Vulnerable Point Research Articles

Enhancing IoT Device Security through Blockchain Technology: A Decentralized Approach

The rapidly growing Internet of Things (IoT) devices pose significant security challenges due to their decentralized nature, limited computing power and reliance on centralized security models Traditional IoT security systems often face issues such as single point of failure, limited scalability and vulnerability to distributed denial of service (DDoS) attacks They also require la-doable security solutions. Blockchain technology has emerged as a potential solution due to its decentralized, immutable and transparent nature, providing advanced security for IoT environments. This study proposes a blockchain-based security strategy aimed at mitigating security risks in IoT networks. The system uses smart contracts to perform basic functions such as device authentication, data integrity verification, and access control. The main goal of the research is to develop IoT security solutions that increase device reliability speeds, reduce power consumption, reduce connection latency, and maximize network availability. The results of the survey show significant improvements over existing IoT security measures. The blockchain-based system achieves device authentication time of 0.1 to 2 seconds, 95% detection rate for unauthorized access, and supports 1000 devices, double the capacity of traditional models Also, the system reduces energy consumption 0.5–2 joules per transaction and transaction latency to 1–5 seconds , making it suitable for real-time IoT applications.

Response time optimization for vulnerability management system by combining the benchmarking and scenario planning models

<span>The growth of information and communication technology has made the internet network have many users. On the other side, this increases cybercrime and its risks. One of the main attack targets is network weakness. Therefore, cyber security is required, which first does a network scan to stop the attack. Points of vulnerability on the network can be discovered using scanning techniques. Furthermore, mitigation or recovery measures can be implemented. However, it needs a short response time and high accuracy while scanning to reduce the level of damage caused by cyber-attacks. In this paper, the proposed method improves the performance of a vulnerability management system based on network and port scanning by combining the benchmarking and scenario planning models. On a network scanning to discover open ports on a subnet, Masscan can achieve response times of less than 2 seconds, and on scenario planning for detection on a single host by Nmap can reach less than 4 seconds. It was combining both models obtained an adequate optimization response time. The total response time is less than 6 seconds.</span>

Implementing an intervention to enhance care delivery and consistency for people with hip fracture and cognitive impairment in acute hospital wards: a mixed methods process evaluation of a randomised controlled feasibility trial (PERFECTED)

ObjectivesTo determine how, and under what circumstances, the PERFECT-ER intervention was implemented in five acute hospital wards and impacted on staff practices and perceptions.DesignMixed methods process evaluation (undertaken between 2016...

Assessing agriculture's vulnerability to drought in European pre-Alpine regions

Abstract. Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define the region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on the expert's opinion. These two methods resulted in vulnerability maps with the expert weighting showing a higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the selected vulnerability factors. Thus, we recommend applying this mixed-method approach to close the gap between science and practitioners.

ChainSure: Agent free insurance system using blockchain for healthcare 4.0

The health insurance industry requires a secure data management architecture characterized by reliable information processing and fast response. Classical health insurance management system runs on a manually controlled centralized architecture which leverages a vulnerable single point failure and requires frequent human intervention. This makes the model prone to human errors and security attacks. The existing system also lacks the flexibility to choose appropriate health insurance policies for different consumers. To this end, we propose an Ethereum blockchain-based framework, ChainSure, to address this problem. With the power of TOPSIS and smart contracts, ChainSure provides an automated, tamperproof, transparent, scalable system that takes care of all the major functional blocks in a medical insurance environment. We have used the TOPSIS method in this proposed model to help the users to find an insurance policy that best suits their needs. ChainSure works in a decentralized environment and provides an interactive interface for the user. The proposed model is implemented on the Ethereum test network and its performance has been compared empirically with other state-of-art models. ChainSure is found to outperform others in terms of service integrity, latency and cost.

Smart Contract Vulnerability Detection Based on Hybrid Attention Mechanism Model

A smart contract, as an important part of blockchain technology, has attracted considerable interest from both industry and academia. It provides the basis for the realization of a variety of practical blockchain applications and plays a crucial role in the blockchain ecosystem. While it also holds a large number of digital assets, the frequent occurrence of smart contract vulnerabilities have caused huge economic losses and destroyed the blockchain-based credit system. Currently, the security and reliability of smart contracts have become a new focus of research, and there are a number of smart contract vulnerability detection methods, such as traditional detection tools based on static or dynamic analysis. However, most of them often rely on expert rules, and therefore have poor scalability and high false negative and false positive rates. Recent deep learning methods alleviate this issue, but without considering the semantic information and context of source code. To this end, we propose a hybrid attention mechanism (HAM) model to detect security vulnerabilities in smart contracts. We extract code fragments from the source code, which focus on key points of vulnerability. We conduct extensive experiments on two public smart contract datasets (a total of 24,957 contracts). Empirical results show remarkable accuracy improvement over the state-of-the art methods on five kinds of vulnerabilities, where the detection accuracy could achieve 93.36%, 80.85%, 82.56%, 85.62%, and 82.19% for reentrancy, arithmetic vulnerability, unchecked return value, timestamp dependency, and tx.origin, respectively.

Privacy preserving Federated Learning framework for IoMT based big data analysis using edge computing

The current industrial scenario has witnessed the application of several artificial intelligence-based technologies for mining and processing IoMT-based big data. An emerging distributed machine learning paradigm, Federated Learning (FL), has been widely applied in IoMT-based systems as a measure to overcome the issues associated with incorporating AI into such lightweight distributed computing systems while tackling privacy issues as well. However, extensive research has identified that classical FL is still prone to privacy threats due to data leakage and the chances of adversarial attacks during gradient transfer operations. Inspired by these issues, we propose a privacy-preserving framework (Fed_select) that ensures user anonymity in IoMT-based environments for big data analysis under the FL scheme. Fed_Select utilizes alternative minimization to limit gradients and participants in system training to decrease points of system vulnerability. The framework works on an edge computing-based architecture which ensures user anonymity via the employment of hybrid encryption techniques along with added benefits of load reduction at the central server. Also, a Laplacian noise-based differential privacy is employed on the shared attributes for security enhancement that adds confidentiality to the transferred data even during adversarial scenarios. Experimental results on standard datasets showcase that the change in the volume of gradients shared and the number of participants is not proportional to the variation in various system performance parameters. Specifically, an idealistic range of client and gradient-sharing fractions along with the appropriate value of noise for differential privacy implementation is determined. Additionally, we analyze the system from a security perspective as well as compare it with other schemes.

THE RCEP E-COMMERCE CHAPTER: IMPLICATIONS FOR THE ASEAN ECONOMIC COMMUNITY

The paper analyses the e-commerce chapter of the Regional Comprehensive Economic Partnership (RCEP) from the perspective of the ASEAN Economic Community. Part One traces the RCEP origins, evolution and interim results. Part Two is focuses on the provisions of Chapter Twelve that outlines the RCEP e-commerce-related parameters of cooperation. Arguably, their most salient features suggest that China may well use them to its best advantage by synergizing the RCEP institutional mechanisms with its mega-strategy the Belt and Road Initiative (BRI). Part Three assesses the impact of the RCEP e-commerce chapter on the Association, most importantly, on the establishment of the ASEAN Economic Community 2025. The author argues that for the association the RCEP e-commerce provisions can be a point of vulnerability rather than a reason for optimism, as ASEAN’s spectrum of the AECrelated instruments may narrow. By adapting the digital transformation to the ASEAN context, the paper takes a step forward in increasing knowledge on ASEAN evolution amidst the current global trends. In light of this, the paper contributes to the existing research on ASEAN and ASEAN-led multilateralism, as the implications of the RCEP e-commerce component have not yet been analyzed from an AEC perspective. The findings and assessments of the paper are of both academic and practical significance.

Meeting today’s healthcare needs: Medicine at the interface

The demographic of Singapore has undergone dramatic change. Historically, younger patients with communicable diseases predominated, whereas patients are now older with chronic multimorbidity and functional impairment. This shift challenges existing health and social care systems in Singapore, which must pivot to meet the changing need. The consequences of mismatched health and social care to patient needs are the fragmentation of care, dysfunctional acute care utilisation and increasing care costs. In Singapore and internationally, there is an inexorable rise in acute care utilisation, with patients facing the greatest point of vulnerability at transitions between acute and chronic care. Recently, innovative care models have developed to work across the boundaries of traditional care interfaces. These "Interface Medicine" models aim to provide a comprehensive and integrated approach to meet the healthcare needs of today and optimise value with our finite resources. These models include Acute Medical Units, Ambulatory Emergency Care, Extensivist-Comprehensivist Care, Virtual Wards, Hospital-at-Home and Acute Frailty Units. We describe these models of care across the acute care chain and explore how they may apply to the Singapore setting. We discuss how these models have evolved, appraise the evidence for clinical effectiveness, point out gaps in knowledge for further study and make recommendations for future progress.

Intelligent Information Network Security Management Strategy for Service Innovation of Manufacturing Enterprises Under Blockchain

Since the beginning of the new century, all manufacturing enterprises have been seeking ways to transform and upgrade the systems to maintain their competitive advantages. In the process of transformation and upgrading, service innovation has become more vital. In the service innovation mode, customers and suppliers are mainly involved in the manufacture of products. In the process of communication, these suppliers and customers need to rely on public key infrastructure (PKI) for data encryption and identity authentication operations, thereby achieving reliable information exchange and identity authentication in an untrusted environment. Therefore, ensuring the security of network communication for various types of users is crucial. The purpose of this paper is to solve the problem that results when a tampered certificate is difficult to trace due to the single point of failure and vulnerability of the current settlement and authentication system. In this scenario, the user's identity information is leaked in the certificate application. Resolving this problem is necessary to ensure the security of the information network.

Fraud Detection in Online Market Transactions

E-Commerce transaction process involves multiple entities at different stages such as market place, merchants, payment gateways, financial institutes. Each of them can act as a vulnerability or attack point for Malicious acts. This makes online marketing systems adapt to high-level security and data handling technology solutions like machine learning, deep learning and predictive analytics which are efficient enough to deal with highly sensitive data, predict frauds and unwanted behavioral patterns in this data. Predictive analytics with machine learning is good fraud detection system helps to identify the fraud transaction accurately and should make the detection possible in real time transactions. The techniques have been used to detect whether a transaction is fraudulent or not.

CNSC-02. BREAST TO BRAIN METASTASIS IS EXACERBATED WITH CHEMOTHERAPY THROUGH BLOOD-CEREBRAL SPINAL FLUID-BARRIER AND INDUCES ALZHEIMER’S-LIKE PATHOLOGY

Abstract Control of breast to brain metastasis remains an urgent unmet clinical need. While chemotherapies are essential in reducing systemic tumor burden, they have also shown to promote non-brain metastatic invasiveness and drug-driven neurocognitive deficits through formation of neurofibrillary tangles (NFT) independently. Now, in this study we investigated the effect of chemotherapy on brain metastatic progression and promoting tumor-mediated NFT. Results show chemotherapies promote increased brain-barrier permeability and facilitate enhanced tumor infiltration, particularly through the blood-cerebrospinal fluid-barrier (BCSFB). This is attributed to increased expression of matrix metalloproteinase 9 (MMP9) which, in turn, mediates loss of Claudin-6 within the choroid plexus cells of the BCSFB. Importantly, increased MMP9 activity in the choroid epithelium following chemotherapy results in cleavage of Tau released from breast cancer cells. This cleaved Tau forms tumor-derived NFT that further destabilize the BCSFB. Our results underline for the first time the importance of the BCSFB as a vulnerable point of entry for brain-seeking tumor cells post-chemotherapy and indicate that tumor cells themselves contribute to Alzheimer’s-like tauopathy.

PRMT3 drives glioblastoma progression by enhancing HIF1A and glycolytic metabolism

Glioblastoma (GBM) is the most common and aggressive primary brain tumor, but the mechanisms underlying tumor growth and progression remain unclear. The protein arginine methyltransferases (PRMTs) regulate a variety of biological processes, however, their roles in GBM growth and progression are not fully understood. In this study, our functional analysis of gene expression networks revealed that among the PRMT family expression of PRMT3 was most significantly enriched in both GBM and low-grade gliomas. Higher PRMT3 expression predicted poorer overall survival rate in patients with gliomas. Knockdown of PRMT3 markedly reduced the proliferation and migration of GBM cell lines and patient-derived glioblastoma stem cells (GSC) in cell culture, while its over-expression increased the proliferative capacity of GSC cells by promoting cell cycle progression. Consistently, stable PRMT3 knockdown strongly inhibited tumor growth in xenograft mouse models, along with a significant decrease in cell proliferation as well as an increase in apoptosis. We further found that PRMT3 reprogrammed metabolic pathways to promote GSC growth via increasing glycolysis and its critical transcriptional regulator HIF1α. In addition, pharmacological inhibition of PRMT3 with a PRMT3-specific inhibitor SGC707 impaired the growth of GBM cells. Thus, our study demonstrates that PRMT3 promotes GBM progression by enhancing HIF1A-mediated glycolysis and metabolic rewiring, presenting a point of metabolic vulnerability for therapeutic targeting in malignant gliomas.

VULNERABILITY ZONING OF URBAN AREAS AGAINST EARTHQUAKE (CASE STUDY: URMIA CITY)

The danger of earthquake always overshadows human societies and causes irreparable damage to these societies; therefore, preparedness to deal with this crisis by identifying vulnerability points and removing them is effective in reducing the damages caused by earthquake. Due to the location of Iran on one of the two world’s earthquake belts and the existence of many faults, the occurrence of earthquakes on the plateau of Iran is a natural phenomenon. Iran is one of the ten earthquake-prone countries in the world. Consequently, the city of Urmia is no exception to this rule due to its location in the hillsides of the Zagros Mountains and witnesses a large number of earthquakes with different intensities every year. Therefore, to deal with the above problem, we need more detailed studies in the fields of construction and safety. In this study, in order to evaluate the severity of earthquake vulnerability, effective parameters were identified and weighted using fuzzy hierarchical analysis process. Vulnerability maps were prepared by index overlap method and fuzzy logic, for statistical blocks of Urmia city and were presented visually in spatial information system. The results showed that about 50% of the city is vulnerable to earthquakes; to be more precise, about 151574 square meters, i.e. 0.005% has a very high degree of vulnerability and 11538359 square meters, with a percentage of 0.40%, has a high degree of vulnerability to earthquakes.

The endoplasmic reticulum stress response in prostate cancer.

In order to proliferate in unfavourable conditions, cancer cells can take advantage of the naturally occurring endoplasmic reticulum-associated unfolded protein response (UPR) via three highly conserved signalling arms: IRE1α, PERK and ATF6. All three arms of the UPR have key roles in every step of tumour progression: from cancer initiation to tumour growth, invasion, metastasis and resistance to therapy. At present, no cure for metastatic prostate cancer exists, as targeting the androgen receptor eventually results in treatment resistance. New research has uncovered an important role for the UPR in prostate cancer tumorigenesis and crosstalk between the UPR and androgen receptor signalling pathways. With an improved understanding of the mechanisms by which cancer cells exploit the endoplasmic reticulum stress response, targetable points of vulnerability can be uncovered.

Enabling Blockchain Services for IoE with Zk-Rollups.

The Internet of Things includes all connected objects from small embedded systems with low computational power and storage capacities to efficient ones, as well as moving objects like drones and autonomous vehicles. The concept of Internet of Everything expands upon this idea by adding people, data and processing. The adoption of such systems is exploding and becoming ever more significant, bringing with it questions related to the security and the privacy of these objects. A natural solution to data integrity, confidentiality and single point of failure vulnerability is the use of blockchains. Blockchains can be used as an immutable data layer for storing information, avoiding single point of failure vulnerability via decentralization and providing strong security and cryptographic tools for IoE. However, the adoption of blockchain technology in such heterogeneous systems containing light devices presents several challenges and practical issues that need to be overcome. Indeed, most of the solutions proposed to adapt blockchains to devices with low resources confront difficulty in maintaining decentralization or security. The most interesting are probably the Layer 2 solutions, which build offchain systems strongly connected to the blockchain. Among these, zk-rollup is a promising new generation of Layer 2/off-chain schemes that can remove the last obstacles to blockchain adoption in IoT, or more generally, in IoE. By increasing the scalability and enabling rule customization while preserving the same security as the Layer 1 blockchain, zk-rollups overcome restrictions on the use of blockchains for IoE. Despite their promises illustrated by recent systems proposed by startups and private companies, very few scientific publications explaining or applying this barely-known technology have been published, especially for non-financial systems. In this context, the objective of our paper is to fill this gap for IoE systems in two steps. We first propose a synthetic review of recent proposals to improve scalability including onchain (consensus, blockchain organization, …) and offchain (sidechain, rollups) solutions and we demonstrate that zk-rollups are the most promising ones. In a second step, we focus on IoE by describing several interesting features (scalability, dynamicity, data management, …) that are illustrated with various general IoE use cases.

Analysis of Planetary Gear Transmission Characteristics Based on ANSYS

Planetary gear transmission is widely used in roadhead, crane and other transmission equipment, its reliability and stability are related to the service life and work efficiency of equipment, but the current research on planetary gear transmission device is not comprehensive, lack of accurate analysis of gear meshing process load. Therefore, in this paper, ANSYS software as a platform, through the construction of dynamics module, to solve the gear teeth surface, gear teeth root and gear teeth tip stress analysis and deformation and displacement, the finite element analysis. The research results provide necessary technical support for the design and production of planetary gear transmission.
 Aims: Through finite element analysis of planetary gear transmission, the dynamic parameters of planetary gear transmission are solved, and the reliability and stability of planetary gear transmission equipment are improved.
 Study Design: By constructing the dynamics module of planetary gear, the stress analysis, deformation and displacement of gear tooth surface, gear tooth root and gear tooth top are solved, and the finite element analysis is carried out.
 Place and Duration of Study: North China University of Water Resources and Electric Power, from March to July 2022.
 Methodology: The finite element analysis was carried out on the model of planetary gear transmission mechanism, and the model was established and simplified by using SolidWorks software. The modal analysis and dynamic analysis were carried out by using ANSYS software, and the meshes were divided and constraints were added. Finally, the parameters such as stress, strain and displacement of the meshing position were solved.
 Results: The result of model meshes is 357575 units and 204871 nodes. The algorithm has 219 iterations and 15 convergence points. The experimental results show that there is a meshing position with the worst contact fatigue strength in the contact area between the outer ring gear and the planetary gear tooth surface. At this position, the contact stress value of the tooth surface is 22626Pa.
 Conclusion: In this paper, the planetary gear device is modeled by SolidWorks software, and the finite element analysis is carried out by ANSYS software to obtain the stress and strain parameters in the transmission process of the device, as well as the worst meshing point of the gear, the most vulnerable point of fatigue and other dangerous points. It lays a certain technical foundation for the optimization and improvement of gear and the design and production of planetary gear transmission device.

BSCI-12 BREAST TO BRAIN METASTASIS IS EXACERBATED WITH CHEMOTHERAPY THROUGH BLOOD-CEREBRAL SPINAL FLUID-BARRIER AND INDUCES ALZHEIMER’S-LIKE PATHOLOGY

Abstract Control of breast to brain metastasis remains an urgent unmet clinical need. While chemotherapies are essential in reducing systemic tumor burden, they have also shown to promote non-brain metastatic invasiveness and drug-driven neurocognitive deficits through formation of neurofibrillary tangles (NFT) independently. Now, in this study we investigated the effect of chemotherapy on brain metastatic progression and promoting tumor-mediated NFT. Results show chemotherapies promote increased brain-barrier permeability and facilitate enhanced tumor infiltration, particularly through the blood-cerebrospinal fluid-barrier (BCSFB). This is attributed to increased expression of matrix metalloproteinase 9 (MMP9) which, in turn, mediates loss of Claudin-6 within the choroid plexus cells of the BCSFB. Importantly, increased MMP9 activity in the choroid epithelium following chemotherapy results in cleavage of Tau released from breast cancer cells. This cleaved Tau forms tumor-derived NFT that further destabilize the BCSFB. Our results underline for the first time the importance of the BCSFB as a vulnerable point of entry for brain-seeking tumor cells post-chemotherapy and indicate that tumor cells themselves contribute to Alzheimer’s-like tauopathy.

트랜스휴머니즘의 몸의 취약성 제거론에 대한 생명윤리적 비판

This paper aims to critique the post-human project of transhumanism that attempts to engineer and artificially evolve the human body by 'removing the vulnerability of the human body' in the post-corona era where 'the vulnerability of the human body' is a problem. First, taking the concept of vulnerability as a starting point, the type and context of vulnerability claimed by transhumanism are identified. Next, transhumanism's reductionist perspective of the human body to attempt engineering evolution is considered. From the point of view of ontological Personalism, the human body is presented as a body with life, a body that acts toward a life purpose and a body that holds human nature. This paper asserts that the human body reveals the human being itself. The scientific, utilitarian, and Enlightenment values embedded in the transhumanism's strategy for eliminating the vulnerability of the body can instrumentalize human life by alienating the human being from the body and reducing human life to the level of usefulness. Rather, This strategy can lead to new vulnerability. On the contrary, the vulnerability of the human body has a positive aspect, which allows the human being to be more empathetic to others, to complete himself, and to grow with others. In conclusion, the vulnerability of the human body is not a negative factor that needs to be completely eliminated, but a marker that clearly shows the basis of human dignity and human flourishing.

Evaluation of a combined and portable light-ultrasound device with which to deter red deer

Human–wildlife conflicts are a growing problem in Northern Hemisphere where wild ungulates are one of the taxonomic groups most frequently involved. To mitigate these conflicts, it is essential to develop preventive actions able to avoid encounters between wildlife and human (activities). We here employed photo-trapping to evaluate the behaviour of red deer (Cervus elaphus) when confronted with dissuasive portable deterrents that function on the basis of changing patterns of light and ultrasound. This was done by following a before/after experimental design, with two phases: (i) a test phase, with active deterrents, and (ii) a control phase, without deterrents. When deterrents were activated they achieved a 48.96% reduction in the frequency of use by red deer (up to 66.64% when it was assessed on a thinner Sect. 10 m wide from the line of deterrents) and produced a reduction of 67.71% in the frequency of deterrent-line crossings. However, a habituation effect was detected since the use by red deer of the treatment area increased as time since treatment. These results indicate that these portable devices are effective as regards dissuading deer, mainly on short time scales. The deterrents tested here could be suitable for use at focal points for short periods or in combination with other methods to improve their effectiveness in vulnerability points. This device could potentially be used to mitigate conflicts caused by wildlife species and in response to relevant and timely situations, such as vehicle collisions and damage to crops, among others.