Elektrotechnik und Informatik (ETI)
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A communication over an Internet Protocol (IP) based network fails if an endpoint sends packets that are too big to reach their destination and if the sender is unable to detect that. The node on the path that drops these packets should respond with a Packet Too Big (PTB) message. However, multiple scenarios exist in which the sender will not receive a PTB message. Even if it does, it refrains from using the information in case it suspects that a potential attacker forged the message. In particular, we are not aware of any implementation of the secure transport protocol QUIC (e.g., used by HTTP/3) that processes PTB messages. In this paper, we present a novel parameterizable PTB detection algorithm for reliable transport protocols that does not depend on PTB messages. We further describe how to integrate our algorithm into QUIC, present results from an evaluation using the algorithm within a QUIC simulation model and, based on these results, suggest concrete parameter values.
The demand for energy storage is increasing massively due to the electrification of transport and the expansion of renewable energies. Current battery technologies cannot satisfy this growing demand as they are difficult to recycle, as the necessary raw materials are mined under precarious conditions, and as the energy density is insufficient. Metal–air batteries offer a high energy density as there is only one active mass inside the cell and the cathodic reaction uses the ambient air. Various metals can be used, but zinc is very promising due to its disposability and non-toxic behavior, and as operation as a secondary cell is possible. Typical characteristics of zinc–air batteries are flat charge and discharge curves. On the one hand, this is an advantage for the subsequent power electronics, which can be optimized for smaller and constant voltage ranges. On the other hand, the state determination of the system becomes more complex, as the voltage level is not sufficient to determine the state of the battery. In this context, electrochemical impedance spectroscopy is a promising candidate as the resulting impedance spectra depend on the state of charge, working point, state of aging, and temperature. Previous approaches require a fixed operating state of the cell while impedance measurements are being performed. In this publication, electrochemical impedance spectroscopy is therefore combined with various machine learning techniques to also determine successfully the state of charge during charging of the cell at non-fixed charging currents.
Keywords:
electrochemical impedance spectroscopy; artificial neural networks; support vector regression; zinc-air battery; state estimation; state of charge
Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in nano- or micro-diamonds is a promising technology for precise magnetic-field sensors. Here, we propose a new, low-cost and stand-alone sensor setup that employs machine learning on an embedded device, so-called edge machine learning. We train an artificial neural network with data acquired from a continuous-wave ODMR setup and subsequently use this pre-trained network on the sensor device to deduce the magnitude of the magnetic field from recorded ODMR spectra. In our proposed sensor setup, a low-cost and low-power ESP32 microcontroller development board is employed to control data recording and perform inference of the network. In a proof-of-concept study, we show that the setup is capable of measuring magnetic fields with high precision and has the potential to enable robust and accessible sensor applications with a wide measuring range.
S/MIME and OpenPGP use cryptographic constructions repeatedly shown to be vulnerable to format oracle attacks in protocols like TLS, SSH, or IKE. However, format oracle attacks in the End-to-End Encryption (E2EE) email setting are considered impractical as victims would need to open many attacker-modified emails and communicate the decryption result to the attacker. But is this really the case?
In this paper, we survey how an attacker may remotely learn the decryption state in email E2EE. We analyze the interplay of MIME and IMAP and describe side-channels emerging from network patterns that leak the decryption status in Mail User Agents (MUAs). Concretely, we introduce specific MIME trees that produce decryption-dependent net work patterns when opened in a victim’s email client.
We survey 19 OpenPGP- and S/MIME-enabled email clients and four cryptographic libraries and uncover a side-channel leaking the decryption status of S/MIME messages in one client. Further, we discuss why the exploitation in the other clients is impractical and show that it is due to missing feature support and implementation quirks. These unintended defenses create an unfortunate conflict between usability and security. We present more rigid countermeasures for MUA developers and the standards to prevent exploitation.
OpenPGP is one of the two major standards for end-to-end email security. Several studies showed that serious usability issues exist with tools implementing this standard. However, a widespread assumption is that expert users can handle these tools and detect signature spoofing attacks. We present a user study investigating expert users' strategies to detect signature spoofing attacks in Thunderbird. We observed 25 expert users while they classified eight emails as either having a legitimate signature or not. Studying expert users explicitly gives us an upper bound of attack detection rates of all users dealing with PGP signatures. 52% of participants fell for at least one out of four signature spoofing attacks. Overall, participants did not have an established strategy for evaluating email signature legitimacy. We observed our participants apply 23 different types of checks when inspecting signed emails, but only 8 of these checks tended to be useful in identifying the spoofed or invalid signatures. In performing their checks, participants were frequently startled, confused, or annoyed with the user interface, which they found supported them little. All these results paint a clear picture: Even expert users struggle to verify email signatures, usability issues in email security are not limited to novice users, and developers may need proper guidance on implementing email signature GUIs correctly.
Quick UDP Internet Connections (QUIC) is a novel transport protocol introducing known features in a new protocol design. To investigate these features and the design, we developed a QUIC implementation in the INET simulation model suite.
In this paper, we describe that implementation, its validation and a result achieved using the simulation model. The result shows the negative impact on throughput, when raising the acknowledgment ratio. We propose a solution and describe how it solves the issue.
A data sender in an IP based network is only capable to efficiently use a network path if it knows the packet size limit of the path, i.e., the Path Maximum Transmission Unit (PMTU). The IETF recently specified a PMTU discovery framework for transport protocols like QUIC. This paper complements this specification by presenting a search algorithm. In addition, it defines several metrics and shows results of analyses for the algorithm with various PMTU candidate sequences using these metrics. We integrated the PMTU discovery with our algorithm into a QUIC simulation model. This paper describes the integration and presents measurements obtained by simulations.
Technical and organizational steps are necessary to mitigate cyber threats and reduce risks. Human behavior is the last line of defense for many hospitals and is considered as equally important as technical security. Medical staff must be properly trained to perform such procedures. This paper presents the first qualitative, interdisciplinary research on how members of an intermediate care unit react to a cyberattack against their patient monitoring equipment. We conducted a simulation in a hospital training environment with 20 intensive care nurses. By the end of the experiment, 12 of the 20 participants realized the monitors’ incorrect behavior. We present a qualitative behavior analysis of high performing participants (HPP) and low performing participants (LPP). The HPP showed fewer signs of stress, were easier on their colleagues, and used analog systems more often than the LPP. With 40% of our participants not recognizing the attack, we see room for improvements through the use of proper tools and provision of adequate training to prepare staff for potential attacks in the future.