Search Results (62)

Opacity, an important property of the information flow in discrete-event systems (DESs), characterizes whether the secret information in a system is ambiguous to a passive observer (called an intruder). Observation models play a critical role in the analysis of opacity. In this paper, instead of adopting a fully static observation model or a fully dynamic observation model, we use a novel Orwellian-type observation model to study the verification of the current-state opacity (CSO), where the observability of an unobservable event can be re-interpreted once certain/several specific conditions are met. First, a K-delay Orwellian observation mechanism (KOOM) is proposed as a novel Orwellian-type observation mechanism for extending the existing Orwellian projection. The main characteristics of the KOOM are delaying the inevitable information release and narrowing the release range for historical information to protect the secrets in a system to a greater extent than with the existing Orwellian projection. Second, we formulate the definitions of standard and strong CSO under the KOOM. Finally, we address the verification problem for these two types of opacity by constructing two novel information structures called a standard K-delay verifier and a strong K-delay verifier, respectively. An analysis of the computational complexity and illustrative examples are also presented for the proposed results. Overall, the proposed notions of standard and strong CSO under the KOOM capture the security privacy requirements regarding a delayed release in applications, such as intelligent transportation systems, etc. Full article

In the framework of the geological mapping of sheet “n. 425—Asinara Island” (NW Sardinia, Italy) of the Italian National Geological Mapping Project (CARG Project), three late- to post-collisional Variscan intrusive units are recognized: (i) Castellaccio Unit; (ii) Punta Sabina Unit; and (iii) sheeted dyke complex. Granitoid rocks from these intrusive units intruded into the medium- to high-grade metamorphic micaschist and paragneiss and the migmatitic complex. A range of deformation microstructures from sub-magmatic to low-temperature subsolidus conditions are recognized. The main observed microstructures are represented by chessboard patterns in quartz and by feldspar sub-grain rotation dynamic recrystallization, indicative of deformation at high-temperature conditions (T > 650 °C). Solid-state high-temperature deformations (T > 450 °C) are provided by feldspar bulging, myrmekites, quartz grain boundary migration and sub-grain rotation dynamic recrystallization. Low-temperature sub-solidus microstructures (T < 450 °C) consist of quartz bulging, mica kinks, and feldspar twinning and bending. These features highlight that the three intrusive units recorded tectonic stresses, which affected the granitoids during cooling without developing a strong penetrative meso/microstructural fabric, as observed in other sectors of the Variscan orogen. The complete sequence of deformation microstructures, recorded in all intrusive units, suggests a weak but still ongoing deformation regime during granitoid emplacement in the Variscan orogen of northwestern Sardinia. These observations are similar to the features highlighted in other sectors of the southern Variscan belt and suggest a complex interplay between transpressional-induced exhumation of the middle/deep crust and magma intrusion. Full article

The Banyo area, located in the southern prolongation of the Mayo Nolti shear zone trend, belongs to the western Cameroon domain of the Neoproterozoic Central African Belt (NCAB). It is made of granitic rocks that intrude metamorphic banded rocks. Both are sometimes mylonitized. The pluton is dominantly of paramagnetic behavior, as shown by the hysteresis loops and the Fe-bearing silicates crystals are the susceptibility carriers. AMS ellipsoids are dominantly of oblate shape, pointing to the importance of flattening during pluton emplacement. The anisotropy degree of magnetic susceptibility values (≤1.20) characterize the magmatic fabric flow. The microstructural study of the granite reveals magmatic, sub-magmatic, solid-state and mylonitic deformations. Field and AMS fabrics show evidence of polyphase deformation (D₁–D₃). The D₁ phase is of flattening mechanism (flat-laying foliation). The D₂ phase points to sinistral ductile simple shear accommodating moderate to steep dipping and N-S- to NW-SE-oriented foliations in plutonic and country rocks and conjugated E-W mylonitic foliation in country rocks bearing sub-horizontal- to moderate-plunge mineral stretching lineation. The D₃ phase is of dextral ductile simple shear. σ- and δ-type kinematic markers in the pluton indicate sinistral top-to-south sense of shear movement, indicating a non-coaxial component of the tectonics. The magnetic fabrics of the pluton are parallel to those of the D₂ deformation phase of the study area. The transpressive D₂ and D₃ events correlate with the D₂ and D₃ phases of the Pan-African tectonic dated at 613–585 Ma and 585–540 Ma, respectively. The pluton, then, emplaced during regional sinistral D₂ deformation under transpressive regime. The emplacement of the NE Banyo granite took place as rock strips sheared in sinistral sense of shear movement. Full article

This paper considers a target-defense game in an open area with one or two defenders as well as an intruder. The intruder endeavors to reach the boundary of the island, while the defenders strive to prevent that by capturing the intruder through contact. Islands, as closed areas, restrict the free movement of the defenders, since the defenders—represented by USVs—cannot traverse the target area directly. First, we are concerned with the barrier, which is the boundary of the winning zones, taking into account the impact of the target. For the initial states lying in the defenders’ winning zone, there exists a strategy for the defenders to intercept the intruder regardless of the intruder’s best effort, while for the initial states lying in the intruder’s winning zone, the intruder can always invade successfully. We propose a geometric method to construct the barrier analytically for two kinds of speed ratios. Then, by taking index functions into consideration, we present optimal strategies for the players after constructing the dominance regions when their initial states lie in different winning zones. Simulation results verify the effectiveness of the proposed method. This study can be extended to scenarios involving multiple defenders. Full article

In the context of discrete event systems (DESs), critical states usually refer to a system configuration of interest, describing certain important system properties, e.g., fault diagnosability, state/language opacity, and state/event concealment. Technically, a DES is critically observable if an intruder can always unambiguously infer, by observing the system output, whether the plant is currently in a predefined set of critical states or the current state set is disjointed with the critical states. In this paper, given a partially observable DES modeled with a finite-state automaton that is not critically observable, we focus on how to make it critically observable, which is achieved by proposing a novel enforcement mechanism based on differential privacy (DP). Specifically, we consider two observations where one observation cannot determine whether a system is currently in the predefined critical states (i.e., the observation violating the critical observability) while the other is randomly generated by the system. When these two observations are processed separately by the differential privacy mechanism (DPM), the system generates an output, exposed to the intruder, that is randomly modified such that its probability approximates the two observations. In other words, the intruder cannot determine the original input of a system by observing its output. In this way, even if the utilized DPM is published to the intruder, they are unable to identify whether critical observability is violated. Full article

Smart security devices, such as smart locks, smart cameras, and smart intruder alarms are increasingly popular with users due to the enhanced convenience and new features that they offer. A significant part of this convenience is provided by the device’s companion smartphone app. Information on whether secure and ethical development practices have been used in the creation of these applications is unavailable to the end user. As this work shows, this means that users are impacted both by potential third-party attackers that aim to compromise their device, and more subtle threats introduced by developers, who may track their use of their devices and illegally collect data that violate users’ privacy. Our results suggest that users of every application tested are susceptible to at least one potential commonly found vulnerability regardless of whether their device is offered by a known brand name or a lesser-known manufacturer. We present an overview of the most common vulnerabilities found in the scanned code and discuss the shortcomings of state-of-the-art automated scanners when looking at less structured programming languages such as C and C++. Finally, we also discuss potential methods for mitigation, and provide recommendations for developers to follow with respect to secure coding practices. Full article

Smart agriculture stands as a promising domain for IoT-enabled technologies, with the potential to elevate crop quality, quantity, and operational efficiency. However, implementing a smart agriculture system encounters challenges such as the high latency and bandwidth consumption linked to cloud computing, Internet disconnections in rural locales, and the imperative of cost efficiency for farmers. Addressing these hurdles, this paper advocates a fog-based smart agriculture infrastructure integrating edge computing and LoRa communication. We tackle farmers’ prime concern of animal intrusion by presenting a solution leveraging low-cost PIR sensors, cameras, and computer vision to detect intrusions and predict animal locations using an innovative algorithm. Our system detects intrusions pre-emptively, identifies intruders, forecasts their movements, and promptly alerts farmers. Additionally, we compare our proposed strategy with other approaches and measure their power consumptions, demonstrating significant energy savings afforded by our strategy. Experimental results highlight the effectiveness, energy efficiency, and cost-effectiveness of our system compared to state-of-the-art systems. Full article

Background: There is a significant need to monitor human cognitive performance in complex environments, with one example being pilot performance. However, existing assessments largely focus on subjective experiences (e.g., questionnaires) and the evaluation of behavior (e.g., aircraft handling) as surrogates for cognition or utilize brainwave measures which require artificial setups (e.g., simultaneous auditory stimuli) that intrude on the primary tasks. Blink-related oscillations (BROs) are a recently discovered neural phenomenon associated with spontaneous blinking that can be captured without artificial setups and are also modulated by cognitive loading and the external sensory environment—making them ideal for brain function assessment within complex operational settings. Methods: Electroencephalography (EEG) data were recorded from eight adult participants (five F, M = 21.1 years) while they completed the Multi-Attribute Task Battery under three different cognitive loading conditions. BRO responses in time and frequency domains were derived from the EEG data, and comparisons of BRO responses across cognitive loading conditions were undertaken. Simultaneously, assessments of blink behavior were also undertaken. Results: Blink behavior assessments revealed decreasing blink rate with increasing cognitive load (p < 0.001). Prototypical BRO responses were successfully captured in all participants (p < 0.001). BRO responses reflected differences in task-induced cognitive loading in both time and frequency domains (p < 0.05). Additionally, reduced pre-blink theta band desynchronization with increasing cognitive load was also observed (p < 0.05). Conclusion: This study confirms the ability of BRO responses to capture cognitive loading effects as well as preparatory pre-blink cognitive processes in anticipation of the upcoming blink during a complex multitasking situation. These successful results suggest that blink-related neural processing could be a potential avenue for cognitive state evaluation in operational settings—both specialized environments such as cockpits, space exploration, military units, etc. and everyday situations such as driving, athletics, human-machine interactions, etc.—where human cognition needs to be seamlessly monitored and optimized. Full article

Wireless-based sensing of physical environments has garnered tremendous attention recently, and its applications range from intruder detection to environmental occupancy monitoring. Wi-Fi is positioned as a particularly advantageous sensing medium, due to the ubiquity of Wi-Fi-enabled devices in a more connected world. Although Wi-Fi-based sensing using Channel State Information (CSI) has shown promise, existing sensing systems commonly configure dedicated transmitters to generate packets for sensing. These dedicated transmitters substantially increase the energy requirements of Wi-Fi sensing systems, and hence there is a need for understanding how ambient transmissions from nearby Wi-Fi devices can be leveraged instead. This paper explores the potential of Wi-Fi-based sensing using CSI derived from ambient transmissions of Wi-Fi devices. We demonstrate that CSI sensing accuracy is dependent on the underlying traffic type and the Wi-Fi transceiver architecture, and that control packets yield more robust CSI than payload packets. We also show that traffic containing upload data is more suitable for human occupancy counting, using the Probability Mass Function (PMF) of CSI. We further demonstrate that multiple spatially diverse streams of Wi-Fi CSI can be combined for sensing to an accuracy of $99\%$. The experimental study highlights the importance of training Wi-Fi sensing systems for multiple transmission sources to improve accuracy. This research has significant implications for the development of energy-efficient Wi-Fi sensing solutions for a range of applications. Full article

In recent years, the Internet of Vehicles (IoV) has garnered significant attention from researchers and automotive industry professionals due to its expanding range of applications and services aimed at enhancing road safety and driver/passenger comfort. However, the massive amount of data spread across this network makes securing it challenging. The IoV network generates, collects, and processes vast amounts of valuable and sensitive data that intruders can manipulate. An intrusion detection system (IDS) is the most typical method to protect such networks. An IDS monitors activity on the road to detect any sign of a security threat and generates an alert if a security anomaly is detected. Applying machine learning methods to large datasets helps detect anomalies, which can be utilized to discover potential intrusions. However, traditional centralized learning algorithms require gathering data from end devices and centralizing it for training on a single device. Vehicle makers and owners may not readily share the sensitive data necessary for training the models. Granting a single device access to enormous volumes of personal information raises significant privacy concerns, as any system-related problems could result in massive data leaks. To alleviate these problems, more secure options, such as Federated Learning (FL), must be explored. A decentralized machine learning technique, FL allows model training on client devices while maintaining user data privacy. Although FL for IDS has made significant progress, to our knowledge, there has been no comprehensive survey specifically dedicated to exploring the applications of FL for IDS in the IoV environment, similar to successful systems research in deep learning. To address this gap, we undertake a well-organized literature review on IDSs based on FL in an IoV environment. We introduce a general taxonomy to describe the FL systems to ensure a coherent structure and guide future research. Additionally, we identify the relevant state of the art in FL-based intrusion detection within the IoV domain, covering the years from FL’s inception in 2016 through 2023. Finally, we identify challenges and future research directions based on the existing literature. Full article

Accurate potential energy curves (PECs) are determined for the twenty-two electronic states of LiRb. In contrast to previous studies, the applied approach relies on the first principle calculations involving correlation among all electrons. The current methodology is founded on the multireference coupled cluster (CC) scheme constructed within the Fock space (FS) formalism, specifically for the (2,0) sector. The FS methodology is established within the framework of the intermediate Hamiltonian formalism and offers an intruder-free, efficient computational scheme. This method has a distinctive feature that, when applied to the doubly ionized system, provides the characteristics of the neutral case. This proves especially beneficial when investigating PECs in situations where a closed-shell molecule dissociates into open-shell fragments, yet its double positive ion forms closed-shell species. In every instance, we successfully computed continuous PECs spanning the entire range of interatomic distances, from the equilibrium to the dissociation limit. Moreover, the spectroscopic characteristic of various electronic states is presented, including relativistic effects. Relativistic corrections included at the third-order Douglas-Kroll level have a non-negligible effect on the accuracy of the determined spectroscopic constants. Full article

Quantum computation offers unique properties that cannot be paralleled by conventional computers. In particular, reading qubits may change their state and thus signal the presence of an intruder. This paper develops a proof-of-concept for a quantum honeypot that allows the detection of intruders on reading. The idea is to place quantum sentinels within all resources offered within the honeypot. Additional to classical honeypots, honeypots with quantum sentinels can trace the reading activity of the intruder within any resource. Sentinels can be set to be either visible and accessible to the intruder or hidden and unknown to intruders. Catching the intruder using quantum sentinels has a low theoretical probability per sentinel, but the probability can be increased arbitrarily higher by adding more sentinels. The main contributions of this paper are that the monitoring of the intruder can be carried out at the level of the information unit, such as the bit, and quantum monitoring activity is fully hidden from the intruder. Practical experiments, as performed in this research, show that the error rate of quantum computers has to be considerably reduced before implementations of this concept are feasible. Full article

This work addresses the problem of quantifying opacity for discrete event systems. We consider a passive intruder who knows the overall structure of a system but has limited observational capabilities and tries to infer the secret of this system based on the captured information flow. Researchers have developed various approaches to quantify opacity to compensate for the lack of precision of qualitative opacity in describing the degree of security of a system. Most existing works on quantifying opacity study specified probabilistic problems in the framework of probabilistic systems, where the behaviors or states of a system are classified as secret or non-secret. In this work, we quantify opacity by a state-worth function, which associates each state of a system with the worth it carries. To this end, we present a novel category of opacity, called worthy opacity, characterizing whether the worth of information exposed to the outside world during the system’s evolution is below a threshold. We first provide an online approach for verifying worthy opacity using the notion of a run matrix proposed in this research. Then, we investigate a class of systems satisfying the so-called 1-cycle returned property and present a worthy opacity verification algorithm for this class. Finally, an example in the context of smart buildings is provided. Full article

The I${}_3^{-}$ molecule is known to undergo substantial structural reorganization upon solvation by a protic solvent, e.g., water. However, the details of this process are still controversially discussed in the literature. In the present study, we combined experimental and theoretical efforts to disentangle this controversy. The valence (5p), N${}_{4,5}$ (4d), and M${}_{4,5}$ (3d) edge photoelectron spectra were measured in an aqueous solution and computed using high-level multi-reference methods. Our previous publication mainly focused on obtaining reliable experimental evidence, whereas in the present article, we focused primarily on theoretical aspects. The complex electronic structure of I${}_3^{-}$ requires the inclusion of both static and dynamic correlation, e.g., via the multi-configurational perturbation theory treatment. However, the resulting photoelectron spectra appear to be very sensitive to problems with variational stability and intruder states. We attempted to obtain artifact-free spectra, allowing for a more reliable interpretation of experiments. Finally, we concluded that the 3d Photoelectron Spectrum (PES) is particularly informative, evidencing an almost linear structure with a smaller degree of bond asymmetry than previously reported. Full article

Active reconnaissance is the primary source of information gathering about the infrastructure of a target network for intruders. Its main functions are host discovery and port scanning, the basic techniques of which are thoroughly analyzed in the present paper. The main contribution of the paper is the definition of a modeling approach regarding (a) all possible intruder actions, (b) full or partial knowledge of the intruder’s preferred methodology, and (c) the topology of the target network. The result of the modeling approach, which is based on state diagrams, is the extraction of a set of all probable paths that the intruder may follow. On top of this, a number of relevant metrics are calculated to enable the dynamic assessment of the risk to specific network assets according to the point on the paths at which the intruder is detected. The proposed methodology aims to provide a robust model that can enable the efficient and automated application of deception techniques to protect a given network. A series of experiments has also been performed to assess the required resources for the modeling approach when applied in real-world applications and provide the required results with bearable overhead to enable the online application of deception measures. Full article