Role Of Cybersecurity Research Articles

The Role of Cyber Security in the Global Century in the Twenty-First Century

This study focuses on the concept of cybersecurity and its role in global security and the extent of changes that occurred in the concept of global security, especially in the twenty-first century and the competition between major powers for supremacy in cyberspace (the United States of America, China) and aims to demonstrate the importance of having an infrastructure in space This study concludes that cyberspace has become the most important field for these countries and the appropriate environment for settling inter-conflicts between the major powers.

SCEMA: An SDN-Oriented Cost-Effective Edge-Based MTD Approach

Protecting large-scale networks, especially Software-Defined Networks (SDNs), against distributed attacks in a cost-effective manner plays a prominent role in cybersecurity. One of the pervasive approaches to plug security holes and prevent vulnerabilities from being exploited is Moving Target Defense (MTD), which can be efficiently implemented in SDN as it needs comprehensive and proactive network monitoring. The critical key in MTD is to shuffle the least number of hosts with an acceptable security impact and keep the shuffling frequency low. In this paper, we have proposed an SDN-oriented Cost-effective Edge-based MTD Approach (SCEMA) to mitigate Distributed Denial of Service (DDoS) attacks at a lower cost by shuffling an optimized set of hosts that have the highest number of connections to the critical servers. These connections are named edges from a graph-theoretical point of view. We have proposed a three-layer mathematical model for the network that can easily calculate the attack cost. We have also designed a system based on SCEMA and simulated it in Mininet. The results show that SCEMA has lower complexity than the previous related MTD field with acceptable performance.

Cyber attack detection with QR code images using lightweight deep learning models

As information technologies evolve rapidly, servers are being attacked by cyberattacks due to their high values such as cloud, IoT, mobile and desktop applications. Therefore, cyber-attacks have caused great concern in many areas. Although intrusion detection systems play an important role in cyber security, it has become an important data analysis object because it consists of complex system operating data. Traditional intrusion detection systems detect cyber attacks by recording previously detected attacks and comparing them with new attacks or looking for system anomalies. Intrusion detection data is huge, attack types are diverse, and due to the development of hacking skills, traditional detection methods are inefficient. In recent years, many intrusion detection mechanisms, especially machine learning and deep learning, have been proposed to improve traditional intrusion detection technology. In this study, we propose a multi-objective optimization-based hybrid method that enables the use of the most convenient features of light deep learning models in detecting cyber attacks. First, QR code images of bulky data with multiple classes were created. Then, QR code images were trained using MobileNetV2 and ShuffleNet CNN models. Deep CNN models and features of the trained images were extracted, and Harris Hawk Optimization (HHO) algorithm was used to select the most effective features for classification purposes. As a result, as a result of the classification of the selected features with the proposed hybrid model HHO, attack types were detected with an accuracy rate of 95.89%, and it provided superior performance compared to CNN models.

DIGITAL ERA IN CYBER CRIME AND SECURITY

Cyber Security is a potential activity by which information and other communication and other communication system are protected from or defended against the unauthorized use or modification or exploitation or even theft .The types of cybercrime are Identity theft, Psychological tricks ,Social media frauds and mobile application frauds ,the most frequently heard in banking frauds . There are many causes of cyber crimes like cyber hoaxes, negligence, revenge or motivation, poor law enforcing bodies and cyber crime committed from publicity or recognition , social media player important role in cyber security. There are many act on Cyber Security like IT Act 2000(Cyber Stalking ) and many more.

A CRITICAL EXAMINATION OF SHIELDING THE CYBERSPACE: A REVIEW ON THE ROLE OF AI IN CYBER SECURITY

This review focuses on the critical analysis of AI’s role in cybersecurity to investigate the issues in the cybersecurity space. By utilizing synchronous and scattered sources on the topic in question, the opinion paper focuses capacity on AI-embedded technologies to enhance cybersecurity and discourage cyber-attacks making critical infrastructure impenetrable by malicious persons [1]. The paper is concerned with applying AI solutions paired with research documenting theoretical outcomes obtained from academic sources, field reports, and practical case examples. Suggestions, pros, and cons of those solutions, as well as the implications, are presented. More importantly, the paper does not only touch on the ethical and policy aspects of AI application in cyber security, but there is also a need for a detailed approach to cyber security, an approach that unites technological innovation to privacy, transparency, and accountability [1]. In contrast, the article brings attention to future developments and innovations in AI-based cybersecurity, which is a crucial need of the hour. AI evolution is seen in different aspects, such as designing complex Machine Learning algorithms till the inclusion of AI in Security Operations Centers (SOCs) and Threat Intelligence Platforms, which have prepared reliable weapons for cyber defense systems.

Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges

Cyberattacks are becoming more and more intense in the banking industry (Ryzhkova et al. 2020). Banking industry is trying to adopt artificial intelligence to create cyber defence system so that the unauthorized access and cyber attacks would be minimized. Banks in Qatar acknowledge the threat of cybercrimes and the role of cybersecurity in sustainable growth. Meanwhile, the banking industry is experiencing a major technological disruption. It becomes important to understand the implications of such technologies as artificial intelligence (AI) on the cybersecurity of banks. The present paper aims to explore the impacts of AI on the cybersecurity of banks in Qatar. A thematic analysis of interviews of 9 experts in the banking industry of Qatar was conducted. A qualitative thematic analysis was conducted using NVIVO 12 tool. Four key themes were identified: (1) AI is a major tool for enhancing the cybersecurity of banks in Qatar; (2) banks face challenges in using AI for improving cybersecurity; (3) AI can be used destructively and thus poses a threat to cybersecurity in banks of Qatar; (4) employed AI-based tools have vulnerabilities that can be exploited. Overall, Qatar banks can be expected to face new challenges in the future, due to changes in regulatory frameworks and increasing availability of AI-powered malware.

Roles and Challenges of AI-Based Cybersecurity: A Case Study

Nowadays, organizations face complex cyber-attacks that are difficult to counter with traditional protections. Therefore, many modern organizations tend to use AI-based cybersecurity systems to secure their assets and infrastructure and to reduce the level of potential risks.
 Because of the lack of clarity of the AI roles in cybersecurity and the ambiguity of the related challenges, this study aims to explore the most prominent roles of AI-based cybersecurity related to information security in the prevention phase, the detection phase and the response phase. The study also aims to determine the most prominent challenges facing AI-based cybersecurity.
 To achieve the goals of this study, we adopt a case-study methodology that origins from the general framework which is information security and ends with the specific framework which is AI-based cybersecurity. After designing a matrix to analyze the case study, the study concludes nine important roles for AI-based cybersecurity distributed over the three phases. Three roles are in the prevention phase, which are automated assessment of security vulnerabilities, awareness and training and authentication. Two roles are in the detection phase; namely, detection of intrusion and security breaches and detection of spams and phishing and four rules are in the response stage, which are analyzing malware, automating routine tasks, deploying traps and topple attackers and isolating important assets.
 The study also identifies eight elements that represent the most prominent challenges facing AI-based cybersecurity: regulations and principles, trust, accountability, privacy, bias, training datasets, human resources and financial costs. In conclusion, the study presents a set of recommendations drawn from the results.

Artificial Intelligence as a Support Tool to Cybersecurity Activities

The present study is based on the analysis of the concepts of Cybersecurity and Artificial Intelligence, focusing on how both relate to each other. The COVID-19 pandemic and the fact that the world was forced into confinement had a huge impact on the increase of cyber-attacks and the birth of new threats. Currently, Cybersecurity is becoming an extremely complicated task, as we can no longer think of blocking an attack only by resorting to humans. The advanced and automated ways in which attacks have been developing mean that the task of defence must also be automated. Artificial Intelligence, due to its particularities, meets this need. This technology has been playing an increasingly important role in Cybersecurity, even though we may still consider it to be at an early stage

Introduction to The Data Mining Techniques in Cybersecurity

As a result of the evolution of the Internet and the massive amount of data that is transmitted every second, as well as the methods for protecting and preserving it and distinguishing those who are authorized to view it, the role of cyber security has evolved to provide the best protection for information over the network. In this paper, the researcher discusses the role of data mining methods in cyber security. Data mining has several uses in security, including national security (for example, surveillance) and cyber security (e.g., virus detection). Attacks against buildings and the destruction of key infrastructure, such as power grids and telecommunications networks, are examples of national security concerns. Cybersecurity is concerned with safeguarding computer and network systems from harmful malware such as Trojan horses and viruses. In addition, data mining is being used to deliver solutions such as intrusion detection and auditing.

The role of cybersecurity and policy awareness in shifting employee compliance attitudes: Building supply chain capabilities

This paper investigates the role of general cybersecurity and cybersecurity policy awareness in enhancing supply chain cyber resilience reactive capabilities. Theorizing from the Protection Motivation Theory, 200 Small and Medium Enterprises (SMEs) were contacted to understand their perception of cybersecurity and policy awareness in affecting their overall cybersecurity hygiene. Data collection was carried out using a questionnaire survey and analysed via Partial Least Squares-based Structural Equation Modelling to validate the research framework. Results of analysis outlined the importance of general cybersecurity and policy awareness in shifting employees’ compliance attitude towards enhancing supply chain reactive capability. Using a mixed-method approach, post-survey interviews were further conducted with practitioners in SMEs to understand the study findings. The implications outlined in this study emphasises the importance of prioritising preventive measures and proper employee cyber hygiene to address the risk and loss following a cyber-attack. Key supply chain operational areas in SMEs are still largely supported by the human workforce serving as its backbone. An unwarranted attack could cause adverse business impacts. Thus, practitioners and SMEs would be alerted to the critical need for a robust security posture and that SMEs’ need of the hour lies at the core of its policy and employee cybersecurity hygiene.

Ransomware Incident Preparations With Ethical Considerations and Command System Framework Proposal

Concerns with cyber-attacks in the form of ransomware are on the mind of many executives and leadership staff in all industries. Inaction is not an option, and approaching the topic with real, honest, and hard discussions will be valuable ahead of such a possible devastating experience. This research note aims to bring thoughtfulness to the topics of ethics in the role of cybersecurity when dealing with ransomware events. Additionally, a proposed set of non-technical recovery preparation tasks are outlined to help organizations bring about cohesiveness and planning for dealing with the real potential of a ransomware event. Constraints from many factors come into focus during preparations for ransomware, and a method to categorize them is detailed. Finally, the use of Incident Command Systems is well known and documented in emergency management, and a proposed model for integrating this process for ransomware episodes is sketched.

Principle of relevance as an information indicator of quality of administrative and legal standards in modern cyberspace

Administrative and legal norms in modern cyberspace are outlined. The general characteristic of the state of professional and personnel level of intellectual potential in the field of nanotechnologies is given. At the same time, it was emphasized that in order to prevent the spread of COVID-19, the world is forced to rapidly reformat into a neural network virtualization mode as a phenomenal digital communication in public relations. An algorithm of actions as the quality of administrative and legal control and coordination of the subjects of cyber-infrastructure support of state and non-state forms of ownership has been formed. It is stated that the human evolution in the conditions of formation and further progress of the information society is one of the fundamental factors of the period of social transformations. It is noted that the legislator should pay attention to the qualitative formation of the national qualifications limit. It is envisaged that the principles of its creation and implementation should be the relevant national and European educational standards and principles of relevance as information indicators of educational quality. In addition, the need to take into account current needs and interests in the labor market on the competence of employees, which creates an effective interaction of the education sector with the labor market. The crucial role of cooperation with the European Neural Network of National Centers for Academic Mobility and Recognition is emphasized. It is determined that all these trends are carried out in order to integrate the domestic higher education system into the European and world educational space. The role of cybersecurity in the neural network cryptosystem of state formation is emphasized, namely the risks and measures related to the need to protect personal data of consumers, preservation of information in telecommunications systems, preservation of confidential information and trade secrets.

A Cost-Sensitive Deep Learning-Based Approach for Network Traffic Classification

Network traffic classification (NTC) plays an important role in cyber security and network performance, for example in intrusion detection and facilitating a higher quality of service. However, due to the unbalanced nature of traffic datasets, NTC can be extremely challenging and poor management can degrade classification performance. While existing NTC methods seek to re-balance data distribution through resampling strategies, such approaches are known to suffer from information loss, overfitting, and increased model complexity. To address these challenges, we propose a new cost-sensitive deep learning approach to increase the robustness of deep learning classifiers against the imbalanced class problem in NTC. First, the dataset is divided into different partitions, and a cost matrix is created for each partition by considering the data distribution. Then, the costs are applied to the cost function layer to penalize classification errors. In our approach, costs are diverse in each type of misclassification because the cost matrix is specifically generated for each partition. To determine its utility, we implement the proposed cost-sensitive learning method in two deep learning classifiers, namely: stacked autoencoder and convolution neural networks. Our experiments on the ISCX VPN-nonVPN dataset show that the proposed approach can obtain higher classification performance on low-frequency classes, in comparison to three other NTC methods.

Towards time evolved malware identification using two-head neural network

Deep learning-based malware detection plays an important role in cybersecurity in recent years. However, with the increasing complexity of malware and the continuous development of anti-detection techniques, a lot of malicious programs evolve over time. As a result, the deep learning-based methods may fail to recognize these time evolved malware samples, which poses a critical challenge to deploy the deep learning models in practice. In this paper, we first implement two well-known deep learning-based malware detection models: MalConv and TextCNN. From our experiments that divide the dataset according to the timestamp information for model training and testing, we found the detection performance of the two models both decline obviously when they process the time evolved malware. To address this problem, we propose an anomaly detection approach based on two-head neural network. This method can identify the time evolved samples. These samples would make the previous trained deep learning models misclassified. The experiments show that the malware detection accuracies can be improved by 8.62% for MalConv and 13.12% for TextCNN after the identified samples are filtered. This indicates that our method could effectively improve the usability of the pre-trained models on processing the new data. Moreover, the experimental results are well studied.

Research Trends, Challenges, and Emerging Topics in Digital Forensics: A Review of Reviews

Due to its critical role in cybersecurity, digital forensics has received significant attention from researchers and practitioners alike. The ever increasing sophistication of modern cyberattacks is directly related to the complexity of evidence acquisition, which often requires the use of several technologies. To date, researchers have presented many surveys and reviews on the field. However, such articles focused on the advances of each particular domain of digital forensics individually. Therefore, while each of these surveys facilitates researchers and practitioners to keep up with the latest advances in a particular domain of digital forensics, the global perspective is missing. Aiming to fill this gap, we performed a qualitative review of all the relevant reviews in the field of digital forensics, determined the main topics on digital forensics topics and identified their main challenges. Despite the diversity of topics and methods, there are several common problems that are faced by almost all of them, with most of them residing in evidence acquisition and pre-processing due to counter analysis methods and difficulties of collecting data from devices, the cloud etc. Beyond pure technical issues, our study highlights procedural issues in terms of readiness, reporting and presentation, as well as ethics, highlighting the European perspective which is traditionally stricter in terms of privacy. Our extensive analysis paves the way for closer collaboration among researcher and practitioners among different topics of digital forensics.

Self-Supervised Vision Transformers for Malware Detection

Malware detection plays a crucial role in cyber-security with the increase in malware growth and advancements in cyber-attacks. Previously unseen malware which is not determined by security vendors are often used in these attacks and it is becoming inevitable to find a solution that can self-learn from unlabeled sample data. This paper presents SHERLOCK, a self-supervision based deep learning model to detect malware based on the Vision Transformer (ViT) architecture. SHERLOCK is a novel malware detection method which learns unique features to differentiate malware from benign programs with the use of image-based binary representation. Experimental results using 1.2 million Android applications across a hierarchy of 47 types and 696 families, shows that self-supervised learning can achieve an accuracy of 97% for the binary classification of malware which is higher than existing state-of-the-art techniques. Our proposed model is also able to outperform state-of-the-art techniques for multi-class malware classification of types and family with macro-F1 score of.497 and.491 respectively.

Cyber security as an innovative protection in the political space of Ukraine

The article focuses on the values of the role of cybersecurity in the modern information society. To develop an effective system of interaction in the information space, there is a need to form boundaries of protection for users. The system of protection that exists in society is aimed at resolving the contradictions that arise at the level of actual confrontation and significant influence on political processes with clearly defined subjects of political activity. For the modern world, the subjects of global governance pay serious attention to the level of security of the management system in individual countries and regions, which indicates the effectiveness or imbalance in the management system. Also, the role of such an entity at the supranational level of the management system. Therefore, the chosen topic is quite relevant for the global process of interaction and taking into account the views of individual regions. In addition, effective protection of cyberspace will help reduce the level of manipulation by political actors, which will help increase the level of political culture among politicians and the level of political awareness among ordinary citizens. The article analyzes modern scientific approaches to understanding the concept of cybersecurity and cybersecurity, provides a generalized description of these concepts, identifies modern forms of security in cyberspace, analyzes the state of cybersecurity in the Ukrainian information space and defines its status as a subject of global interaction in the information space. In the political process, an integral element of interaction is the information space, as the modern platform for public relations between policy actors has been reformatted in the latest ways, and therefore the mechanisms of influencing citizens become innovative and demonstrate uncertain response from society and possible ways of political development. events. As a result, a number of mechanisms need to be put in place to protect all cyberspace users who engage in public communication on important policy issues.

Privacy challenges in cyber security against cybercrime in digital forensic. A systematic literature review in Pakistan.

Cybercrime is a criminal activity that either target or uses a computer network or a network device. IOT become the biggest domain in these days.it is difficult to adopt digital forensics tools in IoT but somehow digital forensics play an important role in cyber security of IoT. Privacy and security challenges are increased day by day in digital forensics. Cybercrime in cyber security is increased day by day in digital forensics. Privacy and security are relate with each other but difference is that privacy relate to any right you have to control your personal information and how it’s used. Lots of work has been done in security issue but less focus on privacy. In the recent year, privacy in cyber security is the biggest challenge against cybercrime in digital forensics. To overcome these challenges of privacy in cyber security we must have deep knowledge which threats and attacks are harmful of our network.in this article we discuss the current privacy threats and attack for cybercrime in digital forensics with the deep knowledge and proposed classification matrix and also define proposed system which control threats and attacks. To the best of our knowledge there is no survey on privacy challenges in cyber security against cybercrime in digital forensics.

Norm Entrepreneurship in Global Cybersecurity

New technologies create new challenges for global security that leave even the most militarily powerful countries vulnerable to attack. Countries are gearing up for electronic warfare and, in this realm, the old rules of international conflict either do not apply or have not been developed. Governments have yet to find stable policy solutions to match potential cyber threats. The challenge then is to establish new global norms concerning acceptable behavior in cyberspace. This article analyzes the attempts to construct global cybersecurity norms. It differs from much of the existing literature on norm‐construction since it moves beyond the interstate level to examine subnational groups and private sector actors that function as norm entrepreneurs in this policy area. The article posits that while nation states remain central, nonstate actors are playing an increasingly important role in cybersecurity norm‐building, supplementing state action, and, to some degree, compensating for state inaction when cooperation reaches an impasse.Related ArticlesGlen, Carol M. 2014. “Internet Governance: Territorializing Cyberspace?” Politics & Policy 42 (5): 635‐657. https://doi.org/10.1111/polp.12093Hellmeier, Sebastian. 2016. “The Dictator's Digital Toolkit: Explaining Variation in Internet Filtering in Authoritarian Regimes.” Politics & Policy 44 (6): 1158‐1191. https://doi.org/10.1111/polp.12189Zeng, Jinghan, Tim Stevens, and Yaru Chen. 2017. “China's Solution to Global Cyber Governance: Unpacking the Domestic Discourse of ‘Internet Sovereignty.’” Politics & Policy 45 (3): 432‐464. https://doi.org/10.1111/polp.12202

Caregivers' Role in Cybersecurity for Aging Information Technology Users with Intellectual Disabilities.

Information technology (IT) users with intellectual disabilities (ID) are likely to experience online privacy violations without adequate support from their caregivers. Given that aging users face additional challenges when using IT than their younger counterparts, the goal of this exploratory study is to investigate caregivers' strategies and barriers for helping to protect the privacy of aging IT users with ID. Six caregivers (four paid caregivers, two family members) of aging users with ID completed a series of six focus groups about their experiences assisting the people they support with using IT, including their strategies and barriers for helping to protect these users' privacy. Participants were also asked about their own attitudes and experiences related to online privacy and information security. Based on our inductive thematic analysis of the qualitative data, participants used three main strategies to help protect the privacy of aging users with ID: (1) restricting access to personal information, (2) limiting disclosure of personal details, and (3) providing just-in-time instruction and feedback. We also identified four key barriers to privacy protection: (1) limited awareness and knowledge about information security, (2) balancing privacy and autonomy, (3) maintaining professional boundaries, and (4) residential care services' policies. Inclusive and transdisciplinary research is needed to address the elevated privacy and security risks for aging IT users with ID, and provide caregivers with training on how to support this population to use IT safely. Technology developers should create solutions to decrease aging users with ID's dependence on caregivers for privacy protection.