Cyber Blackbox for collecting network evidence

In recent years, the hottest topics in the security field are related to the advanced and persistent attacks. As an approach to solve this problem, we propose a cyber blackbox which collects and preserves network traffic on a virtual volume based WORM device, called EvidenceLock to ensure data integrity for security and forensic analysis. As a strategy to retain traffic for long enough periods, we introduce a deduplication method. Also this paper includes a study on the network evidence which is collected and preserved for analyzing the cause of cyber incident. Then, a method is proposed to suggest a starting point for incident analysis to a forensic practitioner who has to investigate on the vast amount of network traffic collected using the cyber blackbox. Experimental results show this approach is effectively able to reduce the amount of data to search by dividing doubtful flows from normal traffic. Finally, we discuss the results with the forensically meaningful point of view and present further works

Cyber Black Box: Network intrusion forensics system for collecting and preserving evidence of attack

Once the system is compromised, the forensics and investigation are always executed after the attacks and the loss of some useful instant evidence. Since there is no log information necessary for analyzing an attack cause after the cyber incident occurs, it is difficult to analyze the cause of an intrusion even after an intrusion event is recognized. Moreover, in an advanced cyber incident such as advanced persistent threats, several months or more are expended in only analyzing a cause, and it is difficult to find the cause with conventional security equipment. In this paper, we introduce a network intrusion forensics system for collecting and preserving the evidence of an intrusion, it is called Cyber Black Box that is deployed in Local Area Network environment. It quickly analyzes a cause of an intrusion event when the intrusion event occurs, and provides a function of collecting evidence data of the intrusion event. The paper also describes the experimental results of the network throughput performance by deploying our proposed system in an experimental testbed environment

Efficacy and safety of acupuncture treatment for fatigue after COVID-19 infection: study protocol for a pilot randomized sham-controlled trial

BackgroundAs the coronavirus disease 2019 (COVID-19) pandemic has spread globally, its sequelae, called Long COVID, have persisted, troubling patients worldwide. Although fatigue is known to be the most frequent among Long COVID symptoms, its mechanism and treatment have not been clearly demonstrated. In 2022, we conducted a preliminary prospective case series and found that acupuncture and moxibustion were feasible interventions for fatigue. This study is a pilot patient-assessor-blinded randomized sham-controlled trial to evaluate the efficacy and safety of acupuncture treatment for patients with fatigue that has persisted for at least 4 weeks after recovery from COVID-19.MethodsThirty patients will be recruited and randomly assigned to either the acupuncture or sham acupuncture treatment groups. Treatment will be conducted thrice a week for both groups during 4 weeks. The primary outcome will be the efficacy and safety of acupuncture, including numeric rating scale (NRS), brief fatigue inventory (BFI), fatigue severity scale (FSS), and adverse event evaluation. Secondary outcomes will be evaluation of improvement in the comorbid symptoms of fatigue and feasibility variables. Outcome variables will be assessed before treatment, 4 weeks after treatment, and 8 weeks after treatment completion.DiscussionThe results of this study will be used to clarify the efficacy and safety of acupuncture treatment for persistent fatigue in patients with Long COVID. Additionally, the feasibility of the study design was validated to provide evidence for future full-scale randomized controlled trials.Clinical trial registration: identifier: KCT0008656 https://cris.nih.go.kr/cris/search/detailSearch.do?seq=24785&search_page=L

Coupling of Semiconductor Nanowires with Neurons and Their Interfacial Structure

We report on the compatibility of various nanowires with hippocampal neurons and the structural study of the neuron–nanowire interface. Si, Ge, SiGe, and GaN nanowires are compatible with hippocampal neurons due to their native oxide, but ZnO nanowires are toxic to neuron due to a release of Zn ion. The interfaces of fixed Si nanowire and hippocampal neuron, cross-sectional samples, were prepared by focused ion beam and observed by transmission electron microscopy. The results showed that the processes of neuron were adhered well on the nanowire without cleft

A Probabilistic Modeling Based on Monte Carlo Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis

As renewable energy resources such as wind and solar power are developing and the penetration of electric vehicles (EVs) is increasingly integrated into existing systems, uncertainty and variability in power systems have become important issues. The charging demands for EVs and wind power output are recognized as highly variable generation resources (VGRs) with uncertainty, which can cause unexpected disturbances such as short circuits. This can deteriorate the reliability of existing power systems. In response, research is required to identify the uncertainties presented by VGRs and is required to examine the ability of power system models to reflect those uncertainties. The deterministic method, which is the most basic method that is currently in use, does not reflect the uncertainty of system components. Therefore, this paper proposes a probabilistic method to assess the steady-state security of power systems, reflecting the uncertainty of VGRs using Monte Carlo simulation (MCS). In the proposed method, the empirical EVs charging demand and wind power output data are modeled as a probability distribution, and then MCS is performed, integrating the power system operation to represent the steady-state security as a probability index. To verify the method proposed in this paper, a security analysis was performed based on the systems in Jeju Island, South Korea, where the penetration of wind power and EVs is expanding rapidly

Position-aware Location Regression Network for Temporal Video Grounding

The key to successful grounding for video surveillance is to understand a semantic phrase corresponding to important actors and objects. Conventional methods ignore comprehensive contexts for the phrase or require heavy computation for multiple phrases. To understand comprehensive contexts with only one semantic phrase, we propose Position-aware Location Regression Network (PLRN) which exploits position-aware features of a query and a video. Specifically, PLRN first encodes both the video and query using positional information of words and video segments. Then, a semantic phrase feature is extracted from an encoded query with attention. The semantic phrase feature and encoded video are merged and made into a context-aware feature by reflecting local and global contexts. Finally, PLRN predicts start, end, center, and width values of a grounding boundary. Our experiments show that PLRN achieves competitive performance over existing methods with less computation time and memory.Y

Proteomic change by Korean Red Ginseng in the substantia nigra of a Parkinson's disease mouse model

Background: Recent studies have shown that Korean Red Ginseng (KRG) successfully protects against dopaminergic neuronal death in the nigrostriatal pathway of a Parkinson's disease (PD) mouse model induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) administration; however, the mechanism has yet to be identified. Therefore, in this study we used two-dimensional electrophoresis to investigate the effects of KRG on the changes in protein expression in the substantia nigra (SN) of MPTP-treated mice. Methods: Male C57BL/6 mice (9 wk old) were intraperitoneally administered MPTP (20 mg/kg) four times at 2-h intervals, after which KRG (100 mg/kg) was orally administered once a day for 5 d. Two hours after the fifth KRG administration, a pole test was conducted to evaluate motor function, after which the brains were immediately collected. Survival of dopaminergic neurons was measured by immunohistochemistry, and protein expression was measured by two-dimensional electrophoresis and Western blotting. Results: KRG alleviated MPTP-induced behavioral dysfunction and neuronal toxicity in the SN. Additionally, the expression of eight proteins related to neuronal formation and energy metabolism for survival were shown to have changed significantly in response to MPTP treatment or KRG administration. KRG alleviated the downregulated protein expression following MPTP administration, indicating that it may enhance neuronal development and survival in the SN of MPTP-treated mice. Conclusion: These findings indicate that KRG may have therapeutic potential for the treatment of patients with PD. Keywords: Korea Red Ginseng, Parkinson's disease, substantia nigra, two-dimensional electrophoresis, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridin

De Novo Assembly and Species-Specific Marker Development as a Useful Tool for the Identification of Scutellaria L. Species

Scutellaria L. (family Lamiaceae) includes approximately 470 species found in most parts of the world and is commonly known as skullcaps. Scutellaria L. is a medicinal herb used as a folk remedy in Korea and East Asia, but it is difficult to identify and classify various subspecies by morphological methods. Since Scutellaria L. has not been studied genetically, to expand the knowledge of species in the genus Scutellaria L., de novo whole-genome assembly was performed in Scutellaria indica var. tsusimensis (H. Hara) Ohwi using the Illumina sequencing platform. We aimed to develop a molecular method that could be used to classify S.indica var. tsusimensis (H. Hara) Ohwi, S. indica L. and three other Scutellaria L. species. The assembly results for S.indica var. tsusimensis (H. Hara) Ohwi revealed a genome size of 318,741,328 bp and a scaffold N50 of 78,430. The assembly contained 92.08% of the conserved BUSCO core gene set and was estimated to cover 94.65% of the genome. The obtained genes were compared with previously registered Scutellaria nucleotide sequences and similar regions using the NCBI BLAST service, and a total of 279 similar nucleotide sequences were detected. By selecting the 279 similar nucleotide sequences and nine chloroplast DNA barcode genes, primers were prepared so that the size of the PCR product was 100 to 1000 bp. As a result, a species-specific primer set capable of distinguishing five species of Scutellaria L. was developed