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Sensors and wearable technology are used to accumulate health-related data from the visually impaired (VI) and other special persons. This health-related data is disseminated via an open network channel, which poses numerous threats and requires rigorous attention for its protection. An appropriate security framework must be implemented on both the sender and the recipient sides to ensure the privacy and security of sensitive medical information for VI and disabled persons. The telehealth system will then benefit the VI and disabled people by improving their quality of life, telemonitoring, saving time and money, providing online support, and increasing the degree of trust and reliance on the system and the treatment of doctors. These practical benefits are not just theoretical but potentially life-changing for the VI and disabled community. Strong and flawless mutual authentication is necessary for the telehealth system to secure and preserve the privacy of VI and disabled people. Therefore, this article proposes a privacy-preserving asymmetric-based, lightweight, and robust security framework for the telehealth system operationalized for VI and disabled people. The proposed security framework alleviates all threats to sensitive information and preserves the privacy and security of the whole telehealth system. The security of the proposed framework has been verified through a well-known Real-Or-Random (RoR) model and simulated through a ProVerif software verification toolkit, while the performance analysis has been tackled by measuring computation, storage, and communication costs. The comparative analysis result revealed that the proposed framework outperforms its competitors, further reinforcing the hope about its potential impact. [Display omitted] • To design a fast and secure protocol for securely authenticating visually impaired (VI) and disabled people of the telehealth system in the digital world. • To present a secure mechanism that not only protects the privacy of VI and disabled people when transmitting personal sensitive information remotely but also opens up new possibilities for their participation in telehealth. • To confirm the security of the proposed authentication protocol formally through the Real-Or-Random (RoR) model and ProVerif and informally through discussions of known attacks. • To conduct a comprehensive performance analysis of the proposed protocol, considering storage, communication and computation costs in providing a robust and reliable solution. • To comparatively analyze the proposed security mechanism with state-of-the-art mechanisms by scrutinizing its efficacy and robustness based on a set of predefined criteria. This will provide a clear understanding of how our protocol stands against existing solutions. [ABSTRACT FROM AUTHOR]

The widespread adoption of emerging information and communication networks has increased organizations' vulnerability to cyberattacks. These attacks – including data breaches, ransomware, and other cyber threats – pose significant economic risks to the stability of modern businesses. This study offers a comprehensive analysis of the economic impacts of cyberattacks within the context of these emerging networks and outlines effective cyber risk management strategies to enhance organizational resilience. The research elucidates the complex economic repercussions of cyber threats by conducting a rigorous literature review and an in-depth case study of the 2019 ransomware attack on Norsk Hydro ASA. The findings underscore the critical necessity for robust cybersecurity measures in the evolving digital landscape. [ABSTRACT FROM AUTHOR]

Businesses increasingly rely on digital technologies in the digital age, making them vulnerable to cyberattacks. These attacks, which range from data leaks to ransomware, can cause significant economic damage. Effective cyber risk management strategies that include preventive, reactive, and continuous measures can significantly reduce the risk and impact of such attacks. Norsk Hydro's case study illustrates the importance of a robust incident response plan and continuous improvements in cybersecurity measures. This study examines the economic impact of cyberattacks on organizations and identifies effective cyber risk management strategies that can strengthen organizational resilience. The methodology is based on a light literature review, including scientific and grey literature. It also includes an analysis of a real-world case study: the ransomware attack on Norsk Hydro ASA in 2019. The results show that cyberattacks cause direct costs. Furthermore, this study contributes to the academic discourse on cybersecurity and economic resilience by providing evidence-based insights and practical recommendations for businesses. Companies that invest in comprehensive cyber risk management strategies can ensure economic stability and gain competitive advantage by better managing the complexities of the digital landscape. [ABSTRACT FROM AUTHOR]

Cyber threats are constantly evolving, making it crucial for organizations in the UAE to enhance their cybersecurity strategies. This study focuses on understanding and countering organized and unorganized cybercrimes within the UAE. Organizations strengthen outer defences but often neglect protecting sensitive data internally. Insiders, individuals with intricate knowledge of system cycles, can cause substantial damage. Their motivations vary, from stealing data to causing harm, making it essential for organizations to comprehend and counter these threats effectively. The study employs qualitative analysis methods and in-depth interviews with key cybersecurity experts across various sectors. Through these discussions, we identified key defensive strategies utilized by different entities in the UAE. Our research highlights the significance of securing networking routes and data transformation pathways, underscoring the need for a proactive cybersecurity approach. Through qualitative analysis and expert interviews, we pinpointed specific defensive methods used by individuals, small organizations, and government/private sectors in the UAE. Additionally, we delve into the motivations of insiders, highlighting their substantial threat due to their in-depth understanding of network layouts, applications, and business practices. By securing these aspects, organizations can identify essential security concerns and develop robust, effective plans. We suggested practical steps to improve cybersecurity frameworks, aiming to prevent data breaches, strengthen security strategies, and promote a cybersecurity-aware mindset. By implementing these strategies, organizations can enhance their defences, foster a culture of cybersecurity awareness, and safeguard digital assets in the UAE. [ABSTRACT FROM AUTHOR]

Enhancing information security in multimedia streams is a critical endeavor in the digital age, where data breaches and cyber threats loom large. This research proposes a novel approach by integrating Logic Learning Machines (LLMs) with Moth-Flame Optimization (MFO) to fortify the defenses of multimedia data against potential vulnerabilities. Logic Learning Machines, known for their ability to make decisions based on logical reasoning, form the foundational intelligence of our proposed system. Leveraging their capacity to process complex patterns and relationships within data, LLMs become the cognitive backbone of our security enhancement model. Moth-Flame Optimization, inspired by the navigational behavior of moths around artificial lights, serves as the optimization engine in this framework. MFO mimics the natural attraction of moths to flames, translating it into an algorithmic strategy to optimize parameters and configurations for heightened security measures. By applying MFO, the system dynamically adapts and refines its security protocols in response to evolving threats. The synergy between LLMs and MFO creates a resilient defense mechanism for multimedia streams. The logic-driven decision-making of LLMs is augmented by the adaptive optimization capabilities of MFO, resulting in a robust and dynamic security infrastructure. This fusion not only enhances the detection of potential threats but also enables proactive adjustments to security parameters, thereby fortifying the system against emerging risks. The proposed framework is validated through extensive simulations and experiments, demonstrating its efficacy in real-world scenarios. The outcomes showcase improved information security for multimedia streams, providing a versatile solution for safeguarding sensitive data in diverse digital environments. [ABSTRACT FROM AUTHOR]

In current information era, every small-scale industry, MNC's, Schools, and Colleges utilise Web Applications to promote their organizations and provide services to society. Web Applications have become a simple and vital medium for communicating with society. This leads to an increase in website utilization. Threats and cyber-attacks are increasing according to the rate of growth of Web Applications. Any organization must ensure the privacy and security of its users' data in order to maintain the company's and users' integrity. Web application vulnerabilities represent major security risks, making it critical to conduct extensive assessments and penetration testing to discover and remediate such flaws. The paper provides a complete overview of web application vulnerability assessment and penetration testing, emphasizing the need of proactive security measures in protecting sensitive data and preserving application integrity. This study aims to identify and categorize web application vulnerabilities (OWASPs) that may compromise the security of the application and result in user data breaches. The primary focus of this project is the security and privacy of user data. Integrating security practices into the software development life cycle through investigating real-world case studies and industry standards. Ultimately, our research adds to the growing body of knowledge in web application security, assisting organizations in creating resilient defenses against cyber threats. [ABSTRACT FROM AUTHOR]

In cyberspace, there exists a prevalent problem that heavily occurs to web application databases and that is the exploitation of websites by using SQL injection attacks. This kind of attack becomes more difficult when it comes to blind SQL vulnerabilities. In this paper, we will first make use of this vulnerability, and subsequently, we will build an ontology (OBSQL) to address the detection of the blind SQL weakness. Therefore, to achieve the exploitation, we reproduce the attacks against a website in production mode. We primarily detect the presence of the vulnerability, after we use our tools to abuse it. Last but not least, we prove the importance of applying ontology in cybersecurity for this matter. The mitigation techniques in our ontology will be addressed in our future work. [ABSTRACT FROM AUTHOR]

In today's digital era, there have been an ever increase in academic libraries embracing digital collections to provide access to a wealth of information to their users. However, the demerit of this digitization brings about the need to ensure the security of these valuable digital collections, especially in developing countries where cyber threats are rampant. This paper aims to address the challenges faced by academic libraries in developing countries with regards to best cybersecurity practices for securing digital collections. The paper also highlights the long-term benefits of prioritizing cyber security in academic libraries. Besides protecting valuable digital collections, robust cyber security practices enhance users trust, promote collaboration among institutions, and support academic research in a secure environment. This paper serves as a valuable resource for academic libraries in developing countries, as it offers guidelines and insights to enhance their cyber security practices. By adopting most of these best practices, libraries can safeguard their digital collections, mitigate cyber threats, and contribute to a secure and thriving academic environment. [ABSTRACT FROM AUTHOR]

Satellite networks are vital in facilitating communication services for various critical infrastructures. These networks can seamlessly integrate with a diverse array of systems. However, some of these systems are vulnerable due to the absence of effective intrusion detection systems, which can be attributed to limited research and the high costs associated with deploying, fine-tuning, monitoring, and responding to security breaches. To address these challenges, we propose a pre-trained Large Language Model for Cyber Security, for short PLLM-CS, which is a variant of pre-trained Transformers, which includes a specialized module for transforming network data into contextually suitable inputs. This transformation enables the proposed LLM to encode contextual information within the cyber data. To validate the efficacy of the proposed method, we conducted empirical experiments using two publicly available network datasets, UNSW_NB 15 and TON_IoT, both providing Internet of Things (IoT)-based traffic data. Our experiments demonstrate that proposed LLM method outperforms state-of-the-art techniques such as BiLSTM, GRU, and CNN. Notably, the PLLM-CS method achieves an outstanding accuracy level of 100% on the UNSW_NB 15 dataset, setting a new standard for benchmark performance in this domain. [ABSTRACT FROM AUTHOR]

The rapid expansion of Internet of Things (IoT) devices presents unique challenges in ensuring the security and privacy of interconnected systems. As cyberattacks become more frequent, developing an effective and scalable Intrusion Detection System (IDS) based on Federated Learning (FL) for IoT becomes increasingly complex. Current methodologies struggle to balance spatial and temporal feature extraction, especially when dealing with dynamic and evolving cyber threats. The lack of diversity in datasets used for FL-based IDS evaluations further impedes progress. There is also a noticeable tradeoff between performance and scalability, particularly as the number of edge devices in communication increases. To address these challenges, this article introduces a horizontal FL model that combines Convolutional Neural Networks (CNN) and Bidirectional Long-Term Short Memory (BiLSTM) for effective intrusion detection. This hybrid approach aims to overcome the limitations of existing methods and enhance the effectiveness of intrusion detection in the context of FL for IoT. Specifically, CNN is used for spatial feature extraction, enabling the model to identify local patterns indicative of potential intrusions, while the BiLSTM component captures temporal dependencies and learns sequential patterns within the data. The proposed IDS follows a zero-trust model by keeping the data on local edge devices and sharing only the learned weights with the centralized FL server. The FL server then aggregates updates from various sources to optimize the accuracy of the global learning model. Experimental results using CICIDS2017 and Edge-IIoTset demonstrate the effectiveness of the proposed approach over centralized and federated deep learning-based IDS. [ABSTRACT FROM AUTHOR]

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There is a massive growth in the rate of heterogeneous devices configured in the Internet of Things (IoT) environment for efficient communication. The IoT devices are limited in resources, and there are no defined protocols in terms of security during communication in the IoT-based platforms. Several solutions are framed to make communication secure in the IoT ecosystem. However, the existing schemes need to be more reliable to handle the cyber threats and unwarranted incidents (such as intrusions, anomalies and attacks) coming from IoT endpoints owing to the unstructured patterns of IoT data and dynamic network conditions. Moreover, heavy cryptographic primitives have their deployment challenges due to the resource constraints of the IoT ecosystem. The dynamic nature of IoT traffic requires flexible and varied rules to handle the threats in different deployment scenarios. Therefore, a programmable interface enabled through Software-defined Networking (SDN) can handle heterogeneous threats and incidents in the IoT cyber world. Thus, in this paper, we have designed a novel framework, SecureFlow, an intrusion detection and dynamic rule configuration system based on the knowledge-based and data-driven ensemble. The proposed framework is robust and fault tolerant owing to dual-layer Intrusion Detection System (IDS) and rule configuration modules that can work without one of them. SecureFlow validated through several experiments performed through emulations in Mininet. The results depict that the proposed framework is effective and promising. [ABSTRACT FROM AUTHOR]

Technology innovation, market demand, and the potential impacts of a changing climate are driving the marine renewable energy (MRE) industry to develop market-ready systems to provide low-carbon electricity for emerging, off-grid markets. The advanced operational and information technology devices used in MRE systems create a pathway for a cyber threat actor to gain unauthorized access to data or disrupt operation. To improve the resiliency of MRE systems as a predictable, affordable, and reliable source of energy from oceans and rivers, guidance was developed for an end users' organization that describes a framework for identifying and managing cybersecurity risk. The development of the cybersecurity guidance is based on standards described in the Risk Management Framework and Cybersecurity Framework developed by the National Institute of Standards and Technology (NIST). This paper is the first of a two-part series that describes an approach to determine the cybersecurity risk forMRE systems based on assessing potential cyber threats, identifying vulnerabilities (people, processes, and technology, including physical and operational environment), and evaluating the consequences a cyberattack would have on operation of the MRE system and impact on end users' mission and business objectives. MRE developers and stakeholders can use this approach to assess their current cybersecurity risk posture to incorporate appropriate cybersecurity controls to reduce the consequences and impacts from a cyberattack on MRE systems. This approach can be refined further as MRE systems are deployed and operational configurations are available. [ABSTRACT FROM AUTHOR]

Cyber espionage is a serious threat. In this tutorial we present an analysis of various cases of cyber espionage. The cases provide insight on the actors and the impact that the incident had on the organization or society at large. The various kinds of attacks are discussed and a final synthesis presents the best practices for managing cyber espionage attacks. [ABSTRACT FROM AUTHOR]

The development of the Internet of things is the final process of mass integration of computer technologies, technological chains of communication and various sectors of the industrial industry. IS bottlenecks arise because of techniques of eavesdropping, distortion and disclosure of personal information, etc. IoT applications face errors on the application plane - with the use of cloud computing, information processing, protection of confidential information and intellectual property rights. [ABSTRACT FROM AUTHOR]

Influential voices call for efforts to curb the accelerating cyber arms race. One proposed strategy is cyber arms control. We argue that the pursuit of this regulation would be stymied, and any regulation passed would be ineffective on the basis that 1) neither unilateral nor multilateral cyber arms control efforts would be effective, and that 2) cyber arms control would conflict with both sovereignty and legitimate peaceful development efforts. [ABSTRACT FROM AUTHOR]

This paper presents the study framework and results in assessing the consequences of cyberattacks on urban automobile transport systems. Consequences in two attack profiles, involving semantic hacking on the one hand and a DoS - attack on the other, are assessed via modelling using the transport simulation system Aimsun. The author compares the negative impact of cyberattacks on urban transport in terms of increased delay and possible traffic accidents, as well as elevated levels of pollutants in the air. [ABSTRACT FROM AUTHOR]

While extant literature on privacy in social networks is plentiful, issues pertaining to information security remain largely unexplored. This paper empirically examines the relationship between online victimisation and users' activity and perceptions of personal information security on social networking services (SNS). Based on a survey of active users, we explore how behavioural patterns on social networks, personal characteristics and technical efficacy of users impact the risk of facing online victimisation. Our results suggest that users with high-risk propensity are more likely to become victims of cybercrime, whereas those with high perceptions of their ability to control information shared on SNS are less likely to become victims. The study shows that there is a negative and statistically significant association between multipurpose dominant SNS (e.g. Facebook, Google +) usage and victimisation. However, activity on the SNS for knowledge exchange (e.g. LinkedIn, Blogger) has a positive and statistically significant association with online victimisation. Our results have implications for practice as they inform the social media industry that protection of individual information security on SNS cannot be left entirely to the user. The importance of user awareness in the context of social technologies plays an important role in preventing victimisation, and social networking services should provide adequate controls to protect personal information. [ABSTRACT FROM AUTHOR]

Smart grid doesn’t have a single standard definition to define it. Commonly, Smart Grid is an incorporation of advanced technologies over the normal electrical grid. Smart grid provides some novel features that mainly includes two way communication and automatic self-healing capability. Like Internet, Smart Grid also consists of many new technologies and equipment that are bind together. These technologies works with the electrical grid and respond digitally to our quickly changing electric demand. Even though it is stuffed with pros, it suffers a lot due to its fragile data security. Smart grid usually have a centralized control system called SCADA to monitor and maintain all the data sources. Attackers would always tend to sneak through this centralized system through numerous types of attacks. Since SCADA system has no definite protocol, it could be adopted with any kind of protocol that is required by the utility. Usually, there are certain tools which are commonly used in the IT and corporate systems. But how long it is compatible with SCADA network is always questionable In this paper, a comparison of countermeasure between the proposed methodology and the security tools (Wireshark, tcpdump) is been analyzed under Distributed Denial of Service (DDoS) with Sniffing attacks . The security system apt for SCADA network is analyzed on the basis of bandwidth consumption and traffic analyzing capacity. [ABSTRACT FROM AUTHOR]

This paper analyses the concept of leadership and its impact on human factors in the minimisation of security risk. A chronology of information security (IS) institutionalisation describes the combination of technical approaches and human management. It explains that many technological approaches to security have been developed to minimise security risks, but that such approaches are meaningless if human management fails to commit. It has been shown that too many incidents leading to cyber threats occur not because of technological, but rather human factors. This paper therefore studies human management by investigating the relationship between leadership and human factors. The research is conducted by means of an online survey of participants who are currently employed at manager, executive and non-executive levels. The two theories tested show that there is a significant correlation between management communication and employees' responsibility, which lead to a significant impact on the human factors in cyber threats. The study concludes that leadership and human failure are correlated to each other and that they contribute to the understanding that leadership is the key aspect in the prevention of cyber threats. [ABSTRACT FROM AUTHOR]

• A precedent study was conducted to evaluate cyber risks to nuclear power plants. • A database of cyber threats was constructed for a probabilistic approach. • A list of cyber threats was developed via operating experience report analysis. • Frequencies of cyber threats were estimated using two-stage Bayesian update. The necessity and importance of cyber risk assessments at nuclear power plants is increasingly being recognized in recent times. However, the cyber risk assessment methods developed thus far have focused on engineering evaluations and expert judgments. Moreover, there is no available probabilistic database of cyber threats for nuclear power plants. In this study the frequencies of cyber threats were estimated based on operating experience analysis. The operating experiences are grouped by their characteristics to suggest the list of cyber threats, and the frequency of each cyber threat is calculated by two-stage Bayesian updates. This research is significant because it is the first study on a probabilistic approach to estimate cyber threats. Furthermore, this research offers the advantage of being able to update the threat frequencies with additional data accumulation. We expect that this approach can also be applied to probabilistic safety assessment, which is the most widely used method for nuclear power plant risk assessment. [ABSTRACT FROM AUTHOR]

• We analyze information security threats to connected and autonomous vehicles (CAVs). • We analyze consumer preference for the security solution protecting CAVs from security threats. • Consumers have a high heterogeneity in security threats and preferred attributes of CAV solution. • Communication failure is regarded as the most dangerous threat to CAV. • Consumer's experience of privacy leakage affects preference for CAV security solution. Connected and autonomous vehicles (CAVs) and intelligent transport systems are transforming individual driving behavior and thus, the vehicle industry and transport sector. However, increasing vehicle connectivity makes CAVs more susceptible to cyber-attacks, which is a barrier to consumers' CAV adoption. This study analyzes the types of information security threats consumers consider to be the most dangerous and consumer preference for the information security solution that protects their CAVs from such information security threats. We use stated preference data from a discrete choice experiment and a mixed logit model to reflect consumers' heterogeneity on information security threats and solutions. Furthermore, we investigate the effects of experiencing privacy leakage on attitudes toward CAV information security threats by dividing respondents into two groups. The results show that consumers regard communication failure and the unauthorized collection of personal information as dangerous information security threats, which implies that confidentiality and availability are more essential to CAV security than other factors. Moreover, convenience of use, such as having automatic updates and a security dashboard, is also important when purchasing a CAV information security solution. We also find that respondents who have experienced privacy leakage have a higher preference for protecting CAVs from information security threats than those who have not. [ABSTRACT FROM AUTHOR]