The application of convolutional neural networks (CNNs) to break cryptographic systems through hardware side-channels facilitated rapid and adaptable attacks on cryptographic systems like smart cards and Trusted Platform Modules (TPMs). However, current approaches rely on manually designed CNN architectures by domain experts, which are time-consuming and impractical for attacking new systems. To overcome this, recent research has delved into the use of neural architecture search (NAS) to discover appropriate CNN architectures automatically. This approach aims to alleviate the burden on human experts and facilitate more efficient exploration of new attack targets. However, these works only optimize the architecture using the secret key information from the attack dataset and explore limited search strategies with one-dimensional CNNs. In this work, we propose a fully black-box NAS approach that solely utilizes the profiling dataset for optimization. Through an extensive experimental parameter study, we investigate which choices for NAS, such as using 1-D or 2-D CNNs and various search strategies, produce the best results on 10 state-of-the-art datasets for identity leakage model. Our results demonstrate that applying the Random search strategy on 1-D inputs achieves a high success rate, enabling retrieval of the correct secret key using a single attack trace on two datasets. This combination matches the attack efficiency of fixed CNN architectures and outperforms them in 4 out of 10 datasets. Our experiments also emphasize the importance of repeated attack evaluations for ML-based solutions to avoid biased performance estimates.

Due to the proliferation of a large amount of publicly available data, information leakage (IL) has become a major problem. IL occurs when secret (sensitive) information of a system is inadvertently disclosed to unauthorized parties through externally observable information. Standard statistical approaches estimate the mutual information between observable (input) and secret information (output), which tends to be a difficult problem for high-dimensional input. Current approaches based on (supervised) machine learning using the accuracy of predictive models on extracted system input and output have proven to be more effective in detecting these leakages. However, these approaches are domain-specific and fail to account for imbalance in the dataset. In this paper, we present a robust autonomous approach to detecting IL, which blends machine learning and statistical techniques, to overcome these shortcomings. We propose to use Fisher’s Exact Test (FET) on the evaluated confusion matrix, which inherently takes the imbalances in the dataset into account. As a use case, we consider the problem of detecting padding side-channels or ILs in systems implementing cryptographic protocols. In an extensive experimental study on detecting ILs in synthetic and real-world scenarios, our approach outperforms the state of the art.

Molecular communication has been identified as a communication concept complementing radio communication in some areas and being the unique solution in others. This particularly includes communication between nano machines but, more recently, also macroscopic application domains such as in fluid systems in a chemical factory. We are interested in simulating such macroscopic molecular communication both accurately as well as on a large scale. In this work, we make use of the concept of vector fields for efficient simulation of particle movements in a fluid environment. Such vector fields can be pre-computed so that the simulation of the communication itself is very fast. We discuss both the concepts and the methodological approach to outline the advantages of this idea and validate the system compared to lab measurements. Going beyond previous work, we also integrated both on-off keying (OOK) and pulse position modulation (PPM) to demonstrate the feasibility of the simulation concept even for more complex signal processing tasks.

Currently most practical attacks on cryptographic protocols like TLS are based on side channels, such as padding oracles. Some well-known recent examples are DROWN, ROBOT and Raccoon (USENIX Security 2016, 2018, 2021). Such attacks are usually found by careful and time-consuming manual analysis by specialists. In this paper, we consider the question of how such attacks can be systematically detected and prevented before (large-scale) deployment. We propose a new, fully automated approach, which uses supervised learning to identify arbitrary patterns in network protocol traffic. In contrast to classical scanners, which search for known side channels, the detection of general patterns might detect new side channels, even unexpected ones, such as those from the ROBOT attack. To analyze this approach, we develop a tool to detect Bleichenbacher-like padding oracles in TLS server implementations, based on an ensemble of machine learning algorithms. We verify that the approach indeed detects known vulnerabilities successfully and reliably. The tool also provides detailed information about detected patterns to developers, to assist in removing a potential padding oracle. Due to the automation, the approach scales much better than manual analysis and could even be integrated with a CI/CD pipeline of a development environment, for example.

Molecular communication can enable transmission of information within industrial networks comprising of pipes, ducts, etc. This work emulates the system by introducing an air-based macroscopic molecular communication testbed, exploiting the fluorescence property of a water-based solution of an organic compound called fluorescein. An efficient transmitter in the form of an industrial sprayer, coupled with a high-speed camera-based detection, eventually paves way to achieve higher data transmission rates. The transmission distances considered are in the range of several centimeters to meters. Additionally, models for spray nozzle injector and camera receiver are described to simulate the testbed in a particle-based simulator. These simulated models are calibrated to the used transmitter and receiver and are compared with the analytical models obtained from the testbed measurements.

Molecular communication in pipe networks is a novel technique for wireless data exchange. Simulating such networks accurately is difficult because of the complexity of fluid dynamics at centimeter scales, which existing molecular communication simulators do not model. The new simulator we present combines computational fluid dynamics simulation and particle movement predictions. It is optimized to be computationally efficient while offering a high degree of adaptability to complex fluid flows in larger pipe networks. We validate it by comparing the simulation with experimental results obtained in a real-world testbed.

Modern cryptographic protocols, such as TLS 1.3 and QUIC, can send cryptographically protected data in "zero round-trip times (0-RTT)", that is, without the need for a prior interactive handshake. Such protocols meet the demand for communication with minimal latency, but those currently deployed in practice achieve only rather weak security properties, as they may not achieve forward security for the first transmitted payload message and require additional countermeasures against replay attacks. Recently, 0-RTT protocols with full forward security and replay resilience have been proposed in the academic literature. These are based on puncturable encryption, which uses rather heavy building blocks, such as cryptographic pairings. Some constructions were claimed to have practical efficiency, but it is unclear how they compare concretely to protocols deployed in practice, and we currently do not have any benchmark results that new protocols can be compared with. We provide the first concrete performance analysis of a modern 0-RTT protocol with full forward security, by integrating the Bloom Filter Encryption scheme of Derler et al. (EUROCRYPT 2018) in the Chromium QUIC implementation and comparing it to Google's original QUIC protocol. We find that for reasonable deployment parameters, the server CPU load increases approximately by a factor of eight and the memory consumption on the server increases significantly, but stays below 400MB even for medium-scale deployments that handle up to 50K connections per day. The difference of the size of handshake messages is small enough that transmission time on the network is identical, and therefore not significant. We conclude that while current 0-RTT protocols with full forward security come with significant computational overhead, their use in practice is feasible, and may be used in applications where the increased CPU and memory load can be tolerated in exchange for full forward security and replay resilience on the cryptographic protocol level. Our results serve as a first benchmark that can be used to assess the efficiency of 0-RTT protocols potentially developed in the future.

Data taken by the DELPHI experiment at centre-of-mass energies of 183 GeV and 189 GeV with a total integrated luminosity of 212 pb^{-1} have been used to search for the supersymmetric partners of the electrons, muons, and taus in the context of the Minimal Supersymmetric Standard Model (MSSM). The decay topologies searched for were the direct decay ({\tilde \ell} -> \ell {\tilde \chi_1^0}), producing acoplanar lepton pairs plus missing energy, and the cascade decay ({\tilde \ell} -> \ell {\tilde \chi_2^0} > \ell \gamma {\tilde \chi_1^0}), producing acoplanar lepton and photon pairs plus missing energy. The observed number of events is in agreement with Standard Model predictions. The 95% CL excluded mass limits for selectrons, smuons and staus are m_{\tilde {e}} \leq 87 GeV/c^2, m_{\tilde {\mu}} \leq 80 GeV/c^2 and m_{\tilde {\tau}} \leq 75 GeV/c^2, respectively, for values of \mu=-200 GeV/c^2 and tan(beta)=1.5.

DELPHI results are presented on the inclusive production of the neutral mesons , f0(980), f2(1270), K 0 2 (1430) and f 0 2(1525) in hadronic Z 0 decays. They are based on about 2 million multihadronic events collected in 1994 and 1995, using the particle identi cation capabilities of the DELPHI Ring Imaging Cherenkov detectors and measured ionization losses in the Time Projection Chamber. The total production rates per hadronic Z decay have been determined to be: 1:19 0:10 for ; 0:164 0:021 for f0(980); 0:214 0:038 for f2(1270); 0:073 0:023 for K 0 2 (1430); and 0:012 0:006 for f 0 2(1525). The total production rates for all mesons and di erential cross-sections for the , f0(980) and f2(1270) are compared with the results of other LEP experiments and with models. (Accepted by Physics Letters B)

F rom the analysis of a data sample corresponding to an integrated luminosity of 4.63 pb -1 taken during the 1990 run of LEP at centre of mass energies between 88.2GeV an 94.2GeV, the tau decays r ~ e g e v T , r -* ,u-~ .v~ , r ~ z c ( K ) v T , r r p v ~ and their charge conjugates have been studied. The following branching ratios have been measured; B R ( r ~ e aTeVT) = 18.6 + 0.8 (stat.) _ 0.6 (sys.)%, BR (z---+ /~17u vT) = 17.4 • 0.7 + 0.6%, B R ( r ~ z c ( K ) v T ) = 11.9_+0.7_ 0.7%, BR ( r > p vT) = 22.4 + 0.8 + 1.3%, in good agreement with world averages. The measured electronic and muonic branching ratios lead to a measurement of the strong coupling constant, es (mT) = 0.26 + 0.09 Extrapolating the c L value from -0 .12" m T to m z yields cL(mz)=0 .109 +0.012 0.028" The average polarization P~ of taus produced in Z---, r + r decays has also been measured using the above decay modes. The weighted mean of the polarizations obtained from the four decay modes is PT = 0.24 _+ 0.07. This value of PT gives, in the improved Born approximation, a ratio between the axial and vector coupling constants of the tau of vT/aT=0.12+__O.04, and hence a value of the effective electroweak mixing parameter sin 2 0 w(m~) = 0.220 _ 0.009.

The hadronic part of the electron structure function F2e has been measured for the first time, using e+e− data collected by the DELPHI experiment at LEP, at centre-of-mass energies of s=91.2–209.5 GeV. The data analysis is simpler than that of the measurement of the photon structure function. The electron structure function F2e data are compared to predictions of phenomenological models based on the photon structure function. It is shown that the contribution of large target photon virtualities is significant. The data presented can serve as a cross-check of the photon structure function F2γ analyses and help in refining existing parameterisations.