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Unveiling cyber threat actors: a hybrid deep learning approach for behavior-based attribution
No full textIn this article, we leverage natural language processing and machine learning algorithms to profile threat actors based on their behavioral signatures to establish identification for soft attribution. Our unique dataset comprises various actors and the commands they have executed, with a significant proportion using the Cobalt Strike framework in August 2020-October 2022. We implemented a hybrid deep learning structure combining transformers and convolutional neural networks to benefit global and local contextual information within the sequence of commands, which provides a detailed view of the behavioral patterns of threat actors. We evaluated our hybrid architecture against pre-trained transformer-based models such as BERT, RoBERTa, SecureBERT, and DarkBERT with our high-count, medium-count, and low-count datasets. Hybrid architecture has achieved F1-score of 95.11% and an accuracy score of 95.13% on the high-count dataset, F1-score of 93.60% and accuracy score of 93.77% on the medium-count dataset, and F1-score of 88.95% and accuracy score of 89.25% on the low-count dataset. Our approach has the potential to substantially reduce the workload of incident response experts who are processing the collected cybersecurity data to identify patterns
Tool path generation for precision roughing of BLISKS via abrasive waterjet machining
No full textManufacturing process chains of bladed disks are energy intense. Heat resistant properties of Inconel alloys make them very challenging to cut by conventional milling at roughing conditions, where excessive cutting forces and vibration arise. Abrasive waterjet machining (AWJM) offers several benefits in cutting of such materials. In the literature, 5-axis AWJM of blisks is not well studied for machining strategy, parameter selection and tool path generation. This paper presents a unified approach for development of 5-axis AWJM roughing of blisks. The proposed approach is demonstrated on a representative part made of Inconel 718
An efficient matheuristic integration with benders decomposition for unmanned aerial vehicle routing problem in forest fire surveillance
No full textWildfires annually cause extensive and immeasurable harm to the environment, incurring significant costs for containment efforts. Early detection plays a crucial role in preventing the escalation of wildfires, requiring accurate and frequent updates on images and information. Despite advancements in detection methods utilizing image processing and satellite monitoring, the demand for improved precision and frequency persists. Presently, satellite images can detect fires as small as 0.1 ha with an accuracy of 1 km. While helicopters offer detailed information, their use is both hazardous and expensive. There is growing interest in Unmanned Aerial Vehicles (UAVs) for wildfire detection due to their ability to quickly cover potential fire areas using high-definition and thermal infrared cameras, particularly in remote and hazardous terrains. This study addresses the routing and scheduling of UAVs for forest fire surveillance. A mixed-integer linear programming (MILP) model is formulated, followed by the introduction of matheuristic approaches to tackle and solve the problem, drawing inspiration from variable neighborhood search. Matheuristics, which integrate mathematical programming techniques and heuristics, provide efficient optimization methods. Additionally, we incorporate Benders Decomposition to enhance the optimization process by decomposing the problem into a master problem and a subproblem, allowing for more effective exploration of feasible solutions. To evaluate the effectiveness of our proposed solution approach, computational experiments are conducted using a set of instances generated from the Covering Vehicle Routing Problem (CoVRP) and Electric Vehicle Routing Problem (EVRP) datasets. The results indicate that our proposed matheuristics approach, augmented by Benders Decomposition, is capable of producing high-quality solutions. Furthermore, a case study is presented focusing on the Belgrade Forest, one of the largest forests in Istanbul, Turkey, to underscore the benefits of utilizing UAVs in forest fire surveillance
Zinc oxide-decorated MIL-53(Al)-derived porous carbon for supercapacitor devices
No full textIn this study, we present a facile and direct approach for the synthesis of ordered mesoporous metal-organic framework (MOF)-derived carbon materials, uniformly adorned with zinc oxide (ZnO), to serve as electrode materials for supercapacitor applications. The method involves the impregnation of zinc nitrate into both the as-synthesized (as) and activated low-temperature (lt) forms of the MIL-53(Al) metal-organic framework, which are subsequently employed as precursors to fabricate ZnO-decorated carbon structures (ZnO@C) through simultaneous decomposition under thermal treatment in an Ar atmosphere. The resultant ZnO@C(as) and ZnO@C(lt) materials exhibit a channel-like carbon morphology with uniformly distributed ZnO and residual alumina nanoparticles and a bimodal porous structure with pores approximately 8.5 and 15 nm in size. Additionally, a greater concentration of carbon-related defect centers was identified in ZnO@C(as) relative to ZnO@C(lt), as evidenced by Raman, and electron paramagnetic resonance spectroscopy. When utilized as electrode materials in both symmetric and asymmetric supercapacitor devices, the ZnO@C materials demonstrated exceptional performance, achieving energy and power densities of up to 30.5 W h kg−1 and 388 kW kg−1, respectively, and exhibiting coulombic efficiencies exceeding 95% in all instances
Mobilizing against the disadvantaged: unraveling the dynamics of anti-minority collective action
No full textExtant research on collective action has investigated how both advantaged and disadvantaged group members mobilise to support the rights of minority status groups. More recent research has begun to examine what might lead advantaged group members to engage in actions that aim to harm disadvantaged groups and protect and/or promote their advantaged group’s status and interests. This review aims to define “anti-minority collective action” by critically discussing existing conceptualisations in the literature and to investigate its social psychological drivers. In light of the evidence, we argue that anti-minority collective action may be largely motivated by social psychological processes similar to those identified in broader collective action research (such as pro-minority collective action), yet existing collective action models may not fully capture what leads advantaged group members to act collectively against the disadvantaged. We further provide future directions that address critical gaps in this emerging literature and discuss the potential implications of these actions within broader social change dynamics
Sürdürülebilir kentler için yenilikçi yol kenarı yönetimi
No full textKentsel alanlar, küresel karbondioksit emisyonlarının %70’inden fazlasından sorumludur (Lwasa ve diğerleri, 2022). Bu emisyonların büyük bir kısmı ulaşım ve binalar gibi insan refahını doğrudan etkileyen faaliyetlerden kaynaklanmaktadır. Yeni teknolojik ilerlemeler olmadığı sürece, uzun vadede, kent hayatının enerji talebiyle doğrudan bağlantılı olan bu emisyonları, yaşam kalitesini etkilemeden ciddi ölçüde azaltmak pek gerçekçi görünmemektedir. Ancak, kısa vadede, gereksiz enerji kullanımına yol açan dışsallıkları ele alarak kentlerin verimliliğini arttırıp emisyonları azaltmaya katkı verebiliriz. Bu konuda umut vadeden ancak yeterince araştırılmamış bir alan ise yol kenarı yönetimidir
Highly self-adhesive and biodegradable silk bioelectronics for all-in-one imperceptible long-term electrophysiological biosignals monitoring
No full textSkin-like bioelectronics offer a transformative technological frontier, catering to continuous and real-time yet highly imperceptible and socially discreet digital healthcare. The key technological breakthrough enabling these innovations stems from advancements in novel material synthesis, with unparalleled possibilities such as conformability, miniature footprint, and elasticity. However, existing solutions still lack desirable properties like self-adhesivity, breathability, biodegradability, transparency, and fail to offer a streamlined and scalable fabrication process. By addressing these challenges, inkjet-patterned protein-based skin-like silk bioelectronics (Silk-BioE) are presented, that integrate all the desirable material features that have been individually present in existing devices but never combined into a single embodiment. The all-in-one solution possesses excellent self-adhesiveness (300 N m−1) without synthetic adhesives, high breathability (1263 g h−1 m−2) as well as swift biodegradability in soil within a mere 2 days. In addition, with an elastic modulus of ≈5 kPa and a stretchability surpassing 600%, the soft electronics seamlessly replicate the mechanics of epidermis and form a conformal skin/electrode interface even on hairy regions of the body under severe perspiration. Therefore, coupled with a flexible readout circuitry, Silk-BioE can non-invasively monitor biosignals (i.e., ECG, EEG, EOG) in real-time for up to 12 h with benchmarking results against Ag/AgCl electrodes
Enhanced supercapacitor performance with cerium-doped polypyrrole nanofibers
No full textThe current study assessed the potential use of cerium (Ce)-incorporated polypyrrole (PPy) nanofibers (PPy:Ce) as electrode materials for supercapacitors. Cerium incorporation improved the electrochemical performance of PPy, especially by overcoming limitations in cycling stability and energy storage capacity. The PPy and PPy:Ce nanofibers, synthesized using chemical oxidative polymerization, have been carefully examined using various characterization techniques. Electron Paramagnetic Resonance (EPR) investigations showed that cerium doping increased the density of paramagnetic centers in the PPy structure, improving electrical conductivity and redox activity. Cyclic voltammetry (CV) tests demonstrated that PPy:Ce nanofibers displayed superior electrochemical performance, achieving a specific capacitance of 203 F g−1 and an energy density of 21.3 W h kg−1. Electron microscopy investigations showed that cerium doping increased the diameter of the nanofibers, resulting in a more uniform shape and improved surface roughness. Brunauer-Emmett-Teller (BET) analysis revealed that while cerium doping reduces surface area, it optimizes the pore structure, enhancing ion transport and electrolyte access. This optimization allows for larger pore sizes that facilitate easier ion movement, compensating for the decreased surface area. Structural and electrochemical improvements have been achieved through the homogeneous incorporation of cerium doping into the PPy framework. Cerium doping boosts the cycling stability of PPy, providing an important advantage for long-term energy storage applications. This work presents an alternate method for producing supercapacitor electrodes that demonstrate outstanding efficacy in practical applications utilizing a two-electrode setup. This study significantly contributes to the literature by demonstrating the enhanced performance values achieved by directly incorporating cerium ions into the PPy matrix
Organic waste-derived activated carbons for supercapacitor applications: advances in synthesis strategies and electrochemical performance enhancement
No full textThis review thoroughly investigates recent advancements in utilizing organic waste, such as carbon precursors, activation methodologies, and supercapacitor applications. The growing problem of environmental pollution and the demand for sustainable energy storage systems motivate researchers to create novel and ecofriendly materials. Activated carbons (AC) derived from organic waste address waste management issues while enhancing the development of high-performance energy storage devices. The study systematically examines various types of organic waste, carbonization, and activation mechanisms while providing a comparative examination of chemical and physical activation processes. A particular focus is placed on the mechanisms of action and process optimization of activation agents like KOH, NaOH, K2CO3, ZnCl2, and H3PO4. The utilization of AC in environmental applications (water treatment, air purification, CO2 capture) and energy storage systems (supercapacitors) is assessed based on the latest research. The enhancement of production processes, emerging trends, and experienced problems is examined comprehensively. This review aims to serve as a thorough resource for researchers engaged in manufacturing and applying AC derived from organic waste while illuminating prospective research possibilities
A moral hazard detection framework: reinforcing trust in ORAN
No full textWith the emergence of the Open Radio Access Network (ORAN) concept and related standardization efforts, future radio access networks are anticipated to feature elements from diverse vendors. Although the ORAN elements can authenticate as legitimate, the system may fail to meet service requirements if some network components do not adhere to their respective agreements, i.e., moral hazard. This issue raises concerns about the network's end-to-end performance, complicating fault attribution and conflict resolution. Therefore, there is a need for an automated zero-trust framework capable of continuously detecting instances of moral hazard. The complexity is exacerbated by the dynamic nature of network elements or artificial intelligence (AI) model performance, which may degrade over time intentionally (e.g., malicious tampering) or unintentionally (e.g., model obsolescence or device performance decline), limiting the effectiveness of offline testing. To address this, we develop a mechanism based on subjective logic principles, incorporating a logic-based argumentation framework that explicitly accommodates argument schemes, argument accrual, and burden of proof. Building upon this framework, we apply contract theory to incentivize compliant devices to participate truthfully in the ORAN ecosystem, thereby enhancing system performance. The simulation results show improved system efficiency and reduced operational costs