German Informatics Society (Gesellschaft für Informatik) with its ECOM working group and KASTEL for their partnership over many years. Further we would like to thank the Swiss Federal Chancellery and the Regional Government of Vorarlberg for their kind support. EVote- ID 2021 conference is kindly supported through European Union's Horizon 2020 projects ECEPS (grant agreement 857622) and mGov4EU (grant agreement 959072). Special thanks go to the members of the international program committee for their hard work in reviewing, discussing, and shepherding papers. They ensured the high quality of these proceedings with their knowledge and experience

Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions

Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be trustworthy for the end-users. However, existing literature still lacks a systematic and comprehensive survey work on the use of XAI for IoT. To bridge this lacking, in this paper, we address the XAI frameworks with a focus on their characteristics and support for IoT. We illustrate the widely-used XAI services for IoT applications, such as security enhancement, Internet of Medical Things (IoMT), Industrial IoT (IIoT), and Internet of City Things (IoCT). We also suggest the implementation choice of XAI models over IoT systems in these applications with appropriate examples and summarize the key inferences for future works. Moreover, we present the cutting-edge development in edge XAI structures and the support of sixth-generation (6G) communication services for IoT applications, along with key inferences. In a nutshell, this paper constitutes the first holistic compilation on the development of XAI-based frameworks tailored for the demands of future IoT use cases.Comment: 29 pages, 7 figures, 2 tables. IEEE Open Journal of the Communications Society (2022