Critical Vulnerabilities Research Articles

The Critical Vulnerability of an Authentic Leader as a Сatalyst for Achieving Outstanding Prosocial Results

Having been in management for more than 15 years, we have identified empirical evidence of critical vulnerability in business leaders who implemented large-scale organizational change and ultimately achieved outstanding prosocial outcomes. This vulnerability may present as resistance or criticism from stakeholders—employees, partners, and shareholders—marked by distrust in leadership vision and active sabotage of decisions, which potentially leads to the termination of the leader's powers. However, as the stakeholders' mindset evolves, the vulnerability tends to subside, paving the way for company consolidation, substantial organizational achievements, self-actualization for stakeholders and recognition for the leader. Such shift allows us to hypothesize that: 1) unique behavioral patterns of authentic leaders during organizational change implementation expose them to the observed critical vulnerability but ultimately lead to substantial prosocial results; 2) the main reason for leader vulnerability is the gap in leadership mindset levels between the leader and stakeholders at the onset of organizational change. Relying on the described assumptions, we executed preliminary research on leader vulnerability, aiming to explore unique leader behavior patterns that cause critical vulnerability. The study involved 8 top managers who are currently leading organizational changes within their organizations. We used purposive sampling to ensure participants’ significant leadership experience and their transformative impact. The research methodology relied on qualitative methods—in-depths interviews. Applying the Michigan Model of Leadership with its Competing Values Framework (CVF), we conducted a thematic analysis of the collected data. We determined that vulnerability typically manifests as a result of a strategic endeavor by leaders to ensure the evolution of stakeholder mindset for subsequent empowerment of them. The study advances knowledge about authentic leadership by emphasizing vulnerability's vital function in accomplishing remarkable prosocial organizational outcomes. More research will be required to create a framework for recognizing and assisting leaders who are critically vulnerable during organizational change implementation.

Prevalence of S-methyl-5'-thioadenosine Phosphorylase (MTAP) Deficiency in Human Cancer: A Tissue Microarray Study on 13,067 Tumors From 149 Different Tumor Types.

Loss of S-methyl-5'-thioadenosine phosphorylase (MTAP) expression is a common event in cancer leading to a critical vulnerability of cancer cells towards anti-cancer drugs. Homozygous MTAP deletions result in a complete expression loss that can be detected by immunohistochemistry (IHC). In this study, a tissue microarray containing 17,078 samples from 149 different tumor entities was analyzed by IHC, and complete MTAP loss was validated by fluorescence in situ hybridization. MTAP loss was observed in 83 of 149 tumor categories, including neuroendocrine neoplasms (up to 80%), Hodgkin lymphoma (50.0%), mesothelioma (32.0% to 36.8%), gastro-intestinal adenocarcinoma (4.0% to 40.5%), urothelial neoplasms (10.5% to 36.7%), squamous cell carcinomas (up to 38%), and various types of sarcomas (up to 20%) and non-Hodgkin lymphomas (up to 14%). Homozygous MTAP deletion was found in 90% to 100% of cases with MTAP expression loss in most tumor categories. However, neuroendocrine tumors, Hodgkin lymphomas, and other lymphomas lacked MTAP deletions. MTAP deficiency was significantly linked to unfavorable tumor phenotype in selected tumor entities and the presence of PD-L1 expression on tumor cells, absence of PD-L1 expression on immune cells, and a low density of CD8 + lymphocytes. In summary, MTAP deficiency can occur in various tumor entities and is linked to unfavorable tumor phenotype and noninflamed tumor microenvironment, but is not always related to deletions. MTAP IHC is of considerable diagnostic value for the detection of neoplastic transformation in multiple different applications.

SAST Tools and Manual Testing to Improve the Methodology of Vulnerability Detection in Web Applications

Statically analyzing code during development is a common process of the development process, using Static Application Security Testing tools. SAST analyzes code without its execution and is also very fast compared to dynamic means and therefore focuses on a certain program part. However, the results of static analysis tools are not always accurate, either missing vulnerabilities or reporting false positives. This paper considers an evaluation of several SAST tools and an analysis of student code samples with known vulnerabilities, comparing manual analysis with the results of SAST tools. The results confirmed that SAST tools properly identify critical vulnerabilities and provide errors. A tool has identified ShiftLeft as the most efficient tool; however, its findings overlapped with the results of other tools for some applications. In addition, an analysis of student projects showed the most frequent vulnerabilities as Cross-site Scripting (XSS), NoSQL/SQL Injection, and Server-Side Request Forgery (SSRF) which make up more than 52% of the found vulnerabilities.

Blockchain-based IoT security solutions for IDS research centers

The rapid evolution of the Internet of Things (IoT) has connected real-world objects to the Internet, enhancing digital interaction and introducing critical security vulnerabilities. Intrusion Detection Systems (IDS) are essential in identifying threats and protecting Internet of Things devices from cyberattacks. A secure, decentralized platform enabled by blockchain technology offers the optimal solution for researchers worldwide to collaboratively address the challenges of IoT security effectively. This study introduces a blockchain-based IDS research center to strengthen IoT network security via global collaboration. It demonstrates the benefits of combining IDS with blockchain to improve cybersecurity in research centers, facilitating the efficient sharing of security solutions. By defining various node types on the blockchain, the platform ensures controlled access to services and streamlined network management through specific authorizations. Research centers can contribute to the blockchain with their findings, whereas others utilize the platform to access IDS services. Our work uses machine learning algorithms to achieve promising performance in detecting DDoS attacks, with the XGBoost algorithm demonstrating good results compared to the literature. The findings illustrate how effectively the presented approach works with blockchain technology and the CiCIoT2023 dataset to provide safe and decentralized information sharing.

The Endo-Lysosomal Damage Response.

Lysosomes are the degradative endpoints of material delivered by endocytosis and autophagy and are therefore particularly prone to damage. Membrane permeabilization or full rupture of lysosomal or late endosomal compartments is highly deleterious because it threatens cellular homeostasis and can elicit cell death and inflammatory signaling. Cells have developed a complex response to endo-lysosomal damage that largely consists of three branches. Initially, a number of repair pathways are activated to restore the integrity of the lysosomal membrane. If repair fails or if damage is too extensive, lysosomes are isolated and degraded by a form of selective autophagy termed lysophagy. Meanwhile, an mTORC1-governed signaling cascade drives biogenesis and regeneration of new lysosomal components to reestablish the full lysosomal capacity of the cell. This damage response is vital to counteract the effects of various conditions, including neurodegeneration and infection, and can constitute a critical vulnerability in cancer cells.

Toward next-generation networks: A blockchain-based approach for core network architecture and roaming identity verification

With the evolution of next-generation communication networks, ensuring robust Core Network (CN) architecture and data security has become paramount. This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks. Traditional centralized network architectures are vulnerable to Distributed Denial of Service (DDoS) attacks, particularly in roaming scenarios where there is also a risk of private data leakage, which imposes significant operational demands. To address these issues, we introduce the Blockchain-Enhanced Core Network Architecture (BECNA) and the Secure Decentralized Identity Authentication Scheme (SDIDAS). The BECNA utilizes blockchain technology to decentralize data storage, enhancing network security, stability, and reliability by mitigating Single Points of Failure (SPoF). The SDIDAS utilizes Decentralized Identity (DID) technology to secure user identity data and streamline authentication in roaming scenarios, significantly reducing the risk of data breaches during cross-network transmissions. Our framework employs Ethereum, free5GC, Wireshark, and UERANSIM tools to create a robust, tamper-evident system model. A comprehensive security analysis confirms substantial improvements in user privacy and network security. Simulation results indicate that our approach enhances communication CNs security and reliability, while also ensuring data security.

Alkaline stability of polyester nanofiltration membranes prepared by interfacial polymerization

Polyester nanofiltration membranes typically outperform traditional polyamide alternatives in fouling resistance, water flux, and chlorine tolerance. However, their alkali resistance remains poorly understood. This study investigates the stability of polyester membranes, prepared via interfacial polymerization of eight hydroxyl monomers with TMC, in alkaline conditions (pH 12.4). We systematically recorded changes in water flux and solute rejection and employed SEM, AFM, zeta-potential, contact angle analysis, and XPS to examine physicochemical structural changes during hydrolysis. The findings reveal that most membranes are susceptible to alkaline hydrolysis, evidenced by increased water flux and decreased rejection rates. Specifically, membranes derived from pyrogallol-based hydroxyl monomers exhibited the greatest instability, whereas those incorporating sodium alginate demonstrated remarkable stability. After immersion in water, the water flux of the TA membrane increased from 8.4 to 21.2 Lm−2h−1bar−1 and the rejection rate decreased from 36.6 % to 12.1 %. the water flux of PG membrane was from 22.0 to 54.2 Lm−2h−1bar−1, while the rejection rate decreased from 60.2 % to 22.7 %. DFT calculations corroborate these observations, linking ester bond energies with membrane stability. This study not only advances our understanding of polyester nanofiltration membrane properties but also highlights critical vulnerabilities in alkali environments, guiding future improvements.

Protecting patient privacy in the age of smart healthcare: practical cybersecurity measures for individuals and healthcare providers

The rise of smart healthcare technologies, including wearable devices, telemedicine, and the Internet of Medical Things (IoMT), has significantly transformed patient care. However, these advancements have also introduced critical cybersecurity vulnerabilities. This paper explores the escalating threats to patient privacy in the digital age, highlighting substantial increase in cyberattacks on healthcare systems, with data breaches averaging $10.1 million per incident. Analysis reveals several prominent cyber threats to smart healthcare technologies, such as ransomware, phishing, Distributed Denial of Service (DDoS) attacks, Man-in-the-Middle (MitM) attacks, malware, SQL injection, and insider threats, all of which compromise the confidentiality and integrity of patient data. Notably, ransomware attacks have surged by 123% in recent years, severely disrupting patient care and privacy. To mitigate these risks, this commentary proposes actionable cybersecurity measures for both healthcare providers and individuals. Healthcare organizations should conduct thorough risk assessments, implement stringent access controls, encrypt sensitive data, provide comprehensive cybersecurity training for staff, and establish robust incident response plans. Concurrently, individuals are encouraged to remain vigilant about cybersecurity threats, secure their personal devices, use only reputable healthcare applications, be cautious with data sharing, and regularly monitor their health information. By adopting these strategies, both healthcare providers and patients can better safeguard sensitive health information and strengthen the security framework of smart healthcare systems.

A Privacy-Preserving Three-Factor Authentication System for IoT-Enabled Wireless Sensor Networks

Recently, Sahoo et al. introduced a three-factor authentication scheme for Wireless Sensor Networks (WSNs) based on an elliptic curve cryptosystem. Nonetheless, upon closer examination, we have identified critical vulnerabilities in their scheme, including susceptibility to user impersonation, gateway impersonation, sensor node impersonation attacks, and a breach in the three-factor security aspect. Further, the scheme fails to withstand offline sensor node identity guessing attacks, man-in-the-middle attacks, and known session-specific temporary information attacks. Intending to elevate both security and efficiency, we propose a novel three-factor authentication scheme that capitalizes on the strengths of a fuzzy extractor and a cryptographic one-way hash function. The proposed scheme’s security has been rigorously assessed using the SCYTHER tool, confirming its validity under the real-or-random (ROR) model. Moreover, a heuristic analysis exemplifies that the scheme effectively withstands various known cryptographic attacks. Consequently, the performance comparisons establish the superiority of our scheme over related approaches in terms of security and efficiency. Additionally, its suitability for WSNs is evident due to the minimal overhead on the sensor nodes, making it a highly promising solution for real-world implementation.

Software verification challenges in the blockchain ecosystem

Blockchain technology has created a new software development context, with its own peculiarities, mainly due to the guarantees that the technology must satisfy, that is, immutability, distributability, and decentralization of data. Its rapid evolution over the last decade implied a lack of adequate verification tools, exposing developers and users to critical vulnerabilities and bugs. This paper clarifies the extent of block chain-oriented software (BoS), that goes well beyond smart contracts. Moreover, it provides an overview of the challenges related to software verification in the blockchain context, encompassing smart contracts, blockchain layers, cross-chain applications, and, more generally, BoS. This study aims to highlight the shortcomings of the state-of-art and of the state-of-practice of software verification in that context and identify, at the same time, new research directions.

Location Privacy Protection in Edge Computing: Co-Design of Differential Privacy and Offloading Mode

Edge computing has emerged as an innovative paradigm that decentralizes computation to the network’s periphery, empowering edge servers to manage user-initiated complex tasks. This strategy alleviates the computational load on end-user devices and increases task processing efficiency. Nonetheless, the task offloading process can introduce a critical vulnerability, as adversaries may infer a user’s location through an analysis of their offloading mode, thereby threatening the user’s location privacy. To counteract this vulnerability, this study introduces differential privacy as a protective mechanism to obscure the user’s offloading mode, thereby safeguarding their location information. This research specifically addresses the issue of location privacy leakage stemming from the correlation between a user’s location and their task offloading ratio. The proposed strategy is based on differential privacy. It aims to increase the efficiency of offloading services and the benefits of task offloading. At the same time, it ensures privacy protection. An innovative optimization technique for task offloading that maintains location privacy is presented. Utilizing this technique, users can make informed offloading decisions, dynamically adjusting the level of obfuscation in response to the state of the wireless channel and their privacy requirements. This study substantiates the feasibility and effectiveness of the proposed mechanism through rigorous theoretical analysis and extensive empirical testing. The numerical results demonstrate that the proposed strategy can achieve a balance between offloading privacy and processing overhead.

Overcoming Chemoresistance in Cancer: The Promise of Crizotinib.

Chemoresistance is a major obstacle in cancer treatment, often leading to disease progression and poor outcomes. It arises through various mechanisms such as genetic mutations, drug efflux pumps, enhanced DNA repair, and changes in the tumor microenvironment. These processes allow cancer cells to survive despite chemotherapy, underscoring the need for new strategies to overcome resistance and improve treatment efficacy. Crizotinib, a first-generation multi-target kinase inhibitor, is approved by the FDA for the treatment of ALK-positive or ROS1-positive non-small cell lung cancer (NSCLC), refractory inflammatory (ALK)-positive myofibroblastic tumors (IMTs) and relapsed/refractory ALK-positive anaplastic large cell lymphoma (ALCL). Crizotinib exists in two enantiomeric forms: (R)-crizotinib and its mirror image, (S)-crizotinib. It is assumed that the R-isomer is responsible for the carrying out various processes reviewed here The S-isomer, on the other hand, shows a strong inhibition of MTH1, an enzyme important for DNA repair mechanisms. Studies have shown that crizotinib is an effective multi-kinase inhibitor targeting various kinases such as c-Met, native/T315I Bcr/Abl, and JAK2. Its mechanism of action involves the competitive inhibition of ATP binding and allosteric inhibition, particularly at Bcr/Abl. Crizotinib showed synergistic effects when combined with the poly ADP ribose polymerase inhibitor (PARP), especially in ovarian cancer harboring BRCA gene mutations. In addition, crizotinib targets a critical vulnerability in many p53-mutated cancers. Unlike its wild-type counterpart, the p53 mutant promotes cancer cell survival. Crizotinib can cause the degradation of the p53 mutant, sensitizing these cancer cells to DNA-damaging substances and triggering apoptosis. Interestingly, other reports demonstrated that crizotinib exhibits anti-bacterial activity, targeting Gram-positive bacteria. Also, it is active against drug-resistant strains. In summary, crizotinib exerts anti-tumor effects through several mechanisms, including the inhibition of kinases and the restoration of drug sensitivity. The potential of crizotinib in combination therapies is emphasized, particularly in cancers with a high prevalence of the p53 mutant, such as triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSOC).

PROACTIVE RISK IDENTIFICATION IN THE CHANGING AUTOMOTIVE INDUSTRY: A COMPREHENSIVE FRAMEWORK

Advancements in technology, shifts in consumer preferences, and revised regulations are all propelling rapid growth in the automotive industry. Traditional approaches to risk management are insufficient when confronted with the emerging risks presented by this transition. Adopting a proactive approach to detecting hazards is essential for successfully navigating this constantly evolving world. The present work presents a comprehensive framework for the proactive identification and management of risks within the ever-changing automotive sector. The essay commences with providing an overview of the industry's historical context and current advancements, followed by an analysis of the inadequacy of conventional risk management methods facing emerging risks. Furthermore, it proposes a complete framework specifically tailored to tackle the unique challenges faced by the automotive sector. Implementing a comprehensive approach to risk management, this framework integrates assessments of technology, markets, legislation, cybersecurity, and supply chain vulnerabilities. The analysis proceeds to discuss potential issues associated with implementing this methodology and offers remedies to overcome them. In order to enhance their decision-making and resilience in the face of industry-wide complexity, stakeholders in the automobile sector might adopt a pre-emptive approach to risk management. This study contributes to our knowledge of proactive risk management strategies and enhances our understanding of future risk identification in the automobile industry. Methodology: By employing this approach, these enterprises can enhance their ability to make well-informed judgements on their risk management plans. The technique facilitates the identification of critical vulnerabilities, therefore enabling the implementation of preventive measures to mitigate the effects of specific risks on net income. Moreover, the model possesses the capability to undertake data analysis from multiple companies within the same industry, thereby offering potential insights that can be extrapolated to other similar organisations. This has the potential to result in enhanced risk management strategies within India's automobile industry.

Comprehensive Review of Advanced Machine Learning Techniques for Detecting and Mitigating Zero-Day Exploits

This paper provides an in-depth examination of the latest machine learning (ML) methodologies applied to the detection and mitigation of zero-day exploits, which represent a critical vulnerability in cybersecurity. We discuss the evolution of machine learning techniques from basic statistical models to sophisticated deep learning frameworks and evaluate their effectiveness in identifying and addressing zero-day threats. The integration of ML with other cybersecurity mechanisms to develop adaptive, robust defense systems is also explored, alongside challenges such as data scarcity, false positives, and the constant arms race against cyber attackers. Special attention is given to innovative strategies that enhance real-time response and prediction capabilities. This review aims to synthesize current trends and anticipate future developments in machine learning technologies to better equip researchers, cybersecurity professionals, and policymakers in their ongoing battle against zero-day exploits.

Climate-induced vulnerability and conservation strategies for coastal heritage sites in the southern Mediterranean Sea using integrated remote sensing and flood modeling

Coastal heritage sites along the southern Mediterranean Sea confront immediate and severe threats from climate change, intensified by rising sea levels and ongoing shoreline erosion. This study presents a comprehensive approach to monitor and safeguard these significant locations, addressing the challenges posed by climate change. Leveraging high-resolution satellite data sources such as Pleiades imagery and Landsat data, shoreline detection was optimized using the Lee Filter and Canny edge detection techniques. Flood modeling and sea-level rise projections were incorporated to comprehensively assess dynamic coastal landscapes. Advanced methods, including the Prophet model, were employed for temperature predictions, showcasing good predictive accuracy. The results provide crucial insights into climate resilience and temperature forecasting amid rising temperatures associated with climate change. Alarming statistics include an annual erosion rate of −4.47 m/year and critical vulnerability to sea-level rise scenarios. In the extreme 4-m sea-level rise scenario, approximately 35 % of the total surface area (approximately 116.79 m2) is projected to be at risk of submersion, emphasizing the severe susceptibility of these sites to climate-induced sea-level rise. Even in the less severe 2-m scenario, around 24 % of the total area (approximately 80.79 m2) could potentially face submersion, posing a substantial threat to the ancient fortifications of the El Borj heritage site. This study underscores the critical role of preserving coastal heritage in addressing the challenges posed by climate change.

Water-Soluble and Freezable Aluminum Salt Vaccine Adjuvant.

Particulate aluminum salts have long occupied a central place worldwide as inexpensive immunostimulatory adjuvants that enable induction of protective immunity for vaccines. Despite their huge benefits and safety, the particulate structures of aluminum salts require transportation and storage at temperatures between 2 °C and 8 °C, and they all have exquisite sensitivity to damage caused by freezing. Here, we propose to solve the critical freezing vulnerability of particulate aluminum salt adjuvants by introducing soluble aluminum salts as adjuvants. The solubility properties of fresh and frozen aluminum chloride and aluminum triacetate, each buffered optimally with sodium acetate, were demonstrated with visual observations and with UV-vis scattering analyses. Two proteins, A244 gp120 and CRM197, adjuvanted either with soluble aluminum chloride or soluble aluminum triacetate, each buffered by sodium acetate at pH 6.5-7.4, elicited murine immune responses that were equivalent to those obtained with Alhydrogel®, a commercial particulate aluminum hydroxide adjuvant. The discovery of the adjuvanticity of soluble aluminum salts might require the creation of a new adjuvant mechanism for aluminum salts in general. However, soluble aluminum salts might provide a practical substitute for particulate aluminum salts as vaccine adjuvants, thereby avoiding the risk of inactivation of vaccines due to accidental freezing of aluminum salt particles.

The Most Important Types of Cyber Attacks that France is Expected to Face in the Future and the Cyber Security Measures it Must Implement to Protect Critical Infrastructure, Telecommunication Networks and Personal Data

As the digital landscape continues to evolve, nations like France find themselves on the frontline of an escalating cyber warfare scenario. This abstract provides an insightful overview of the most significant types of cyber attacks that France is expected to face in the future, offering a comprehensive analysis based on current trends and emerging technologies. The research delves into the realm of advanced persistent threats (APTs), examining the sophisticated techniques employed by state-sponsored actors and cybercriminal organizations to compromise critical infrastructure, sensitive data, and national security. It explores the evolving landscape of ransomware attacks, focusing on the potential impact on both public and private sectors, and the looming threat of extortion campaigns that could cripple essential services. Furthermore, the abstract sheds light on the rising concern of supply chain attacks, as interconnected global networks make businesses and government entities vulnerable to malicious actors seeking to exploit weaknesses in third-party systems. The research also explores the nuances of social engineering attacks, recognizing the human element as a critical vulnerability that threat actors may exploit through targeted phishing campaigns and manipulation tactics. In addition, the abstract touches upon the growing menace of Internet of Things (IoT) vulnerabilities, acknowledging the increased interconnectivity of devices and the potential for large-scale disruptions. It also considers the implications of emerging technologies such as artificial intelligence and quantum computing in shaping the future threat landscape. By examining these diverse aspects of cyber threats, this abstract aims to provide a forward-looking perspective on the challenges France is likely to encounter in the digital realm. As Cyber security becomes an integral component of national defense, understanding these anticipated threats is crucial for policymakers, security experts, and technology professionals seeking to fortify France’s resilience against the evolving nature of cyber attacks.

Cyber Security Risk Assessment Methods for Smart Healthcare

The perverseness of the Internet of Things (IoT) has reached the healthcare sector, where interconnected medical devices are transforming how we deliver and manage health. These devices, linked wirelessly, create a vast network known as Internet of Medical Things (IoMT), that integrates seamlessly with the broader healthcare system. This interconnected infrastructure facilitates the exchange of massive amounts of patient data, paving the way for a more distributed and data-driven approach to healthcare. In healthcare’s ICT environment rely heavily on electronic health records (EHR), e-prescribing systems and other systems. Protecting this sensitive data necessitates robust cybersecurity measures. Even though data security is an indirect cost, it is crucial for healthcare systems. In general, patient trust in a healthcare system depends on the infrastructure’s ability to protect data from security and privacy threats. A critical component of this strategy is security risk assessment. A risk is an indirect cost borne by those designing these systems. The risk assessment process identifies, evaluates, and prioritizes potential threats to the organization’s assets including hardware and software. By assessing risks before acting, healthcare organizations can effectively allocate resources to mitigate the most critical vulnerabilities. While broadly applicable cyber risk assessment frameworks like NIST, ISO, and OCTAVE exist, they may lack a strong risk between assets, threats and impacts, and controls. Therefore, they do not provide a comprehensive picture for healthcare specifically. A more thorough examination is required to establish a strong association between protected systems, potential threats, and the resulting risks. This paper critically reviews these frameworks and their methodologies and limitations for healthcare cybersecurity. Even though data security is an indirect cost, it is crucial for healthcare systems.

Инновационный потенциал регионов арктической зоны Российской Федерации: состояние и пространственная дифференциация

The article considers the components of the innovation potential of Russian regions that are fully or partially included in the Arctic zone. The purpose of the article is to analyze and evaluate the state and dynamics of innovative development of the regions of the Arctic zone of the Russian Federation. The methodology for calculating the composite index of innovative development is proposed. The calculations are made on the basis of the database formed by the authors, which consists of four blocks; the main conclusions on the blocks are formed. According to the composite index for the period 20152021, the leading positions are occupied by the Krasnoyarsk Krai, the Arkhangelsk Oblast and the Komi Republic, and the Republics of Karelia, Sakha (Yakutia) and Komi in terms of the index growth rate. The study of the state, dynamics and level of innovation development in the regions of the AZRF shows that some components of innovation potential are unevenly developed in the regions that are fully or partially included in the AZRF. At the same time, the regions differ in the dynamics of innovative development. Thus, the worst indicators of innovative development in accordance with the proposed methodology are observed in the Arkhangelsk Oblast, Chukotka and Nenets Autonomous okrugs. The high correlation between the composite index of innovative development and indicators of socio-economic development of the regions revealed by the authors characterizes the positive impact of innovation activity on the socio-economic development of the AZRF subjects. In this regard, the key recommendations are the following: improvement of legislative support for the formation of eco-industrial, tourist zones, innovation sites and cluster formations in the Arctic territory within the framework of testing new formats of economic intensification of the Russian Arctic regions; formation of a macro-regional register of suppliers of innovative products for the projects of residents of the AZRF with the distribution of preferential measures of a special economic and administrative regime. The prospects of the research are related to the study of critical vulnerabilities in the production and technological processes of the sectors of specialization of the Arctic regions in import substitution.

Is Blockchain a Panacea for Guarding PDO Supply Chains? Exploring Vulnerabilities, Critical Control Points, and Blockchain feasibility in Greece

AbstractWithin food Supply Chains (SCs), food products labeled through Geographical Indications (GIs) hold paramount importance as distinctive and culturally significant entities, ensuring the integrity and distinctiveness of regional specialties. By strictly regulating the geographic origin and production methods, the Protected Designation of Origin (PDO) not only guarantees the preservation of traditional practices but also safeguards the cultural legacy and identity of the regions where genuine PDO products are produced. However, the very mechanisms safeguarding PDO authenticity can be exploited within globalized food systems, creating opportunities for fraudulent activities and intentional or unintentional adulteration. This study specifically delves into the overarching realm of PDO SCs, using PDO Feta cheese as a prominent case study. Through an assessment of Feta cheese SC in Greece, encompassing the Delphi Technique with the amalgamation of the design stages of Hazard Analysis and Critical Control Points (HACCP), Vulnerabilities Assessment and Critical Control Point (VACCP), and Threat Assessment and Critical Control Point (TACCP) methodologies, the operations, vulnerabilities, and critical control points are scrutinized. The results indicate multifaceted vulnerabilities and Critical Control Points (CCPs) in the Feta cheese SC that need to be addressed and constitute a precursor for augmenting PDO SCs. Moreover, the utilization of Blockchain Technology (BT) exhibits intrinsic potential for enhancing the administration of supply chains with the potential to fundamentally transform data management practices and foster increased levels of trust among stakeholders.