Security Breaches Research Articles

Integrated Shared Random Key Agreement Protocol for Wireless Sensor Network

The secured data transmission in Wireless Sensor Network (WSN) relies on effective key generation and secured sharing. The generated key must be random to enhance data confidentiality. The processes associated with the security in WSN must be designed at reduced computing time and communication cost. Our research work aims to design a novel lightweight key-sharing protocol that is needed for ensuring data confidentiality. The protocol must meet the constraints of WSN by being lightweight and consuming less energy. Security breaches in WSNs occur due to insecure keys. This can be overcome by generating shared keys which are generated once using the dynamic features of Sensor Nodes (SNs) when the Cluster Heads (CHs) are selected. In this research work, we have generated the Master Shared Key (MSK) at the transmitter node by forming a Galois Ring (GR) using WSN parameters and derived the Shared Random Key (SRK) using matched positions of exchanged Random Sequences (RSs). It is protected using a Physically Unclonable Function (PUF). The novelty lies in the SRK generation from MSK which is chosen at random from the polynomials generated during the formation of GR. The MSK is securely shared with the receiver node by encrypting using a Preloaded Key (PK). After this exchange, the key for encryption and decryption is derived by the transmitter and the receiver by exchanging RSs. The SRK is then encrypted using a key which is a unique fingerprint of the SN generated using PUF and stored in the SNs and the CHs to prevent node capture attack that occurs in WSN. Our proposed Shared Random Key Agreement Protocol (SRKAP) is comparable to the Localized Encryption and Authentication Protocol (LEAP) and performs better compared to the Elliptic Curve Diffie Hellman (ECDH) algorithm

Intrusion-tolerant sink configuration: A key to prolonged lifetime in wireless sensor networks

This study investigates the pivotal role of sink configuration in enhancing the lifetime of Wireless Sensor Networks (WSNs). A comparative analysis between configurations employing 2 sinks and 3 sinks reveals that the latter significantly outperforms the former in terms of network longevity. The study delves into the integration of an intrusion-aware protocol, providing resilience during security breaches. This protocol stabilizes network lifetime amidst intrusion attacks, which is crucial for maintaining system efficiency. This work introduces a novel machine learning model tailored for WSNs, exhibiting superior accuracy on a WSN-specific dataset. Through these combined efforts, it presents a comprehensive approach to improving WSN lifetime, encompassing sink configuration optimization, intrusion tolerance, and innovative machine learning techniques.

Securing Pervasive Computing Networks: Enhancing Network Security via Network Virtualization in Wireless Communications Infrastructure

The seamless integration of technology for computing into everyday items and environments is known as pervasive computing. To protect against cyber threats and vulnerabilities, robust security mechanisms are necessary. Conventional security measures, including gateways and the use of encryption, may not be sufficient to address the unique challenges encountered in ubiquitous computing systems. But these techniques are still vital. In addition to the variety of devices, resource limitations, mobility needs, and the possibility of large-scale distributed attacks, these obstacles also include the potential for attack. Network virtualization, that abstracts and separates network facilities and functions, is a promising way to increasing security in pervasive computing deployments: it abstracts and isolates network resources and processes. Wireless communication play a significant part in the development of a digital infrastructure that is both resilient and trustworthy. The processes of dynamic resource allocation, isolation, and management of network bandwidth are made possible through the utilization of virtualization, leads to the proposal of Secure Wireless Virtual Resource Allocation and Authentication Algorithm(SWVRA3) to make the abstraction of the network's physical resources into virtualized entities By using network virtualization, pervasive computing applications and services can be secured with logically segregated virtual networks. The cross-contamination and security breaches can be reduced by this separation. Furthermore, flexible configuration, dynamic allocation of resources, and centralized virtual control are allowed by network visualization that improves threat incidence response, enforcement of policies, and security surveillance.

ИНФОРМАЦИОННЫЕ СИСТЕМЫ, ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ КАК ИНСТРУМЕНТ УПРАВЛЕНИЯ КОМПАНИЕЙ

The use of information systems and information technologies is critical for modern companies. They allow them to increase efficiency, improve the quality of products and services, as well as communications with customers and within the company. However, the use of information technology also poses risks, including data loss and security breaches, and companies must be prepared to manage these risks. The authors explore the possibilities of doing business using information systems and information technologies. The introduction of information systems and information technologies becomes the main factor in the quality of the company’s management system.

Feeling safe online and experience with cyber incidents among university students

The field of education increasingly depends on technology to manage extensive volumes of information, underscoring the paramount importance of cybersecurity. Security breaches are rising within the education sector, necessitating the preemptive improvement of awareness. Within this article, we will delve into the findings of a survey that inquired with university students about their perceptions of safety in the digital realm and their encounters with cybersecurity events. The outcomes shed light on the fact that while a majority of students do perceive online safety, a noteworthy portion has already encountered security incidents.

Distributed private preserving learning based chaotic encryption framework for cognitive healthcare IoT systems

In the field of cognitive healthcare Internet of Things (CH-IoT), there is a strong demand for reliable and minimally intrusive smart gadgets that consistently acquire, analyse, and obtain the confidential health details of the individual. In fact, CH-IoT is empowered with artificial intelligence (AI) to transmute a fewer operational inputs into actionable, intelligent actions through the digitization of medical healthcare data. However, these systems consume more network complexity, interaction, and overhead costs, while inducing a blend of susceptibility and confidentiality issues. In support of this complexity, these cognitive systems need centralised data collection and to be gathered and analysed, which affects scalability issues and adds fuel to privacy and security breaches. Even though it possesses greater intricacy in its potential application, a substantial factor is maintaining the private preservation of healthcare data against the growing attacks. Thus, this paper presents a distributed privacy-preserving, chaotic encryption-based framework that can be deployed for CH-IoT systems to safeguard sensitive data against message modification, denial of service (DoS), and man-in-the-middle attacks (MIM), guaranteeing privacy and data integrity. The proposed framework integrated the federated learning layered hybrid chaotic encryption strategies by investigating through examination the learning infrastructure of convolutional neural networks (CNN). In the examination, the complete framework was carried out in the Tensorflow Federated Learning Libraries (FLL), and numerous performance metrics such as accuracy, precision, recall, f1-score, transmission efficiency, and overhead ratio were measured and contrasted with the various existing frameworks. For the intensive analysis, formal and informal security experiments were also conducted by NIST (National Institute of Science and Technology). The analytical results illustrate the importance of the proposed framework by achieving better security performance and outperforming the other existing models. Lastly, the proposed framework has more potential than the other existing frameworks and finds its place in real-time healthcare systems, but it needs to be improvised for real-time datasets.

Block Cipher Algorithms for Data Security in Cloud: A Review

Cloud computing simplifies access to data in a virtualized setting through the internet ubiquitously and users only pay for what they use. If the data is not sufficiently safeguarded from threats like data breaches, side-channel attacks, data loss transit, etc., unauthorized users can access the data stored in the cloud. Encryption methods have been used to protect the information. Currently, the Advanced Encryption Standard algorithm is preferred over the Data Encryption Standard algorithm. This paper conducts a thorough examination of research related to topics like data security threats in the cloud, including occurrence, threats, and remediation. It also assesses encryption algorithms based on parameters such as design, security, computational efficiency, flexibility, and limitations to prevent data breaches. It has been found that maximum throughput rate and minimum memory usage are two measure performance metrics that are competent to prevent data from security breaches by applying experimental and simulation techniques, concluding that the Advanced Encryption Standard is superior to both Data Encryption Standard and 3-DES

Cyber Security Risk Assessment and Optimal Risk Management of a National Vulnerability Database

This research article focuses principally on a certain quantitative rather than qualitatively subjective and non-numerical cyber security risk assessment method, the Security Meter (SM) algorithm, to compute vital security indices in a national vulnerability database case study. The primary purpose will be followed up by a secondary, although critical, goal of managing an unfavorable risk percentage by optimally mitigating it to one selected acceptable level. This objective will be realized by an optimization method using the well-known Linear Programming (LP) technique via both SM and an alternate LP-feasible solution method, EXCEL (XL) Solver. Information and cyber security risks become essential to an organization’s or user’s daily operations in today’s IT-centric world. Vulnerabilities and threats can pose many challenges to the core security of any system, second only to the electric power grid that supplies the Internet. Without the vulnerability and associated threat-exposure management process, organizations remain blind and indifferent to those risks directly related to their IT infrastructure security. This advantage allows any organization or user (given they understand the security risks they face) to take well-advised decisions concerning remediating actions for managing the risks seriously with a cost-effective roadmap. Along with the rampant rise of the potential risks from unexpected cyber-attacks, damage due to uncountable breaches of cyber security is growing at an unprecedented rate and becoming a serious economic concern and peril to users, organizations, and nations. This research article proposes application-based quantitative analyses of commonly encountered security risks in a national vulnerability database, as initial steps toward the optimal security-centric technological investment-savvy evaluations and cost-effective decision-making processes to best manage and prioritize risk mitigation. The SM optimization results favorably compare with XL Solver solutions although SM’s cumulative percentage of countermeasure changes to achieve the mitigation target is demonstrated to be less than that of the XL Solver’s, and therefore, the more cost-optimal. As a major takeaway, the proposed quantitative algorithms are more competitive, practical, goal-oriented, functional, and cost-conscious than conventionally limited descriptive and categorical cyber security risk assessment and management options.

Security Risk and Breach Detection Approach Based Blockchain for Medical Applications

Security Risk and Breach Detection Approach Based Blockchain for Medical Applications

Securing the road ahead: Machine learning-driven DDoS attack detection in VANET cloud environments

Vehicular ad-hoc network (VANET) technology has gained prominence, especially in the context of the emerging field of VANET Cloud as an integral part of connected and autonomous vehicles. The automotive industry’s move towards automation and the integration of vehicles into the digital ecosystem has revolutionized wireless network communications. Nevertheless, security remains a paramount concern in these advanced technological landscapes. Safeguarding system integrity and data privacy is of utmost importance before the widespread adoption of VANET Cloud solutions. This study addresses the critical challenge of security within the context of VANET Cloud. Specifically, the focus is on anticipating and mitigating Distributed Denial of Service (DDoS) attacks, which can potentially disrupt the functioning of connected vehicles and associated cloud-based services. To tackle this issue, an innovative architectural framework is proposed to capture and analyze network flows within the VANET Cloud environment. Additionally, it leverages machine learning techniques for classification and predictive analytics with an accuracy of 99.59%. The architecture presented in this research offers the potential to significantly enhance security measures in VANET Cloud deployments. Its adaptability ensures practical applicability to real-world systems, enabling timely responses to security threats and breaches.

Network Intrusion Detection and Prevention System Using Hybrid Machine Learning with Supervised Ensemble Stacking Model

Network intrusion detection systems play a critical role in protecting a variety of services ranging from economic through social to commerce. However, the growing level and sophistication of malicious attacks launched on networks in the current technological landscape have necessitated the need for advanced and robust detection mechanisms to mitigate against security breaches of confidentiality, integrity, and denial‐of‐service. In this paper, we present a hybrid intrusion detection system that combines supervised and unsupervised learning models through an ensemble stacking model to increase the detection accuracy rates of attacks in networks while minimising false alarms. Three machine learning algorithms comprising a multilayer perceptron neural network, a modified self‐organizing map, and a decision tree were used for the detection framework. The intrusion detection system was trained and evaluated on benchmark datasets: NSL‐KDD and CIC‐DDoS2019. The intrusion detection system was implemented as a Java solution and the detection performance was evaluated. A 10‐fold cross‐validation performance was also performed to validate how well the detection system predicts unknown attacks for prevention. The results of the tests revealed a detection accuracy of 99.84% of the instances in the NLS‐KDD dataset with a true positive rate of 99.8% and a false positive rate of 0.10% while a detection accuracy of 99.90% was achieved with the CIC‐DDoS2019 dataset. Furthermore, the detection system was effective in distinguishing attack traffic from normal traffic in the NSL‐KDD dataset and was able to adequately detect DOS, Probe, and R2L attacks with F1 scores of 100%, 99.6%, and 95.1%, respectively, which are significantly impressive. However, the detection of less frequency attack types such as U2R attacks was quite low with an F1 score of 62.5%. The detection performance of the proposed hybrid intrusion detection system suggests that it can be deployed in network security applications to detect packets that exhibit suspicious behaviour or indicate potential threats and respond appropriately to attacks. Implementing the detection framework as a Java solution makes it possible to deploy it across various operating system platforms without any impact on the detection performance.

Cyberattack Ramifications, The Hidden Cost of a Security Breach

Cyberattack Ramifications, The Hidden Cost of a Security Breach

A Hybrid Intrusion Detection Approach for Cyber Attacks

The field of cybersecurity constantly evolves as attackers develop new methods and technologies. Defending against cyberattacks involves a combination of robust security measures, regular updates, user education, and the use of advanced technologies, such as intrusion detection systems and artificial intelligence, to find out the threats in real-time. IDS are designed to identify and address any unauthorized actions or potential security threats within a computer network or system. A hybrid intrusion detection system (IDS) combines many detection techniques and strategies from different IDS types into a single, coherent solution. Combining the benefits of each approach should result in more comprehensive and effective intrusion detection. This paper outlines a proposed anomaly intrusion detection system (AIDS) framework that leverages a hybrid of deep learning strategies. It incorporates Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models, which were developed using XGBoost, and their efficacy was assessed with the NSL-KDD dataset. The evaluation of the suggested model focused on its accuracy, detection capabilities, and the rate of false positives. The outcomes of this research are noteworthy within the cybersecurity field. In this paper, a framework of an Anomaly IDS is proposed. The purpose of an anomaly IDS, or AIDS, is to spot odd behavior on a network or system that might point to a security breach or malevolent attempt to hack it. Anomaly-based IDSs concentrate on finding departures from accepted typical behavior, in contrast to signature-based detection systems, which depend on a predefined database of known attack patterns.

Implication of Security Breaches on Nigeria’s Security Development: Examination of IPOB in South-East Geo-Political Zone

This paper examines the consequences of security breaches on Nigeria’s security progress, specifically analyzing the actions of the Indigenous People of Biafra (IPOB) in the south-east geopolitical zone. The study explores the various and complex outcomes of security breaches, taking into account issues relating to national security, economic ramifications, societal unity, considerations of human rights, international relations, governmental reactions, attempts towards peace-building, and initiatives for reconciliation. By conducting a thorough analysis, it highlights the interdependence of these consequences and the need for a comprehensive approach to effectively tackle security concerns. The paper emphasises the significance of dialogue, inclusive governance, economic advancement, community policing, safeguarding human rights, engaging with the media, diplomatic initiatives, investing in education and social services, and monitoring underlying factors in addressing security risks and fostering sustainable development. This paper seeks to enhance comprehension of security dynamics in Nigeria and provide insights for policy responses that promote peace, stability, and prosperity in the South-East region and the entire country, with a focus on the case of IPOB.

Customer awareness and cyber security in the Organisation for Economic Co-operation and Development countries

In certain circumstances, millions of documents have been exposed due to an increase in the yearly incidence of cyber security breaches in recent years. In the context of the banking industry’s digital transition in the Organisation for Economic Co-operation and Development (OECD), this study investigates consumer knowledge of and satisfaction with cyber security. The study is empirical and based on the data obtained from 240 banking clients in OECD. Cyber attacks, phishing, and hacking have been examined from diverse angles. The effects of cyber attacks, phishing, hacking, cyber security help, and expectations on cyber security’s technical awareness are investigated using analysis of variance (ANOVA) and bivariate regression analysis. The findings demonstrate how the banking industry has benefited from digital change, and users gain from online services. Nonetheless, a customer’s degree of awareness regarding hacking, phishing, and cyber attacks will have an impact on how satisfied they are with digital transactions. The findings also showed that banks should regularly offer training programs to protect their clients from cyber attacks and that customers need more assurance from banks about security-related issues. Banks might easily meet their long-term sustainability goals if they implemented better safer cyber security management. This paper has repercussions for policymakers, investors, and business organizations. Importantly, our study reveals how customer awareness and cyber security are related in OECD.

Zero trust architecture logical components and implementation approaches

Zero Trust Architecture (ZTA) is a contemporary cybersecurity approach that challenges the traditional perimeter-based security model. In the zero-trust model, organizations do not automatically trust any user or device, regardless of whether they are inside or outside the corporate network. Instead, it assumes that threats can come from both internal and external sources, and it verifies every user and device attempting to access resources. Here are the key principles of this software development trend: • Identity verification: individuals need to authenticate their identity before gaining access to resources. This often includes multifactor authentication and reliable verification methods. • Least privilege access: users are granted the minimum access required to perform their tasks. Access is limited only to essential elements, reducing the potential impact of a security breach. • Micro-segmentation: involves segmenting the network at a granular level, allowing isolation and protection of individual resources. • Data encryption: encryption is applied both during transmission and at rest to safeguard data from unauthorized access. • No implicit trust: applying the principle of "never trust, always verify," meaning verification is necessary at every stage of access. The article discusses modern challenges and approaches to cybersecurity amidst the rapid development of cloud technologies. Specifically, it analyzes the shift in container usage in software deployment and its impact on the cybersecurity model. Security approaches based on the concept of Zero Trust Architecture (ZTA) are highlighted in the context of new demands and opportunities. The article elaborates on key logical components of ZTA, such as policy mechanism and policy administrator, pointing out their interaction in creating a secure environment. It also provides an overview of data sources used for creating access policy rules and their consideration in ZTA mechanisms. Additionally, approaches to implementing ZTA for operational workflows in corporate environments are proposed: enhanced identity management, logical micro-segmentation, and network-based segmentation. Each of these approaches has its advantages and is considered based on the needs of individual organizations.

Max Drone: environmental influence on a company

Learning outcomes This case study seeks to develop the analytical and critical thinking skills of the students so that they can not only understand and carry out a comprehensive diagnosis of the case in its facets of entrepreneurship but also see reflected the inherent difficulties of the process and how these can be overcome, based on available resources and capabilities. In the same way, it seeks to develop students’ capacity for critical analysis when making a decision in which, on the one hand, there is a very large market potential that they can try to exploit, taking into account the political transformation that modifies the rules of the game with which the business began, in addition, of course, to the case of a security breach specified in the case and, on the other hand, the possibility of resigning, avoiding greater losses. Case overview/synopsis This case study exposes the situation of the company Max Drone Venezuela, which had been dedicated to the service, repair and training of drones. This family-owned company had gone through a series of stages that clearly exemplified how environmental factors served to identify opportunities in the early stages of the business, promote strategic actions to maintain itself, guide the course to sustain itself and seek development in hostile environments. Complexity academic level Given the characteristics of this case study, it can be used for the teaching and learning of business or business administration, marketing, economics or related students, at higher or postgraduate levels (graduate school). Supplementary materials Teaching notes are available for educators only. Subject code CSS3: Entrepreneurship.

An empirical study on differences between self-assessed and measured real risk in online behaviour

As the leading cause of security breaches is human susceptibility to hackers' deception, the riskiness of an individual's online behaviour and low awareness regarding privacy protection significantly influence the overall security of an information system. Thus, this study aimed to compare self-assessed and measured real risk in online behaviour among online users. The additional aim was to modify the questionnaire by replacing the existing trick question about password quality with the new questions on accepting the terms and conditions. An international online Behavioral Cognitive Internet Security Questionnaire (BCISQ), validated in previous studies, was used for data collection. The examinees involved in this study were 278 students from different faculties. The results showed a relatively high level of risk in online behaviour, as 22.7% of examinees revealed their passwords. In comparison, only 10.8% read the consent statement. Students who behave in a riskier manner self-assess themselves as being significantly safer in online behaviour, which is contradictory. They also performed worse in all other examined variables. The new version of the simulation subscale, with improved internal consistency and reliability (Cronbach's Alfa=0.810), consists of only three items, which are questions used in the previous version, without adding any of the two tested trick questions. Generally, this study concludes that, on average, information security awareness is still low among online users and that even the ones realistically acting riskier believe they are acting more safely.

A cellular automata approach for extending data privacy and security of edge computing

This article introduces a cellular automaton (CA) based method to heighten the security breach of edge computing data. Edge computing is an innovative computing paradigm that controls the processing network’s edge devices. Relocating computation nearer to the resource is the main goal of edge computing. Based on the CA’s concept, a strong secret key is introduced for text cryptography. The secret key generated in this research is a 64-character key, which performs substitutions and reverse substitutions on the plain text and cipher text by dividing the text into blocks of 64 characters. The key may be to use the same or different letters to substitute the same letters of the plain text which makes it a unique key. The strength of the key is evaluating using the substitution speed, memory utilization, possible attack, and avalanche effects.

Інструменти цифрової економіки в контексті підвищення ефективності діяльності промислових підприємств

Digital transformation is becoming an integral part of the development of industrial enterprises in the modern world. The phase of transition to the digital economy is expected not only to increase the productivity and efficiency of production processes, but also to open up new opportunities for development and a competitive position in the market. The inclusion of digital instruments in the activities of industrial enterprises can greatly facilitate management, improve product quality and ensure more efficient use of resources. The aim of the article is to study and analyze the instruments of the digital economy in the context of improving the efficiency of industrial enterprises. The article analyzes the definition of «digital economy» and provides the authors’ own definition of this term. The prospects for the introduction of the digital economy in the activities of industrial enterprises are determined, among which an increase in labor productivity, an increase in product quality parameters, a decrease in costs, an increase in the level of adaptation and the level of competitiveness are allocated. The main program document for the development of Industry 4.0 in Ukraine named «Strategy 4.0» is analyzed. The main instruments of the digital economy have been identified, which should include the Internet of Things, artificial intelligence, machine learning, data analytics, cloud technologies, digital platforms, and ecosystems. It is proved that the introduction of digital economy instruments in the activities of industrial enterprises creates prerequisites for optimizing production processes. The article also states that the process of introducing digital instruments into the activities of industrial enterprises creates prerequisites for certain challenges and threats, including the threat of cyberattacks, data security breaches, large investments in the transfer of knowledge and technology and, as a result, the need to upgrade production equipment to more modern, complex integration of new technologies into existing production processes. Therefore, the development of the digital economy at industrial enterprises can help increase their competitiveness and stability in the market. Ensuring that digital instruments are correctly selected, implemented, and optimized is an important task for enterprise management and staff in the era of digital transformation.