Security Landscape Research Articles

Securing the virtual marketplace: Navigating the landscape of security and privacy challenges in E-Commerce

This paper provides a comprehensive examination of the evolving challenges and critical considerations surrounding security and privacy within the realm of e-commerce. As the digital marketplace continues to expand, the significance of safeguarding sensitive information and ensuring user privacy has become paramount. This paper explores various dimensions of security threats, including data breaches, phishing attacks, and vulnerabilities associated with payment gateways, shedding light on the potential repercussions for businesses and consumers alike. Additionally, it delves into emerging technologies and innovative solutions aimed at fortifying e-commerce platforms against evolving cyber threats. The paper not only identifies the existing vulnerabilities but also proposes proactive strategies and future directions for research and implementation. Topics such as biometric authentication, post-quantum cryptography, and privacy-preserving technologies are explored as potential avenues for enhancing the security posture of e-commerce systems. The research presented emphasizes the critical intersection of technology, regulation, and user awareness in fostering a secure and trustworthy online shopping environment. By offering insights into both the current state of e-commerce security and promising avenues for future exploration, this paper aims to contribute to the ongoing discourse on fortifying the digital marketplace against the challenges posed by an ever-evolving cyber landscape.

ANALYZING CYBERCRIMES AND CYBER SECURITY LANDSCAPE IN THE BANKING SECTOR OF INDIA

Since the onset of COVID-19, the banking sector has been completely digitalized, in terms of both back-end and front-end operations. With the emergence of latest technologies, the incidence of cyber-attacks is constantly increasing . Most of the banking institutions are online it has caused ransomware, phishing attacks, privacy concerns, and other risks. Both online and mobile services lack in strong security measures and cyber threats are getting more common. The banking sector always remains on the radar of cybercriminals for financial benefits. This paper studies the devastating effect of cybercrime in the Indian banking sector, existing cyber security landscapes to curb the effects of cyber threats, and measures to protect the Indian banking sector. The study is based on secondary data collected from various online sources, articles, research papers, government portals, news sites, etc. It is also required for case studies of cyber crimes that have led to significant financial loss in recent years. This paper will look into cyber security measures that will help financial institutions, banks, and society by dealing with cyber-attacks that can be prevented for better security.

Future Horizons: AI-Enhanced Threat Detection in Cloud Environments: Unveiling Opportunities for Research

In this extensive and comprehensive review paper, we delve into the dynamic landscape of artificial intelligence (AI)-enhanced threat detection within cloud environments. The evolution of this field, from traditional methodologies to the seamless integration of AI, is meticulously explored, providing a nuanced understanding of the transformative potential of AI in bolstering cyber security measures. The exploration encompasses a myriad of crucial aspects, offering readers a holistic view of the subject. The revolutionary impact of AI is scrutinized, emphasizing its role in reshaping the conventional paradigms of threat detection and response. The paper meticulously addresses current challenges in cloud security, providing insights into the multifaceted nature of contemporary threats and how AI serves as a robust defense mechanism. As we navigate through the intricacies of this field, the review paper sheds light on ongoing research prospects, presenting a roadmap for future endeavors. Real-world case studies are examined to illustrate the practical applications of AI-enhanced threat detection, offering valuable lessons and perspectives for decision-makers, researchers, and practitioners in the realm of cyber security. Ethical considerations are given due attention, as the integration of AI in threat detection raises important questions surrounding privacy, bias, and accountability. By analyzing current trajectories and emerging technologies, the article provides readers with a forward-looking perspective, helping them anticipate the evolving landscape of cyber security. In addition to exploring the technological facets, the paper emphasizes the importance of a collaborative approach and ongoing adaptation. The interconnected nature of threats in the digital realm necessitates a collective effort from industry experts, researchers, and policymakers. The review paper advocates for a holistic strategy that integrates AI technologies with human expertise to create a resilient defense against the ever-evolving landscape of cyber threats.

Metaheuristic and Data Mining Algorithms-based Feature Selection Approach for Anomaly Detection

In response to the evolving landscape of data security and the rising threat of anomalies in various domains, this study presents an innovative approach for anomaly detection in data streams and extends its application to financial network security. Our research initially focuses on identifying relevant correlation ratios for anomaly detection in the commercial data traffic of some companies listed during the 2014–2020 period. Utilising genetic algorithms (GA), gray wolf optimisation (GWO) for dimensionality reduction, we process 96 different financial streams. Subsequently, we employ the support vector machine (SVM) classifier to categorise companies into anomaly classes based on their financial data. The SVM classifier's initial performance, considering all financial ratios, falls short of our expectations. Our research thus provides a comprehensive approach to anomaly detection, showcasing the versatility and effectiveness of our methods in financial data stream analysis and network security. By combining the strengths of metaheuristic methods in data analysis and advanced deep learning techniques in network security, our work offers comprehensive solutions for anomaly detection in both domains. To enhance the classification accuracy and streamline the ratios, we introduce metaheuristic algorithms. GWO, in particular, stands out, with a fitness function of 0.2940 and an accuracy of 70.06% after 31 iterations. This algorithm successfully extracts 9 crucial financial ratios. These GWO-extracted ratios are then integrated into the SVM classifier, resulting in an anomaly detection model with outstanding accuracy, precision, error reduction, and efficiency, achieving 75.83%, 66.80%, 33.2%, and 80.3%, respectively.

Horizoning recent trends in the security of smart cities: Exploratory analysis using latent semantic analysis

The expeditious advancement and widespread implementation of intelligent urban infrastructure have yielded manifold advantages, albeit concurrently engendering novel security predicaments. Examining current patterns in the security of smart cities is paramount in comprehending nascent risks and formulating efficacious preventative measures. The present study suggests the utilization of Latent Semantic Analysis (LSA) as a means to scrutinize and reveal implicit semantic associations within a collection of textual materials pertaining to the security of smart cities. Through the process of gathering and pre-processing pertinent textual data, constructing a matrix that represents the frequency of terms within documents, and utilizing techniques that reduce the number of dimensions, Latent Semantic Analysis (LSA) has the ability to uncover concealed patterns and associations among concepts related to security. This study proposes five recommendations for future research that employ a topic modeling technique to investigate the often-explored subjects related to smart city security. This discovery provides additional evidence in favor of the proposition that a robust blockchain-driven framework is vital for the advancement of smart cities. Latent Semantic Analysis (LSA) offers important insights into the dynamic landscape of smart city security by employing several techniques such as pattern recognition, document or phrase clustering, and result visualization. Through the examination of patterns and developments, individuals in positions of political authority, urban planning, and security knowledge possess the ability to uphold their proficiency, render judicious choices substantiated by empirical data, and establish proactive strategies aimed at preserving the security, privacy, and sustainability of intelligent urban environments.

“I don't think we're there yet”: The practices and challenges of organisational learning from cyber security incidents

Learning from cyber incidents is crucial for organisations to enhance their cyber resilience and effectively respond to evolving threats. This study employs neo-institutional and organisational learning theories to examine how organisations learn from incidents and gain insights into the challenges they face. Drawing on qualitative research methods, interviews were conducted with 34 security practitioners from organisations operating in the UK spanning a range of industries. The findings highlight the importance of consciously evaluating learning practices and creating a culture of openness to hear about incidents from employees, customers and suppliers. Deciding which incidents to learn from, as well as who should participate in the learning process, emerged as critical considerations. Overcoming defensiveness and addressing systemic causes were recognised as barriers to effective learning. The study emphasises the need to assess the value and impact of identified lessons and to avoid superficial reviews that treat symptoms rather than underlying causes to improve resilience. While progress has been made in learning from incidents, further enhancements are needed. Practical recommendations have been proposed to suggest how organisations may gain valuable insights for maximising the benefits derived from incident learning. This research contributes to the existing knowledge on organisational learning and informs future studies exploring the social and political influences on the learning process. By considering the suggested recommendations, organisations may strengthen their cyber security, foster a culture of continuous improvement, and respond effectively to the dynamic cyber security landscape.

Picture Perfect: Standardizing and Safekeeping Clinical Photography in Plastic Surgery.

Abstract Plastic surgery relies heavily on clinical photography to document preoperative and postoperative changes, visualize surgical approaches, and evaluate outcomes. However, the contemporary landscape of plastic surgery photography faces challenges, including a lapse in standards due to the prevalence of smartphones, social media platforms, and security concerns related to data storage and cyberattacks. In this comprehensive review, the authors aim to provide plastic surgeons with practical guidelines for achieving standardized, high-quality clinical photography while navigating the evolving landscape of technology, security, and ethical considerations. We explore the security challenges associated with storing clinical photographs, emphasizing the legal obligations under the Health Insurance Portability and Accountability Act (HIPAA). We also discuss various storage options, including HIPAA-compliant cloud services, electronic medical records, and emerging technologies like blockchain and artificial intelligence. Level of Evidence: 5

The Rise and Fall of South Africa’s Intelligence Community during Apartheid

The author explores the context that contributed to the evolution of the South African Intelligence Community (SAIC) from political police to an independent security state during the apartheid, nondemocratic regime (1961–1994). It also assesses the circumstances that led to the demise of authoritarian rule and the reform of the intelligence apparatus. It finds that such factors as the security landscape, changes in leadership, and enabling legislation assisted the SAIC’s consolidation of power as political police, morphing it into an independent security state during that period. Subsequently, leadership, liberalization measures, scandals, and inquiries contributed to the demise of the apartheid intelligence apparatus and the slow emergence of a democratically inclined SAIC.

Strengthening Digital Security: Dynamic Attack Detection with LSTM, KNN, and Random Forest

Digital security is an ever-escalating concern in today's interconnected world, necessitating advanced intrusion detection systems. This research focuses on fortifying digital security through the integration of Long Short-Term Memory (LSTM), K-Nearest Neighbors (KNN), and Random Forest for dynamic attack detection. Leveraging a robust dataset, the models were subjected to rigorous evaluation, considering metrics such as accuracy, precision, recall, F1-score, and AUC-ROC. The LSTM model exhibited exceptional proficiency in capturing intricate sequential dependencies within network traffic, attaining a commendable accuracy of 99.11%. KNN, with its non-parametric adaptability, demonstrated resilience with a high accuracy of 99.23%. However, the Random Forest model emerged as the standout performer, boasting an accuracy of 99.63% and showcasing exceptional precision, recall, and F1-score metrics. Comparative analyses unveiled nuanced differences, guiding the selection of models based on specific security requirements. The AUC-ROC comparison reinforced the discriminative power of the models, with Random Forest consistently excelling. While all models excelled in true positive predictions, detailed scrutiny of confusion matrices offered insights into areas for refinement. In conclusion, the integration of LSTM, KNN, and Random Forest presents a robust and adaptive approach to dynamic attack detection. This research contributes valuable insights to the evolving landscape of digital security, emphasizing the significance of leveraging advanced machine learning techniques in constructing resilient defenses against cyber adversaries. The findings underscore the need for adaptive security solutions as the cyber threat landscape continues to evolve, with implications for practitioners, researchers, and policymakers in the field of cybersecurity.

Shrinking reconstruction space in the Gaza Strip: rebuilding after the 2021 and 2022 wars

ABSTRACT This paper presents a comprehensive analysis of the reconstruction efforts in the Gaza Strip following the 2021 and 2022 wars, placing these efforts in the context of previous reconstruction experiences after the 2008/09, 2012, and 2014 conflicts. Employing a mixed-methods approach that includes interviews, primary data analysis, and policy document reviews, the study uncovers the dynamics and challenges shaping the recent reconstruction processes. A key finding of this research is the marked slowdown and ineffectiveness of the post-2021 reconstruction, contrasting with earlier efforts. Unlike previous rounds where material flow restrictions due to the blockade were the predominant hindrance, the study identifies a critical shift in the recent context: a significant lack of funds emerged as the primary obstacle. This change reflects evolving political, economic, and security landscapes in the region, including donor fatigue and shifting international priorities. The paper explores continuities and discontinuities in the factors influencing reconstruction outcomes in Gaza, offering a nuanced understanding of how the changing context has impacted rebuilding efforts. It examines the implications of these findings for future reconstruction initiatives in Gaza and similar conflict-affected regions, providing insights into the complex interplay of financial, political, and logistical challenges in post-conflict reconstruction.

Nuclear security measures: A review of selected emerging technologies and strategies

This review article delves into the ever-evolving landscape of nuclear security, presenting an overview of emerging technologies and strategies that have the potential to enhance the safeguarding of nuclear materials, facilities, and information. With the global security environment continuously evolving, staying ahead of potential threats to nuclear assets is paramount. This article explores a wide range of cutting-edge advancements that could revolutionize nuclear security efforts, offering a balanced assessment of their benefits, and challenges. To facilitate an organized presentation and analysis, the extracted articles were categorized into distinct sections based on the identified key topics. These categories included "advanced surveillance and monitoring systems," "cybersecurity and digital protection," "non-destructive evaluation techniques," "physical security enhancements," "nuclear material characterization nuclear forensics," and "international collaboration and policy frameworks." Each section was dedicated to exploring the advancements, challenges, and implications specific to the respective technology or strategy. By offering this synthesis, the article aims to serve as a strategic resource for policymakers, security professionals, and researchers, underlining the pivotal role of technology in safeguarding against nuclear threats in an interconnected world.

СТРАТЕГІЯ НАЦІОНАЛЬНОЇ БЕЗПЕКИ НІМЕЧЧИНИ В УМОВАХ ШИРОКОМАСШТАБНОГО ВТОРГНЕННЯ РФ В УКРАЇНУ

The article analyses the main mechanisms of developing Germany’s security strategy in the context of key issues and prospective threats to European security in the 21st century. By examining changes in the overall security landscape and contemporary challenges to the global order, it analyzes how countries’ military security strategies shape approaches to defence and protection over a certain historical period. On the other hand, a detailed analysis of the prerequisites and course of military conflicts at the end of the 20th and the first decades of the 21st century allows the conclusion that those states capable of swiftly and effectively altering their approaches to security are able to resist external threats efficiently. To achieve this, a state must possess and continuously refine all doctrinal documents related to national defence matters. The German doctrinal documents regarding the definition of national security fundamentals are specifically studied. This is pertinent for understanding shifts in the views of the senior military and political leadership on how to adequately ensure the state’s integrity from external and internal threats. The article asserts that Germany’s leadership pays significant attention to general security issues, including purely military aspects. Moreover, such shifts in perspectives occur under changes in the global military-political environment, not only in Europe but worldwide. At the same time, the article examines the main sections of the latest National Security Strategy of Germany, which was approved in 2023. According to this document, one of Germany’s primary tasks today is direct participation in shaping a free international order committed to international law, the United Nations Charter, and sovereign equality of states. Therefore, emphasis is placed on the fact that such an approach to national security issues and Germany’s NATO membership are bases for providing significant military-technical assistance to Ukraine in countering Russian aggression.

Enhancing IoT Security Development and Evaluation of a Predictive Machine Learning Model for Attack Detection

The research aims to develop and evaluate a model for Internet of Things (IoT) attack identification utilizing IoT data from the Global Cyber Alliance’s (GCA) Automated IoT Defense Ecosystem (AIDE). In the growing landscape of IoT security, the need for enhanced predictive solutions is vital. Our research leverages an enormous dataset, overall historical data from various IoT devices and network interactions, to develop a model to identify potential security threats. The key to our methodology concerns exploratory data analysis, which is focused on understanding complex patterns and anomalies in IoT data. This step is vital for feature engineering, where we meticulously select and transform data attributes to advance the model’s predictive strength. The data pre-processing stage further improves the dataset, ensuring the model training and testing on high-quality, relevant data. Model development is a composite process in this research. We tried out a few machine-learning algorithms, finally selecting the one that exhibited outstanding performance in preliminary tests. The chosen model endured strict training, with a basis on balancing accuracy and validity to effectively predict IoT attacks in various scenarios. The evaluation of our model is as durable as its development. We utilized a range of metrics, including accuracy, precision, recall, and F1 score, to evaluate the model’s behavior overall. The results show that our model not only attains high accuracy but also maintains a notable level of precision in predicting IoT attacks, which is crucial in minimizing false positives. In conclusion, our research contributes to the enhancement of IoT security by providing a very effective predictive model for IoT attack detection.

Balancing security and user experience in the evolving digital landscape

In today's digital landscape, the prevalence of automated threats poses a significant challenge to online security. This study addresses the evolving landscape of online security by investigating next-generation CAPTCHAs, which aim to strike a balance between heightened security and an enhanced user experience. The relentless arms race between automated threats and online security necessitates the development of innovative solutions capable of countering advanced technological threats while ensuring a seamless user experience. The primary objective of this research is to explore and evaluate the effectiveness the presented approach in enhancing online security and user satisfaction. We examine how the integration of behavioral biometrics, gamification techniques, and supplementary tools such as device fingerprinting, geolocation, and browser attributes can contribute to a more robust and user-friendly CAPTCHA experience. Our study employs a comprehensive methodology, including a thorough literature review, and data collection from diverse sources. We evaluate the authenticity of these advanced systems, taking into account their ability to adjust to ever-changing digital environments. However, challenges persist in striking the right balance between security and convenience, addressing privacy concerns, and adapting to evolving digital landscapes. These findings validate the critical importance of ongoing research and innovation technology to safeguard online platforms effectively.

HOW THE RUSSIAN-UKRAINIAN WAR IS TRANSFORMING INTERNATIONAL SYSTEM AND INTERNATIONAL ORDER

The article examines the impact of the Russian-Ukrainian war on international system and international order. It assesses the former through the lenses of realism and neorealism, while approaching the latter within constructivist and English School approaches. Structural and normative changes in international politics are examined. The war has been revealing and transforming the balance of power on a global and regional levels. By doing so, it is enhancing structural changes in the international system. The article explores the scope of these changes. On the normative side, the conflict challenges and potentially alters the rule-based international order, affecting established norms and institutions. This war not only affects Ukraine but also has broader implications, contributing to the ideological standoff and security paradigm shifts globally. The article underscores the interplay between structural changes and normative shifts, illustrating how these dynamics are interconnected and mutually reinforcing. This comprehensive analysis provides insights into the evolving landscape of international relations and security, emphasizing the far-reaching consequences of the Russian-Ukrainian war on both international system and order.

National and Civil Security in Kosovo – Premises, Components, Challenges, and Risks

This paper explores the complex landscape of national and civil security in Kosovo, focusing on the premises, main components, challenges, and risks associated with establishing a secure and stable environment in Europe’s youngest nation. Kosovo’s journey towards statehood and security is hindered by a myriad of factors including political instability, economic underdevelopment, and the lingering effects of ethnic tensions. The research delves into the intricate dynamics between national security measures and human security needs, emphasizing the impact of political instability on the broader security framework. By examining the roles of various security institutions such as the Kosovo Security Force and the Kosovo Police and assessing their effectiveness in the face of external threats, particularly from Serbia and its allies, this study highlights the ongoing struggles and the necessary reforms in Kosovo’s security sector. Additionally, the paper discusses the influence of international actors and frameworks, including NATO and the EU, in shaping Kosovo’s security policies and practices. Through a comprehensive analysis, this study calls for a concerted effort from both local leadership and international partners to enhance Kosovo’s security architecture, ensuring a stable, secure, and prosperous future for its citizens. The recommendations provided aim to fortify Kosovo’s institutional capabilities and address the socio-political challenges that impede its path to a secure statehood. Key words: Kosovo, National Security, Civil Security, Political Instability, Security Institutions, Human Security, NATO, EU.

A Study on Evaluation and Implementation of Indian Social Security Programs and Initiatives in India

This study critically assesses the implementation of Indian Social Security Programs, employing a comprehensive research design that integrates qualitative and quantitative methodologies. The examination encompasses diverse factors such as financial inclusion, healthcare accessibility, education, and support for vulnerable groups. Findings offer a nuanced understanding of strengths, challenges, and areas for improvement in India’s social security landscape, focusing on programs like Pradhan Mantri Jan Dhan Yojana, Atal Pension Yojana, and National Health Mission. The research’s practical implications extend to policymakers, administrators, and advocacy groups, providing evidence-based recommendations to refine and strengthen social security interventions. Addressing gaps in awareness, administrative efficiency, and inclusivity, the study guides practical interventions for enhanced program efficacy. This research stands out for its comprehensive evaluation of multiple social security dimensions, providing a holistic perspective on India’s initiatives. Synthesizing diverse data sources and incorporating beneficiaries’ lived experiences, contributes to the existing knowledge on social security implementation. The findings form a foundation for evidence-based policy-making, promoting a more inclusive, responsive, and sustainable social security framework in India. Additionally, the study contributes valuable insights to the global discourse on social welfare, illuminating challenges and opportunities in implementing social security programs amid a rapidly evolving socio-economic landscape.

India's Strategic Considerations With Russia In The Post-Russia-Ukraine War Era

This article examines India's strategic considerations in the aftermath of the Russia crisis, explicitly focusing on India-Russia relations. The article analyses the factors influencing India's approach towards Russia, particularly in defense cooperation while considering the implications of China's rising influence on India's strategic calculations. By conducting a case study of India-Russia relations, the paper investigates the dynamics of defense collaboration, the significance of Russia as a defense partner for India, and the evolving regional security landscape shaped by China's ascent. The research provides insights into India's strategic alignments and decision-making processes in the post-Russia crisis era, considering Russia's new foreign policy emphasizing India and China. Furthermore, the paper examines the encircling impact of China's rising influence in South Asia on India, highlighting India's abstention in the UN General Assembly resolution condemning Russia's invasion of Ukraine as a reflection of its difficult position amidst these geopolitical developments. The findings of this research contribute to the understanding of India's strategic responses and decision-making frameworks in the context of shifting regional dynamics, considering the implications of Russia's foreign policy approach and China's growing power.

Relevance of Kautilya’s Arthashastra concerning Contemporary Hybrid Warfare

The concept of hybrid warfare, known by the increasingly indistinct and blurred lines between conventional and unconventional tactics, has surfaced as a serious threat in the contemporary security landscape. Since the threats have been evolving rapidly, it becomes paramount for nations to have their countermeasures ready. This research investigates the ability of the ancient Indian treatise, Arthashastra, to suffice as a countermeasure to hybrid threats. This paper highlights not only the analysis of the articulation of warfare strategies but also the non-military strategies traced in the Arthashastra and tests its potential further in light of the 21st century’s complexities and hybrid warfare. The analysis tries to contribute to the ongoing discourse on hybrid warfare by exploring a historical text and trying to establish a link between ancient wisdom and contemporary security challenges, offering insights to tackle the complexities of hybrid warfare.

Circular economy-based integrated farming system for indigenous chicken: Fostering food security and sustainability

Addressing the global challenge of food security necessitates innovative and sustainable approaches capable of meeting the demands of a growing population while ensuring a sufficient and nutritious food supply. This study explores circular economy-based integrated farming systems for indigenous chicken, focusing on the principles of circular economy, TBL approach and sustainable agriculture to enhance the food security landscape. To comprehensively assess the status of the indigenous chicken sector, a detailed analysis of farm operations is conducted. Qualitative data collection and a system dynamics approach provided valuable insights into the intricate dynamics of the system. Leveraging simulation and modelling, interactions and behaviours within the sub-systems are unveiled, ultimately leading to the integration of forward and reverse value chain linkages. The Indigenous Chicken-based Integrated Farming System value chain, developed because of this study, offers a transformative model for sustainable food production. This model provides clear insights into the dynamics of indigenous chicken farming, highlighting the importance of circular economy principles. It also aids in understanding the impact of varying parameters, such as egg production and parent chicken population, on the system's behavior. Moreover, the research identifies exponential growth patterns in critical components, shedding light on the system's scalability potential. Additionally, it emphasizes the significance of integrating forward and reverse linkages in achieving sustainability and minimizing waste throughout the value chain.