Search Results (1,017)

Existing methods for identifying Tactics, Techniques, and Procedures (TTPs) from complex cyber-attack descriptions face three core challenges: (1) severe semantic asymmetry between unstructured attack narratives and standardized TTP definitions; (2) continuously distributed semantic relations that cannot be fully captured by hard-label supervision; and (3) an open, long-tailed TTP taxonomy that impairs model generalization. To address these limitations, we introduce DTGBI-TM, a lightweight dual-tower semantic matching framework that integrates soft-label supervision, hierarchical hard-negative sampling, and gated binary interaction modeling. The model separately encodes attack descriptions and TTP definitions and employs a gated interaction module to adaptively fuse shared and divergent semantics, enabling fine-grained asymmetric alignment. A confidence-guided soft–hard collaborative supervision mechanism unifies weighted classification, semantic regression, and contrastive consistency into a multi-objective loss, dynamically rebalancing gradients to mitigate long-tail effects. Leveraging ATT & CK hierarchical priors, the model further performs in-tactic and cross-tactic hard-negative sampling to enhance semantic discrimination. Experiments on a real-world corpus demonstrate that DTGBI-TM achieves 98.53% F1 in semantic modeling and 79.77% Top-1 accuracy in open-set TTP prediction, while maintaining high inference efficiency and scalability in deployment. Full article

Historical inference attacks pose a critical privacy threat in mobile edge computing (MEC), where adversaries exploit long-term task and location patterns to infer users’ sensitive information. To address this challenge, we propose a privacy-preserving task scheduling framework that adaptively balances privacy protection and system performance under dynamic vehicular environments. First, we introduce a dynamic privacy-aware adaptation mechanism that adjusts privacy levels in real time according to vehicle mobility and network dynamics. Second, we design a dual-algorithm framework composed of two complementary solutions: a Markov Approximation-Based Online Algorithm (MAOA) that achieves near-optimal scheduling with provable convergence, and a Privacy-Aware Deep Q-Network (PAT-DQN) algorithm that leverages deep reinforcement learning to enhance adaptability and long-term decision-making. Extensive simulations demonstrate that our proposed methods effectively mitigate privacy leakage while maintaining high task completion rates and low energy consumption. In particular, PAT-DQN achieves up to 14.2% lower privacy loss and 19% fewer handovers than MAOA in high-mobility scenarios, showing superior adaptability and convergence performance. Full article

One of the main vulnerabilities in robotic systems lies in the communication buses that enable low-level controllers to interact with the actuators responsible for the robot’s movements. In this context, hardware attacks represent a significant threat; however, the hardware version of the man-in-the-middle attack, implemented by Trojan hardware, has not yet been extensively studied. This article examines the impact of such threats on robotic control systems, focusing on vulnerabilities in an asynchronous communication bus used to transmit commands to a digital servomotor. To explore this, Trojan hardware was implemented on an FPGA device (XC7A100T, AMD: Santa Clara, CA, USA). Furthermore, the article proposes and implements detection methods to identify this type of attack, integrating them into an FPGA device as part of the actuator. The method is based on measuring the answer time detecting the presence of a strange module due to an increase in this time considering an AX-12 servomotor (Robotis: Seoul, Republic of Korea), with a Dynamixel protocol. This approach has been validated through a series of experiments involving a large number of transmitted messages, resulting in a high rate of true positives and a low rate of false negatives. The main conclusion is that response time can be used to detect foreign modules in the system, even if the module is kept waiting to attack, as long as the condition that the servomotors have a low variation in their latency is met. Full article

Faces are central to human interaction, serving as primary sources of identity, emotional cues, and social judgments. Facial attractiveness is strongly linked to perceptions of trustworthiness and moral goodness, leading to preferential treatment across education, employment, and legal contexts. Deviations from facial norms—such as asymmetry or visible differences—are, by contrast, often associated with negative traits, social avoidance, and dehumanisation. Across cultures and centuries, deliberate facial disfiguration has been used as a form of punishment for perceived moral or legal transgressions. Evidence from ancient Egypt, Mediaeval Europe, and early modern legislation, as well as modern acid attacks, indicates that intentional facial disfiguration has long served as a means of ongoing punishment through humiliation and identity disruption. Motivations for targeting the face may be rooted in its central role in identity, beauty, symmetry, and symbolic purity. Despite contemporary legal efforts to curb acid attacks and related violence, legislation specifically addressing intentional facial disfiguration remains limited. Modern psychological research confirms that acquiring a facial difference can severely impact quality of life, social functioning, and identity. This paper synthesises historical, cultural, and psychological perspectives on punitive facial disfiguration, highlighting its enduring role as a mechanism of social control. Future research should examine perpetrators’ decision-making, possible differences between different types of facial disfiguration, and the perceptual and emotional consequences of different facial injuries to inform prevention strategies and improve support for victims. Full article

The Social Internet of Things (SIoT) combines social networks and the Internet of Things, enabling closer interaction between devices, users, and services. However, this interaction brings risks of trust attacks. These trust attacks not only affect the stability of SIoT systems but also threaten personal privacy and data security. This paper provides a decade-long review of SIoT trust attack research. First, it outlines the SIoT architecture, social relationship types, concept of trust, and trust management processes. It maps seven attacks—bad mouthing attack (BMA), ballot stuffing attack (BSA), self-promoting attack (SPA), discriminatory attack (DA), whitewashing attack (WWA), on-off attack (OOA), and opportunistic service attack (OSA)—clarifying their mechanisms and traits. Next, we synthesize the literature on SIoT trust models, enumerate which attack types they address, and classify defense strategies. It then conducts simulation-based comparative experiments on trust attacks to reveal their impact on node trust and transaction processing, compares attack capabilities along disruption speed, attack strength, and stealthiness, and summarizes attack surfaces with corresponding defense recommendations to better guide the design of SIoT trust management schemes. Finally, we identify open challenges and future research directions, to support the development of new trust management models better equipped to address evolving trust attacks. Full article

The Twin Hybrid Autonomous Underwater Vehicle (THAUV) is an underwater monitoring system consisting of a twin buoyant body and a fixed wing mounted between them. It is equipped with two propeller thrusters and a pair of elevators at the aft end. As a new type of underwater vehicle, it combines the long endurance of an underwater glider (UG), the high-speed maneuverability of an autonomous underwater vehicle (AUV), and the ability to carry larger payloads. In this paper, the motion equations of the THAUV are established, and its simulation model is developed using SIMULINK. Computational fluid dynamics (CFD) is further employed to identify hydrodynamic parameters under different elevator size conditions. A case study is conducted to analyze the effects of three different widths of elevators on glide performance, including gliding speed, pitching angle, and gliding trajectory. CFD results show that when the elevator deflection angle is zero, the hydrodynamic forces acting on the THAUV increase as the elevator width increases under identical angle of attack and velocity conditions. Under CFD conditions with fixed angle of attack and flow velocity, the sensitivity of the hydrodynamic characteristics to elevator deflection became significantly more pronounced. Increasing the elevator deflection angle led to substantial growth in the generated hydrodynamic forces. Motion simulations further show that increasing the elevator deflection angle enhances the THAUV’s gliding performance. Comparative results also reveal that glide performance improves with larger elevator width. Full article

Intrusion detection systems (IDSs) must operate under severe class imbalance, evolving attack behavior, and the need for calibrated decisions that integrate smoothly with security operations. We propose a human-in-the-loop IDS that combines a convolutional neural network and a long short-term memory network (CNN–LSTM) classifier with a variational autoencoder (VAE)-seeded conditional Wasserstein generative adversarial network with gradient penalty (cWGAN-GP) augmentation and entropy-based abstention. Minority classes are reinforced offline via conditional generative adversarial (GAN) sampling, whereas high-entropy predictions are escalated for analysts and are incorporated into a curated retraining set. On CIC-IDS2017, the resulting framework delivered well-calibrated binary performance (ACC = 98.0%, DR = 96.6%, precision = 92.1%, F1 = 94.3%; baseline ECE ≈ 0.04, Brier ≈ 0.11) and substantially improved minority recall (e.g., Infiltration from 0% to >80%, Web Attack–XSS +25 pp, and DoS Slowhttptest +15 pp, for an overall +11 pp macro-recall gain). The deployed model remained lightweight (~42 MB, <10 ms per batch; ≈32 k flows/s on RTX-3050 Ti), and only approximately 1% of the flows were routed for human review. Extensive evaluation, including ROC/PR sweeps, reliability diagrams, cross-domain tests on CIC-IoT2023, and FGSM/PGD adversarial stress, highlights both the strengths and remaining limitations, notably residual errors on rare web attacks and limited IoT transfer. Overall, the framework provides a practical, calibrated, and extensible machine learning (ML) tier for modern IDS deployment and motivates future research on domain alignment and adversarial defense. Full article

Background: Circulating microRNAs (miRNAs) have emerged as potential biomarkers of platelet reactivity and thrombotic risk. Among them, miR-223-3p regulates P2Y12 receptor expression and may influence response to antiplatelet therapy. This study aimed to evaluate the prognostic value of selected circulating miRNAs in post-stroke patients receiving antiplatelet treatment. Methods: Sixty ischemic stroke survivors were prospectively enrolled and followed for 18 months for recurrent vascular events (stroke, transient ischemic attack, or myocardial infarction). Plasma levels of miR-126-3p, miR-223-3p, miR-24-3p, and miR-199a-5p were quantified using reverse transcription real-time PCR. Clinical data, antiplatelet regimen, statin use, and Essen Stroke Risk Scores (ESRS) were recorded. Logistic regression was applied to identify independent predictors of thrombotic events. Results: Expression of all examined miRNAs differed significantly across treatment groups. The dual antiplatelet therapy (DAPT) group showed the highest levels of miR-126-3p and miR-199a-5p (p < 0.01). Within the statin-naïve DAPT subgroup, lower miR-199a-5p levels (p < 0.001) were observed among patients who experienced ischemic events (n = 7/60; 12%; stroke = 4, TIA = 2, ACS = 1) during 18 months of follow-up. In multivariate analysis, reduced miR-223-3p remained the only independent predictor of recurrent thrombotic events (OR 1.18, 95% CI 1.01–1.37, p = 0.036), independent of ESRS and platelet reactivity. Elevated miR-126-3p and miR-199a-5p were associated with favorable treatment response, particularly among statin users. Conclusions: This study identifies low circulating miR-223-3p as an independent biomarker of thrombotic risk in post-stroke patients, potentially reflecting enhanced platelet activation via P2Y12 signaling. In contrast, higher miR-126-3p and miR-199a-5p levels may indicate more effective antiplatelet response. These findings support the potential utility of miRNA profiling for individualized antiplatelet therapy and long-term risk stratification after ischemic stroke. Full article

In an increasingly interconnected world, cybersecurity professionals play a pivotal role in safeguarding organizations from cyber threats. To secure their cyberspace, organizations are forced to adopt a cybersecurity framework such as the NIST National Initiative for Cybersecurity Education Workforce Framework for Cybersecurity (NICE Framework). Although these frameworks are a good starting point for businesses and offer critical information to identify, prevent, and respond to cyber incidents, they can be difficult to navigate and implement, particularly for small-medium businesses (SMBs). To help overcome this issue, this paper identifies the most frequent attack vectors to SMBs (Objective 1) and proposes a practical model of both technical and non-technical tasks, knowledge, skills, abilities (TKSA) from the NICE Framework for those attacks (Objective 2). This research develops a scenario-based curriculum. By immersing learners in realistic cyber threat scenarios, their practical understanding and preparedness in responding to cybersecurity incidents is enhanced (Objective 3). Finally, this work integrates practical experience and real-life skill development into the curriculum (Objective 4). SMBs can use the model as a guide to evaluate, equip their existing workforce, or assist in hiring new employees. In addition, educational institutions can use the model to develop scenario-based learning modules to adequately equip the emerging cybersecurity workforce for SMBs. Trainees will have the opportunity to practice both technical and legal issues in a simulated environment, thereby strengthening their ability to identify, mitigate, and respond to cyber threats effectively. We piloted these learning modules as a semester-long course titled “Hack Lab” for both Computer Science (CS) and Law students at CSU during Spring 2024 and Spring 2025. According to the self-assessment survey by the end of the semester, students demonstrated substantial gains in confidence across four key competencies (identifying vulnerabilities and using tools, applying cybersecurity laws, recognizing steps in incident response, and explaining organizational response preparation) with an average improvement of +2.8 on a 1–5 scale. Separately, overall course evaluations averaged 4.4 for CS students and 4.0 for Law students, respectively, on a 1–5 scale (college average is 4.21 and 4.19, respectively). Law students reported that hands-on labs were difficult, although they were the most impactful experience. They demonstrated a notable improvement in identifying vulnerabilities and understanding response processes. Full article

This paper addresses the stability analysis and control design for discrete-time hidden semi-Markov jump systems under the compounded challenges of denial-of-service (DoS) attacks and incomplete emission probabilities. Such conditions are prevalent in modern networked control systems, yet they pose significant hurdles for robust controller design. Existing control methods, typically based on integer-order dynamics, are inherently memoryless, struggling to effectively mitigate the long-term impact of mode observation uncertainties and intermittent cyberattacks. To overcome these challenges, we propose, for the first time, a fractional-order sliding mode control (FOSMC) strategy tailored for this class of systems. The core of our method is a novel sliding surface that leverages a discrete fractional-order sum to embed the system’s history—including observed modes and elapsed sojourn times—into the control logic. This memory-based approach enhances robustness against both mode observation uncertainties and adversarial packet losses. A corresponding FOSMC law is synthesized to ensure finite-time reachability of this surface. We derive sufficient conditions, formulated as linear matrix inequalities, to guarantee the mean-square stability of the resulting sliding mode dynamics.A numerical simulation validates the effectiveness of the proposed control scheme, demonstrating a convergence speed improvement ranging from 40% (under moderate attacks) to nearly 50% (under severe attacks) over its integer-order counterpart, conclusively validating its performance enhancement capability under compound uncertainties. Full article

Post-5G and 6G telecommunication infrastructures face critical information security challenges due to increasing network complexity and sophisticated cyberattacks. Traditional intrusion detection systems based on statistical traffic analysis struggle to identify advanced threats that exploit semantic-level vulnerabilities in modern communication protocols. This paper proposes a Transformer-based intrusion detection system specifically designed for post-5G and 6G networks. Our approach integrates three key innovations: First, a comprehensive feature extraction method capturing both semantic content characteristics and communication behavior patterns. Second, a dynamic semantic embedding mechanism that adaptively adjusts positional encoding based on semantic context changes. Third, a Transformer-based classifier with multi-head attention mechanisms to model long-range dependencies in attack sequences. Extensive experiments on CICIDS2017 and UNSW-NB15 datasets demonstrate superior performance compared to LSTM, GRU, and CNN baselines across multiple evaluation metrics. Robustness testing and cross-dataset validation confirm strong generalization capability, making the system suitable for deployment in heterogeneous post-5G and 6G telecommunication environments. Full article

Invasive seed predators can severely affect the reproduction of long-lived trees, especially when host range expansion occurs. The beetle Specularius impressithorax (Chrysomelidae: Bruchinae), native to Africa, has become established in Hawaiʻi where it attacks the endemic coral tree (Erythrina sandwicensis; Wiliwili). Here, we report the infestation of an African coral tree (E. livingstoniana) by this beetle and assess its performance and oviposition patterns on native and non-native hosts. Field surveys showed that eggs were aggregated on both hosts but more abundant on E. sandwicensis than on E. livingstoniana. Laboratory assays revealed no difference in larva-to-adult survival between the two hosts, although adults emerging from E. sandwicensis were larger. Choice tests indicated no oviposition preference between the two Erythrina species, despite the larger seed size of E. sandwicensis. To explore potential host range expansion, trials were run on economic legumes with varying phylogenetic distance from Erythrina, which showed oviposition on peanut (Arachis hypogaea) with low but successful survival (10.3%), while no development occurred on broad bean or pigeon pea. More E. sandwicensis seeds germinated when infested by a single early-stage larva (70% germination) than when uninfested (20%), suggesting that minimal seed predation may facilitate germination because previously reported greater damage induced by infestation through adulthood reduces germination. Our findings highlight the ecological flexibility of an invasive bruchine, its potential to exploit other Faboideae plants, and the dual role of seed predators as both threats and facilitators of seed germination. These results have implications for conservation of endemic coral trees and for understanding invasion dynamics of shared seed predators. Additionally, we examined non-botanical substrate filled with seed powder for oviposition and compiled global host records of S. impressithorax to contextualize its host range expansion. Full article

Background: Moyamoya syndrome is a moyamoya-like cerebrovascular condition associated with an identifiable underlying condition. Although head trauma has historically been considered a possible contributing factor, it is currently excluded from the Japanese diagnostic criteria. We report a rare case of progressive unilateral moyamoya-like vasculopathy that developed on the ipsilateral chronic subdural hematoma (CSDH) following head trauma, with a decade-long imaging follow-up. Anterior circulation basi-parallel anatomical scanning (BPAS) provided unique insights into the progressive vessel narrowing beyond the vascular lumen, suggesting its potential utility in evaluating such rare vasculopathies. Case Presentation: A 40-year-old man developed a left-sided CSDH after head trauma and underwent burr hole drainage. Although his symptoms resolved, serial magnetic resonance angiography (MRA) over the subsequent 10 years revealed progressive stenosis of the left middle cerebral artery (MCA), ultimately culminating in an occlusion-like appearance. BPAS revealed moyamoya-like collateral vessels in the same hemisphere, a significant reduction in the outer diameter of the left MCA, supporting the presence of structural arterial wall changes that were not apparent on conventional MRA. Single-photon emission computed tomography revealed mildly reduced cerebral blood flow on the affected side, with a difference of less than 5% compared to non-affected side. He remained neurologically non-symptomatic, with no history of transient ischemic attacks or overt ischemic stroke. Conclusions: This case highlights a rare clinical course of progressive ipsilateral moyamoya-like vascular changes following head trauma and burr-hole drainage for CSDH, potentially indicating an association between head trauma, CSDH, and subsequent moyamoya-like collateral vessel development, warranting further investigation. The use of the anterior circulation BPAS contributed to the detection of structural arterial changes that were not apparent on conventional MRA, suggesting its potential utility in evaluating such vascular abnormalities. Full article

Among animal diseases, those characterized with transboundary potential enhance their interconnection to the One Health principle. Zoonoses with a higher capacity to spread compared to other diseases with a lower level of transmissibility multiply their potential impact on human populations. The routes and speed of transmission and virulence may also increase the impact on animal health in the zootechnic sector and in wild animals. This risk, especially in endangered species, has the potential to alter biodiversity, negatively affecting the environment. The characteristics of these pathogens represent a global health danger that requires knowledge and the capacity for prevention and control, considering the possibility of natural outbreak occurrence together with the deliberate use of such pathogens as biological weapons for terrorist attacks. Animal pathogens, particularly those with zoonotic potential, have long been considered for use in bioterrorism. International conventions prohibit the use of microbiological and toxin weapons. Furthermore, recent European legislation has also addressed the potential misuse of animal pathogens in bioterrorism. In this context, the Parliamentary Assembly of the Mediterranean (PAM) and its Center for Global Studies are committed to preventing global health threats by promoting transboundary cooperation, especially through a One Health approach that links human, animal, and environmental health. In the face of future emergencies, PAM is also committed to promoting greater information sharing for harmonized legislative frameworks and equitable access to resources, to strengthen the resilience of global health systems, especially in developing countries. In both the past and recent history, various outbreaks have been attributed to proven or alleged bioterrorist attacks targeting human or animal populations. This study discusses the general characteristics of several relevant transboundary diseases. Paying high attention to One Health is of utmost importance. However, for a full understanding, it is necessary to consider all related aspects and implications. Full article

In recent years, Norwegian cultural production has increasingly foregrounded the experiences of sailors serving aboard merchant vessels allied with the British during the Second World War. These men endured not only physical injuries from submarine and aerial attacks, but also profound psychic trauma, often manifesting in post-war alcoholism and depression. However, the war at sea also left indelible marks on women’s bodies. This article examines Vigdis Stokkelien’s trilogy on Gro—Lille-Gibraltar (Little Gibraltar, 1972), Båten under solseilet (The boat under the sun sail, 1982), and Stjerneleden (The star joint, 1984)—to explore how emotions as fear, shame and pain circulate between different individuals and groups during the war and in war memories. Drawing on affect theory, this reading of Stokkelien’s novels demonstrates how what happened at sea marked Norwegian bodies and national identity for a long time after the war. Full article