Biblio

As demonstrated recently, Wireless Physical Layer Security (WPLS) has the potential to offer substantial advantages for key management for small resource-constrained and, therefore, low-cost IoT-devices, e.g., the widely applied 8-bit MCU 8051. In this paper, we present a WPLS testbed implementation for independent performance and security evaluations. The testbed is based on off-the-shelf hardware and utilizes the IEEE 802.15.4 communication standard for key extraction and secret key rate estimation in real-time. The testbed can include generically multiple transceivers to simulate legitimate parties or eavesdropper. We believe with the testbed we provide a first step to make experimental-based WPLS research results comparable. As an example, we present evaluation results of several test cases we performed, while for further information we refer to https://pls.rub.de.

High-accuracy localization is a prerequisite for many wireless applications. To obtain accurate location information, it is often required to share users' positional knowledge and this brings the risk of leaking location information to adversaries during the localization process. This paper develops a theory and algorithms for protecting location secrecy. In particular, we first introduce a location secrecy metric (LSM) for a general measurement model of an eavesdropper. Compared to previous work, the measurement model accounts for parameters such as channel conditions and time offsets in addition to the positions of users. We determine the expression of the LSM for typical scenarios and show how the LSM depends on the capability of an eavesdropper and the quality of the eavesdropper's measurement. Based on the insights gained from the analysis, we consider a case study in wireless localization network and develop an algorithm that diminish the eavesdropper's capabilities by exploiting the reciprocity of channels. Numerical results show that the proposed algorithm can effectively increase the LSM and protect location secrecy.

Cooperative spectrum sensing is often necessary in cognitive radios systems to localize a transmitter by fusing the measurements from multiple sensing radios. However, revealing spectrum sensing information also generally leaks information about the location of the radio that made those measurements. We propose a protocol for performing cooperative spectrum sensing while preserving the privacy of the sensing radios. In this protocol, radios fuse sensing information through a distributed particle filter based on a tree structure. All sensing information is encrypted using public-key cryptography, and one of the radios serves as an anonymizer, whose role is to break the connection between the sensing radios and the public keys they use. We consider a semi-honest (honest-but-curious) adversary model in which there is at most a single adversary that is internal to the sensing network and complies with the specified protocol but wishes to determine information about the other participants. Under this scenario, an adversary may learn the sensing information of some of the radios, but it does not have any way to tie that information to a particular radio's identity. We test the performance of our proposed distributed, tree-based particle filter using physical measurements of FM broadcast stations.

An important topic in cybersecurity is validating Active Indicators (AI), which are stimuli that can be implemented in systems to trigger responses from individuals who might or might not be Insider Threats (ITs). The way in which a person responds to the AI is being validated for identifying a potential threat and a non-threat. In order to execute this validation process, it is important to create a paradigm that allows manipulation of AIs for measuring response. The scenarios are posed in a manner that require participants to be situationally aware that they are being monitored and have to act deceptively. In particular, manipulations in the environment should no differences between conditions relative to immersion and ease of use, but the narrative should be the driving force behind non-deceptive and IT responses. The success of the narrative and the simulation environment to induce such behaviors is determined by immersion, usability, and stress response questionnaires, and performance. Initial results of the feasibility to use a narrative reliant upon situation awareness of monitoring and evasion are discussed.

Standard classification procedures of both data mining and multivariate statistics are sensitive to the presence of outlying values. In this paper, we propose new algorithms for computing regularized versions of linear discriminant analysis for data with small sample sizes in each group. Further, we propose a highly robust version of a regularized linear discriminant analysis. The new method denoted as MWCD-L2-LDA is based on the idea of implicit weights assigned to individual observations, inspired by the minimum weighted covariance determinant estimator. Classification performance of the new method is illustrated on a detailed analysis of our pilot study of authentication methods on computers, using individual typing characteristics by means of keystroke dynamics.

The aim of this study is to examine the utility of physiological compliance (PC) to understand shared experience in a multiuser technological environment involving active and passive users. Common ground is critical for effective collaboration and important for multiuser technological systems that include passive users since this kind of user typically does not have control over the technology being used. An experiment was conducted with 48 participants who worked in two-person groups in a multitask environment under varied task and technology conditions. Indicators of PC were measured from participants' cardiovascular and electrodermal activities. The relationship between these PC indicators and collaboration outcomes, such as performance and subjective perception of the system, was explored. Results indicate that PC is related to group performance after controlling for task/technology conditions. PC is also correlated with shared perceptions of trust in technology among group members. PC is a useful tool for monitoring group processes and, thus, can be valuable for the design of collaborative systems. This study has implications for understanding effective collaboration.