Matthias Hollick

Dingwen Yuan, Luis F. Abanto-Leon, Matthias Hollick

This paper investigates scheduling strategies for wireless sensor-actuator networks (WSANs) in Industry 4.0 scenarios. In particular, we address the problem of real-time scheduling for multi-rate control systems by proposing a novel framework. Our framework features four strategies that improve reliability, schedulability and execution time, and reduce communication and storage costs. Two-phase scheduling is our first strategy, devised to improve communication reliability. Our second strategy is the least-laxity-first with remaining conflicts (LLF-RC) scheduling algorithm, which has high schedulability and affordable execution time. LLF-RC also keeps the maximum queue length at a moderate level, making it suitable for storage-constrained devices. Our third and fourth strategies are opportunistic aggregation and repetitive scheduling. Opportunistic aggregation performs simple and effective packet aggregation, enhancing schedulability by up to 97% and reducing execution time by up to 29%, in our simulation. Repetitive scheduling has negligible execution time, and contributes to minimize communication and storage costs. It reduces the maximum execution time by 92% and the maximum communication and storage cost by 99%, in our simulation. We compare our proposed framework against existing approaches, and evaluate the advantages of our strategies in realistic scenarios.

Tobias Kröll, Stephan Kleber, Frank Kargl et al.

Wireless chips and interfaces expose a substantial remote attack surface. As of today, most cellular baseband security research is performed on the Android ecosystem, leaving a huge gap on Apple devices. With iOS jailbreaks, last-generation wireless chips become fairly accessible for performance and security research. Yet, iPhones were never intended to be used as a research platform, and chips and interfaces are undocumented. One protocol to interface with such chips is Apple Remote Invocation (ARI), which interacts with the central phone component CommCenter and multiple user-space daemons, thereby posing a Remote Code Execution (RCE) attack surface. We are the first to reverse-engineer and fuzz-test the ARI interface on iOS. Our Ghidra scripts automatically generate a Wireshark dissector, called ARIstoteles, by parsing closed-source iOS libraries for this undocumented protocol. Moreover, we compare the quality of the dissector to fully-automated approaches based on static trace analysis. Finally, we fuzz the ARI interface based on our reverse-engineering results. The fuzzing results indicate that ARI does not only lack public security research but also has not been well-tested by Apple. By releasing ARIstoteles open-source, we also aim to facilitate similar research in the future.

Yannik Dittmar, Marvin Jerome Stephan, Thomas Völkl et al.

Many existing Artificial Intelligence (AI) solutions on mobile devices rely on an extensive collection of sensitive data, raising privacy concerns and often requiring storage for both context and model improvement. Apple's Private Cloud Compute (PCC) aims to address this by emphasizing mobile device integration and a privacy-first design. The central claim of PCC is that it does not store any user data and that user input and user accounts are unlinkable. While most of the PCC system specifications are public, compiled binaries add a layer of opaqueness. There are no reproducible builds, and there are no symbols within those binaries, creating potential discrepancies between the specification and what is shipped to the user. Additionally, the underlying models and interfaces for querying PCC are not openly accessible, limiting academic evaluation of model properties, such as accuracy. This poses a challenge in assessing whether a privacy-preserving approach like PCC is actually trustworthy while also providing high-quality answers. We are the first to reverse-engineer the PCC implementation on mobile devices to evaluate privacy aspects and to open its non-public interfaces on local devices to support custom PCC queries. We demonstrate this level of access beyond Apple's intended use cases by independently benchmarking the PCC model. We enable future research by making our PCC benchmarking framework publicly available.

Steffen Klee, Alexandros Roussos, Max Maass et al.

Near-Field Communication (NFC) is being used in a variety of security-critical applications, from access control to payment systems. However, NFC protocol analysis typically requires expensive or conspicuous dedicated hardware, or is severely limited on smartphones. In 2015, the NFCGate proof of concept aimed at solving this issue by providing capabilities for NFC analysis employing off-the-shelf Android smartphones. In this paper, we present an extended and improved NFC toolkit based on the functionally limited original open-source codebase. With in-flight traffic analysis and modification, relay, and replay features this toolkit turns an off-the-shelf smartphone into a powerful NFC research tool. To support the development of countermeasures against relay attacks, we investigate the latency incurred by NFCGate in different configurations. Our newly implemented features and improvements enable the case study of an award-winning, enterprise-level NFC lock from a well-known European lock vendor, which would otherwise require dedicated hardware. The analysis of the lock reveals several security issues, which were disclosed to the vendor.

Alexander Heinrich, Milan Stute, Matthias Hollick

The market for Bluetooth Low Energy devices is booming and, at the same time, has become an attractive target for adversaries. To improve BLE security at large, we present BTLEmap, an auditing application for BLE environments. BTLEmap is inspired by network discovery and security auditing tools such as Nmap for IP-based networks. It allows for device enumeration, GATT service discovery, and device fingerprinting. It goes even further by integrating a BLE advertisement dissector, data exporter, and a user-friendly UI, including a proximity view. BTLEmap currently runs on iOS and macOS using Apple's CoreBluetooth API but also accepts alternative data inputs such as a Raspberry Pi to overcome the restricted vendor API. The open-source project is under active development and will provide more advanced capabilities such as long-term device tracking (in spite of MAC address randomization) in the future.

Santiago Aragon, Marco Tiloca, Max Maass et al.

The Authentication and Authorization for Constrained Environments (ACE) framework provides fine-grained access control in the Internet of Things, where devices are resource-constrained and with limited connectivity. The ACE framework defines separate profiles to specify how exactly entities interact and what security and communication protocols to use. This paper presents the novel ACE IPsec profile, which specifies how a client establishes a secure IPsec channel with a resource server, contextually using the ACE framework to enforce authorized access to remote resources. The profile makes it possible to establish IPsec Security Associations, either through their direct provisioning or through the standard IKEv2 protocol. We provide the first Open Source implementation of the ACE IPsec profile for the Contiki OS and test it on the resource-constrained Zolertia Firefly platform. Our experimental performance evaluation confirms that the IPsec profile and its operating modes are affordable and deployable also on constrained IoT platforms.

Alexander Heinrich, Niklas Bittner, Matthias Hollick

Finder networks in general, and Apple's Find My network in particular, can pose a grave threat to users' privacy and even health if these networks are abused for stalking. Apple's release of the AirTag, a very affordable tracker covered by the nearly ubiquitous Find My network, amplified this issue. While Apple provides a stalking detection feature within its ecosystem, billions of Android users are still left in the dark. Apple recently released the Android app "Tracker Detect," which does not deliver a convincing feature set for stalking protection. We reverse engineer Apple's tracking protection in iOS and discuss its features regarding stalking detection. We design "AirGuard" and release it as an Android app to protect against abuse by Apple tracking devices. We compare the performance of our solution with the Apple-provided one in iOS and study the use of AirGuard in the wild over multiple weeks using data contributed by tens of thousands of active users.

Gerbert Roitburd, Matthias Ortmann, Matthias Hollick et al.

Corporate Virtual Private Networks (VPNs) enable users to work from home or while traveling. At the same time, VPNs are tied to a company's network infrastructure, forcing users to install proprietary clients for network compatibility reasons. VPN clients run with high privileges to encrypt and reroute network traffic. Thus, bugs in VPN clients pose a substantial risk to their users and in turn the corporate network. Cisco, the dominating vendor of enterprise network hardware, offers VPN connectivity with their AnyConnect client for desktop and mobile devices. While past security research primarily focused on the AnyConnect Windows client, we show that Linux and iOS are based on different architectures and have distinct security issues. Our reverse engineering as well as the follow-up design analysis and fuzzing reveal 13 new vulnerabilities. Seven of these are located in the Linux client. The root cause for privilege escalations on Linux is anchored so deep in the client's architecture that it only got patched with a partial workaround. A similar analysis on iOS uncovers three AnyConnect-specific bugs as well as three general issues in iOS network extensions, which apply to all kinds of VPNs and are not restricted to AnyConnect.

Jiska Classen, Francesco Gringoli, Michael Hermann et al.

Modern mobile devices feature multiple wireless technologies, such as Bluetooth, Wi-Fi, and LTE. Each of them is implemented within a separate wireless chip, sometimes packaged as combo chips. However, these chips share components and resources, such as the same antenna or wireless spectrum. Wireless coexistence interfaces enable them to schedule packets without collisions despite shared resources, essential to maximizing networking performance. Today's hardwired coexistence interfaces hinder clear security boundaries and separation between chips and chip components. This paper shows practical coexistence attacks on Broadcom, Cypress, and Silicon Labs chips deployed in billions of devices. For example, we demonstrate that a Bluetooth chip can directly extract network passwords and manipulate traffic on a Wi-Fi chip. Coexistence attacks enable a novel type of lateral privilege escalation across chip boundaries. We responsibly disclosed the vulnerabilities to the vendors. Yet, only partial fixes were released for existing hardware since wireless chips would need to be redesigned from the ground up to prevent the presented attacks on coexistence.

Matthias Gazzari, Annemarie Mattmann, Max Maass et al.

Wearables that constantly collect various sensor data of their users increase the chances for inferences of unintentional and sensitive information such as passwords typed on a physical keyboard. We take a thorough look at the potential of using electromyographic (EMG) data, a sensor modality which is new to the market but has lately gained attention in the context of wearables for augmented reality (AR), for a keylogging side-channel attack. Our approach is based on neural networks for a between-subject attack in a realistic scenario using the Myo Armband to collect the sensor data. In our approach, the EMG data has proven to be the most prominent source of information compared to the accelerometer and gyroscope, increasing the keystroke detection performance. For our end-to-end approach on raw data, we report a mean balanced accuracy of about 76 % for the keystroke detection and a mean top-3 key accuracy of about 32 % on 52 classes for the key identification on passwords of varying strengths. We have created an extensive dataset including more than 310 000 keystrokes recorded from 37 volunteers, which is available as open access along with the source code used to create the given results.

Patrick Leu, Giovanni Camurati, Alexander Heinrich et al.

We present the first over-the-air attack on IEEE 802.15.4z High-Rate Pulse Repetition Frequency (HRP) Ultra-WideBand (UWB) distance measurement systems. Specifically, we demonstrate a practical distance reduction attack against pairs of Apple U1 chips (embedded in iPhones and AirTags), as well as against U1 chips inter-operating with NXP and Qorvo UWB chips. These chips have been deployed in a wide range of phones and cars to secure car entry and start and are projected for secure contactless payments, home locks, and contact tracing systems. Our attack operates without any knowledge of cryptographic material, results in distance reductions from 12m (actual distance) to 0m (spoofed distance) with attack success probabilities of up to 4%, and requires only an inexpensive (USD 65) off-the-shelf device. Access control can only tolerate sub-second latencies to not inconvenience the user, leaving little margin to perform time-consuming verifications. These distance reductions bring into question the use of UWB HRP in security-critical applications.

Mikhail Fomichev, Luis F. Abanto-Leon, Max Stiegler et al.

Context-based copresence detection schemes are a necessary prerequisite to building secure and usable authentication systems in the Internet of Things (IoT). Such schemes allow one device to verify proximity of another device without user assistance utilizing their physical context (e.g., audio). The state-of-the-art copresence detection schemes suffer from two major limitations: (1) they cannot accurately detect copresence in low-entropy context (e.g., empty room with few events occurring) and insufficiently separated environments (e.g., adjacent rooms), (2) they require devices to have common sensors (e.g., microphones) to capture context, making them impractical on devices with heterogeneous sensors. We address these limitations, proposing Next2You, a novel copresence detection scheme utilizing channel state information (CSI). In particular, we leverage magnitude and phase values from a range of subcarriers specifying a Wi-Fi channel to capture a robust wireless context created when devices communicate. We implement Next2You on off-the-shelf smartphones relying only on ubiquitous Wi-Fi chipsets and evaluate it based on over 95 hours of CSI measurements that we collect in five real-world scenarios. Next2You achieves error rates below 4%, maintaining accurate copresence detection both in low-entropy context and insufficiently separated environments. We also demonstrate the capability of Next2You to work reliably in real-time and its robustness to various attacks.

Jiska Classen, Matthias Hollick

Bluetooth pairing establishes trust on first use between two devices by creating a shared key. Similar to certificate warnings in TLS, the Bluetooth specification requires warning users upon issues with this key, because this can indicate ongoing Machine-in-the-Middle (MitM) attacks. This paper uncovers that none of the major Bluetooth stacks warns users, which violates the specification. Clear warnings would protect users from recently published and potential future security issues in Bluetooth authentication and encryption.

Max Maass, Henning Pridöhl, Dominik Herrmann et al.

Researchers help operators of vulnerable and non-compliant internet services by individually notifying them about security and privacy issues uncovered in their research. To improve efficiency and effectiveness of such efforts, dedicated notification studies are imperative. As of today, there is no comprehensive documentation of pitfalls and best practices for conducting such notification studies, which limits validity of results and impedes reproducibility. Drawing on our experience with such studies and guidance from related work, we present a set of guidelines and practical recommendations, including initial data collection, sending of notifications, interacting with the recipients, and publishing the results. We note that future studies can especially benefit from extensive planning and automation of crucial processes, i.e., activities that take place well before the first notifications are sent.

Max Maass, Marc-Pascal Clement, Matthias Hollick

In the era of large-scale internet scanning, misconfigured websites are a frequent cause of data leaks and security incidents. Previous research has investigated sending automated email notifications to operators of insecure or compromised websites, but has often met with limited success due to challenges in address data quality, spam filtering, and operator distrust and disinterest. While several studies have investigated the design and phrasing of notification emails in a bid to increase their effectiveness, the use of other contact channels has remained almost completely unexplored due to the required effort and cost. In this paper, we investigate two methods to increase notification success: the use of letters as an alternative delivery medium, and the description of attack scenarios to incentivize remediation. We evaluate these factors as part of a notification campaign utilizing manually-collected address information from 1359 German website operators and focusing on unintentional information leaks from web servers. We find that manually collected addresses lead to large increases in delivery rates compared to previous work, and letters were markedly more effective than emails, increasing remediation rates by up to 25 percentage points. Counterintuitively, providing detailed descriptions of possible attacks can actually *decrease* remediation rates, highlighting the need for more research into how notifications are perceived by recipients.

Mikhail Fomichev, Julia Hesse, Lars Almon et al.

With the advent of the Internet of Things (IoT), establishing a secure channel between smart devices becomes crucial. Recent research proposes zero-interaction pairing (ZIP), which enables pairing without user assistance by utilizing devices' physical context (e.g., ambient audio) to obtain a shared secret key. The state-of-the-art ZIP schemes suffer from three limitations: (1) prolonged pairing time (i.e., minutes or hours), (2) vulnerability to brute-force offline attacks on a shared key, and (3) susceptibility to attacks caused by predictable context (e.g., replay attack) because they rely on limited entropy of physical context to protect a shared key. We address these limitations, proposing FastZIP, a novel ZIP scheme that significantly reduces pairing time while preventing offline and predictable context attacks. In particular, we adapt a recently introduced Fuzzy Password-Authenticated Key Exchange (fPAKE) protocol and utilize sensor fusion, maximizing their advantages. We instantiate FastZIP for intra-car device pairing to demonstrate its feasibility and show how the design of FastZIP can be adapted to other ZIP use cases. We implement FastZIP and evaluate it by driving four cars for a total of 800 km. We achieve up to three times shorter pairing time compared to the state-of-the-art ZIP schemes while assuring robust security with adversarial error rates below 0.5%.

Alexander Heinrich, Milan Stute, Tim Kornhuber et al.

Overnight, Apple has turned its hundreds-of-million-device ecosystem into the world's largest crowd-sourced location tracking network called offline finding (OF). OF leverages online finder devices to detect the presence of missing offline devices using Bluetooth and report an approximate location back to the owner via the Internet. While OF is not the first system of its kind, it is the first to commit to strong privacy goals. In particular, OF aims to ensure finder anonymity, untrackability of owner devices, and confidentiality of location reports. This paper presents the first comprehensive security and privacy analysis of OF. To this end, we recover the specifications of the closed-source OF protocols by means of reverse engineering. We experimentally show that unauthorized access to the location reports allows for accurate device tracking and retrieving a user's top locations with an error in the order of 10 meters in urban areas. While we find that OF's design achieves its privacy goals, we discover two distinct design and implementation flaws that can lead to a location correlation attack and unauthorized access to the location history of the past seven days, which could deanonymize users. Apple has partially addressed the issues following our responsible disclosure. Finally, we make our research artifacts publicly available.

Luis F. Abanto-Leon, Andreas Baeuml, Gek Hong et al.

The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric fingerprint. This fingerprint can be used as an additional means of authentication to enhance security. In fact, recent works propose practical fingerprinting solutions that can be readily implemented in commercial-off-the-shelf devices. In this paper, we prove analytically and experimentally that these solutions are highly vulnerable to impersonation attacks. We also demonstrate that such a unique device-based signature can be abused to violate privacy by tracking the user device, and, as of today, users do not have any means to prevent such privacy attacks other than turning off the device. We propose RF-Veil, a radiometric fingerprinting solution that not only is robust against impersonation attacks but also protects user privacy by obfuscating the radiometric fingerprint of the transmitter for non-legitimate receivers. Specifically, we introduce a randomized pattern of phase errors to the transmitted signal such that only the intended receiver can extract the original fingerprint of the transmitter. In a series of experiments and analyses, we expose the vulnerability of adopting naive randomization to statistical attacks and introduce countermeasures. Finally, we show the efficacy of RF-Veil experimentally in protecting user privacy and enhancing security. More importantly, our proposed solution allows communicating with other devices, which do not employ RF-Veil.

Max Maass, Alina Stöver, Henning Pridöhl et al.

Misconfigurations and outdated software are a major cause of compromised websites and data leaks. Past research has proposed and evaluated sending automated security notifications to the operators of misconfigured websites, but encountered issues with reachability, mistrust, and a perceived lack of importance. In this paper, we seek to understand the determinants of effective notifications. We identify a data protection misconfiguration that affects 12.7 % of the 1.3 million websites we scanned and opens them up to legal liability. Using a subset of 4754 websites, we conduct a multivariate randomized controlled notification experiment, evaluating contact medium, sender, and framing of the message. We also include a link to a public web-based self-service tool that is run by us in disguise and conduct an anonymous survey of the notified website owners (N=477) to understand their perspective. We find that framing a misconfiguration as a problem of legal compliance can increase remediation rates, especially when the notification is sent as a letter from a legal research group, achieving remediation rates of 76.3 % compared to 33.9 % for emails sent by computer science researchers warning about a privacy issue. Across all groups, 56.6 % of notified owners remediated the issue, compared to 9.2 % in the control group. In conclusion, we present factors that lead website owners to trust a notification, show what framing of the notification brings them into action, and how they can be supported in remediating the issue.

Jörn Tillmanns, Jiska Classen, Felix Rohrbach et al.

Bluetooth chips must include a Random Number Generator (RNG). This RNG is used internally within cryptographic primitives but also exposed to the operating system for chip-external applications. In general, it is a black box with security-critical authentication and encryption mechanisms depending on it. In this paper, we evaluate the quality of RNGs in various Broadcom and Cypress Bluetooth chips. We find that the RNG implementation significantly changed over the last decade. Moreover, most devices implement an insecure Pseudo-Random Number Generator (PRNG) fallback. Multiple popular devices, such as the Samsung Galaxy S8 and its variants as well as an iPhone, rely on the weak fallback due to missing a Hardware Random Number Generator (HRNG). We statistically evaluate the output of various HRNGs in chips used by hundreds of millions of devices. While the Broadcom and Cypress HRNGs pass advanced tests, it remains indistinguishable for users if a Bluetooth chip implements a secure RNG without an extensive analysis as in this paper. We describe our measurement methods and publish our tools to enable further public testing.

Jan Ruge, Jiska Classen, Francesco Gringoli et al.

Wireless communication standards and implementations have a troubled history regarding security. Since most implementations and firmwares are closed-source, fuzzing remains one of the main methods to uncover Remote Code Execution (RCE) vulnerabilities in deployed systems. Generic over-the-air fuzzing suffers from several shortcomings, such as constrained speed, limited repeatability, and restricted ability to debug. In this paper, we present Frankenstein, a fuzzing framework based on advanced firmware emulation, which addresses these shortcomings. Frankenstein brings firmware dumps "back to life", and provides fuzzed input to the chip's virtual modem. The speed-up of our new fuzzing method is sufficient to maintain interoperability with the attached operating system, hence triggering realistic full-stack behavior. We demonstrate the potential of Frankenstein by finding three zero-click vulnerabilities in the Broadcom and Cypress Bluetooth stack, which is used in most Apple devices, many Samsung smartphones, the Raspberry Pis, and many others. Given RCE on a Bluetooth chip, attackers may escalate their privileges beyond the chip's boundary. We uncover a Wi-Fi/Bluetooth coexistence issue that crashes multiple operating system kernels and a design flaw in the Bluetooth 5.2 specification that allows link key extraction from the host. Turning off Bluetooth will not fully disable the chip, making it hard to defend against RCE attacks. Moreover, when testing our chip-based vulnerabilities on those devices, we find BlueFrag, a chip-independent Android RCE.

Davide Toldo, Jiska Classen, Matthias Hollick

In this demo, we provide an overview of the macOS Bluetooth stack internals and gain access to undocumented low-level interfaces. We leverage this knowledge to add macOS support to the InternalBlue firmware modification and wireless experimentation framework.

Jiska Classen, Matthias Hollick

Multiple initiatives propose utilizing Bluetooth Low Energy (BLE) advertisements for contact tracing and SARS-CoV-2 exposure notifications. This demo shows a research tool to analyze BLE advertisements; if universally enabled by the vendors, the uncovered features could improve exposure notifications for everyone. We reverse-engineer the firmware-internal implementation of BLE advertisements on Broadcom and Cypress chips and show how to extract further physical-layer information at the receiver. The analyzed firmware works on hundreds of millions of devices, such as all iPhones, the European Samsung Galaxy S series, and Raspberry Pis.

Mikhail Fomichev, Max Maass, Matthias Hollick

Reproducibility and realistic datasets are crucial for advancing research. Unfortunately, they are often neglected as valid scientific contributions in many young disciplines, with computer science being no exception. In this article, we show the challenges encountered when reproducing the work of others, collecting realistic data in the wild, and ensuring that our own work is reproducible in turn. The presented findings are based on our study investigating the limits of zero-interaction security (ZIS) -- a novel concept, leveraging sensor data collected by Internet of Things (IoT) devices to pair or authenticate devices. In particular, we share our experiences in reproducing five state-of-the-art ZIS schemes, collecting a comprehensive dataset of sensor data from the real world, evaluating these schemes on the collected data, and releasing the data, code, and documentation to facilitate reproducibility of our results. In our discussion, we outline general considerations when conducting similar studies and give specific examples of technical and methodological issues that we experienced. We hope that our findings will raise awareness about the importance of reproducibility and realistic datasets in computer science and inform future research.

Dennis Mantz, Jiska Classen, Matthias Schulz et al.

Bluetooth is one of the most established technologies for short range digital wireless data transmission. With the advent of wearables and the Internet of Things (IoT), Bluetooth has again gained importance, which makes security research and protocol optimizations imperative. Surprisingly, there is a lack of openly available tools and experimental platforms to scrutinize Bluetooth. In particular, system aspects and close to hardware protocol layers are mostly uncovered. We reverse engineer multiple Broadcom Bluetooth chipsets that are widespread in off-the-shelf devices. Thus, we offer deep insights into the internal architecture of a popular commercial family of Bluetooth controllers used in smartphones, wearables, and IoT platforms. Reverse engineered functions can then be altered with our InternalBlue Python framework---outperforming evaluation kits, which are limited to documented and vendor-defined functions. The modified Bluetooth stack remains fully functional and high-performance. Hence, it provides a portable low-cost research platform. InternalBlue is a versatile framework and we demonstrate its abilities by implementing tests and demos for known Bluetooth vulnerabilities. Moreover, we discover a novel critical security issue affecting a large selection of Broadcom chipsets that allows executing code within the attacked Bluetooth firmware. We further show how to use our framework to fix bugs in chipsets out of vendor support and how to add new security features to Bluetooth firmware.

Mikhail Fomichev, Max Maass, Lars Almon et al.

The Internet of Things (IoT) demands authentication systems which can provide both security and usability. Recent research utilizes the rich sensing capabilities of smart devices to build security schemes operating without human interaction, such as zero-interaction pairing (ZIP) and zero-interaction authentication (ZIA). Prior work proposed a number of ZIP and ZIA schemes and reported promising results. However, those schemes were often evaluated under conditions which do not reflect realistic IoT scenarios. In addition, drawing any comparison among the existing schemes is impossible due to the lack of a common public dataset and unavailability of scheme implementations. In this paper, we address these challenges by conducting the first large-scale comparative study of ZIP and ZIA schemes, carried out under realistic conditions. We collect and release the most comprehensive dataset in the domain to date, containing over 4250 hours of audio recordings and 1 billion sensor readings from three different scenarios, and evaluate five state-of-the-art schemes based on these data. Our study reveals that the effectiveness of the existing proposals is highly dependent on the scenario they are used in. In particular, we show that these schemes are subject to error rates between 0.6% and 52.8%.

Max Maass, Nicolas Walter, Dominik Herrmann et al.

Today, online privacy is the domain of regulatory measures and privacy-enhancing technologies. Transparency in the form of external and public assessments has been proposed for improving privacy and security because it exposes otherwise hidden deficiencies. Previous work has studied privacy attitudes and behavior of consumers. However, little is known on how organizations react to measures that employ public "naming and shaming" as an incentive for improvement. We performed the first study on this aspect by conducting a qualitative survey with 152 German health insurers. We scanned their websites with PrivacyScore.org to generate a public ranking and confronted the insurers with the results. We obtained a response rate of 27%. Responses ranged from positive feedback to legal threats. Only 12% of the sites - mostly non-responders - improved during our study. Our results show that insurers struggle due to unawareness, reluctance, and incapability, and demonstrate the general difficulties of transparency-based approaches.

Flor Álvarez, Max Kolhagen, Matthias Hollick

Practical solutions to bootstrap security in today's information and communication systems critically depend on centralized services for authentication as well as key and trust management. This is particularly true for mobile users. Identity providers such as Google or Facebook have active user bases of two billion each, and the subscriber number of mobile operators exceeds five billion unique users as of early 2018. If these centralized services go completely `dark' due to natural or man made disasters, large scale blackouts, or country-wide censorship, the users are left without practical solutions to bootstrap security on their mobile devices. Existing distributed solutions, for instance, the so-called web-of-trust are not sufficiently lightweight. Furthermore, they support neither cross-application on mobile devices nor strong protection of key material using hardware security modules. We propose Sea of Lights(SoL), a practical lightweight scheme for bootstrapping device-to-device security wirelessly, thus, enabling secure distributed self-organized networks. It is tailored to operate `in the dark' and provides strong protection of key material as well as an intuitive means to build a lightweight web-of-trust. SoL is particularly well suited for local or urban operation in scenarios such as the coordination of emergency response, where it helps containing/limiting the spreading of misinformation. As a proof of concept, we implement SoL in the Android platform and hence test its feasibility on real mobile devices. We further evaluate its key performance aspects using simulation.

Roland Kluge, Michael Stein, Gergely Varró et al.

In the communication systems domain, constructing and maintaining network topologies via topology control (TC) algorithms is an important cross-cutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of TC algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of TC algorithms. Furthermore, even though many TC algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of TC algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual TC algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; TC algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given TC algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of TC algorithms. To show the feasibility of our approach, we reneging six existing TC algorithms and develop e-kTC, a novel energy-efficient variant of the TC algorithm kTC. Finally, we evaluate a subset of the specified TC algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.

Roland Kluge, Michael Stein, Gergely Varró et al.

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approach

Mikhail Fomichev, Flor Álvarez, Daniel Steinmetzer et al.

Secure Device Pairing (SDP) schemes have been developed to facilitate secure communications among smart devices, both personal mobile devices and Internet of Things (IoT) devices. Comparison and assessment of SDP schemes is troublesome, because each scheme makes different assumptions about out-of-band channels and adversary models, and are driven by their particular use-cases. A conceptual model that facilitates meaningful comparison among SDP schemes is missing. We provide such a model. In this article, we survey and analyze a wide range of SDP schemes that are described in the literature, including a number that have been adopted as standards. A system model and consistent terminology for SDP schemes are built on the foundation of this survey, which are then used to classify existing SDP schemes into a taxonomy that, for the first time, enables their meaningful comparison and analysis.The existing SDP schemes are analyzed using this model, revealing common systemic security weaknesses among the surveyed SDP schemes that should become priority areas for future SDP research, such as improving the integration of privacy requirements into the design of SDP schemes. Our results allow SDP scheme designers to create schemes that are more easily comparable with one another, and to assist the prevention of persisting the weaknesses common to the current generation of SDP schemes.

Hossein Fereidooni, Jiska Classen, Tom Spink et al.

Tens of millions of wearable fitness trackers are shipped yearly to consumers who routinely collect information about their exercising patterns. Smartphones push this health-related data to vendors' cloud platforms, enabling users to analyze summary statistics on-line and adjust their habits. Third-parties including health insurance providers now offer discounts and financial rewards in exchange for such private information and evidence of healthy lifestyles. Given the associated monetary value, the authenticity and correctness of the activity data collected becomes imperative. In this paper, we provide an in-depth security analysis of the operation of fitness trackers commercialized by Fitbit, the wearables market leader. We reveal an intricate security through obscurity approach implemented by the user activity synchronization protocol running on the devices we analyze. Although non-trivial to interpret, we reverse engineer the message semantics, demonstrate how falsified user activity reports can be injected, and argue that based on our discoveries, such attacks can be performed at scale to obtain financial gains. We further document a hardware attack vector that enables circumvention of the end-to-end protocol encryption present in the latest Fitbit firmware, leading to the spoofing of valid encrypted fitness data. Finally, we give guidelines for avoiding similar vulnerabilities in future system designs.