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Edge data analytics refers to processing near data sources at the edge of the network to reduce delays in data transmission and, consequently, enable real-time interactions. However, data analytics at the edge introduces numerous security risks that can impact the data being processed. Thus, safeguarding sensitive data from being exposed to illegitimate users is crucial to avoiding uncertainties and maintaining the overall quality of the service offered. Most existing edge security models have considered attacks during data analysis as an afterthought. In this paper, an overview of edge data analytics in healthcare, traffic management, and smart city use cases is provided, including the possible attacks and their impacts on edge data analytics. Further, existing models are investigated to understand how these attacks are handled and research gaps are identified. Finally, research directions to enhance data analytics at the edge are presented.

Edge data analytics refers to processing near data sources at the edge of the network to reduce delays in data transmission and, consequently, enable real-time interactions. However, data analytics at the edge introduces numerous security risks that can impact the data being processed. Thus, safeguarding sensitive data from being exposed to illegitimate users is crucial to avoiding uncertainties and maintaining the overall quality of the service offered. Most existing edge security models have considered attacks during data analysis as an afterthought. In this paper, an overview of edge data analytics in healthcare, traffic management, and smart city use cases is provided, including the possible attacks and their impacts on edge data analytics. Further, existing models are investigated to understand how these attacks are handled and research gaps are identified. Finally, research directions to enhance data analytics at the edge are presented. [ABSTRACT FROM AUTHOR]

With the advancement of ICTs, the fifth generation has developed into an emergent communication platform that supports high speed, low-latency, and excellent connectivity to numerous devices with modern radio technology, service-oriented design, and cloud infrastructure. The recent developments in 5G and existing proposed plans are centered on the security model of this study, with authentication, availability, confidentiality, integrity, visibility, and a centralized security policy. However, initiating innovative technologies and enhanced aspects in 5G communication raises new requirements and has presented various security challenges. 5G-based applications face security risks because they use modern technology. This paper presents a study of security attacks and the security risks faced by 5G intelligent applications. This article also investigates the three main 5G usage scenarios (i.e., eMBB, uRLLC, and mMTC). This research recommends reducing the security risks of 5G usage scenarios and intelligent applications. [ABSTRACT FROM AUTHOR]

Many organizations around the world suffer large losses due to unexpected risks which can have a profound impact on their survival. This paper presents a novel security framework to address the security needs of Saudi organizations. There are four stages in the security framework: risk assessment and management, security intelligence and analytics, security policies and procedures, and security monitoring. A comprehensive security solution was provided by combining common security frameworks, e.g. ISO/IEC 27001:2013, NIST Cybersecurity Framework, and COBIT. The developed framework was designed to help Saudi organizations identify, assess, and control risks and respond to unexpected events in a timely and effective manner. It is expected to help organizations develop and implement effective security measures to protect their critical assets and operations from security threats. The proposed framework is comprehensive and can cover most organizations' requirements. [ABSTRACT FROM AUTHOR]

Security represents one of the most important challenges for the global supply chains that characterise our globalised economic systems. The occurrence of (lack of) security related events has raised the attention of practitioners, governments and scholars. The aim of this paper is twofold. It first wants to propose a review of the models that concern transport security and to highlight that some of them refer to the prevention (regime models, proactive models and participation models) while others attain the efficient and effective reaction and the minimisation of the consequences of security related episodes (barrier models, preparedness models and reactive models). The presentation of the models is complemented by a comparative analysis that will draw some general remarks on the main common topics that emerge in the previous description and highlights the ever-increasing role of coordination and communication among stakeholders for the enhancement of transport security. The second objective of the paper lies in the subsumption of transport security in general Supply Chains. In order to reach this goal, the points of vulnerability and risk factors of the supply chain are considered. This analysis is then extended to a discussion of the main supply chain security practices and activities and of the relevant role played by the transport security models. The review allows to draw several conclusions. A sound security strategy is based on preparation and planning, alongside effective partnerships, structural and managerial adaptation and dedicated communications and technologies both in a static and in a dynamic perspective. Moreover, security strategies need to consider the trade-offs with privacy and with efficiency issues. Security efforts should be concentrated on the preeminent infrastructures, nodal points and arcs according to their degree of weakness and to their centrality in the supply chain. It is also important to plan a set of incentives for the firms that contribute to the security investments and of penalties for those who adopt a free-riding behaviour. Lastly, it is relevant to assess which share of security activities can be accomplished internally and the ones that have to be outsourced to security specialised firms. [ABSTRACT FROM AUTHOR]

The term intrusion refers to a series of behaviours that exposes computer networks and systems' security to compromises. Corrective action on the network cannot go on without intrusion detection. IDS and IDS is the framework used to detect network traffic intrusions, which is how the network control mechanism identifies potential intrusions. Security breaches are designed to undermine one or more of the network's three primary security goals: privacy, availability, and trust. To get access to a system, an attacker must follow a predetermined set of procedures. Once inside, they can begin gathering data such as the protocol being used and the network resources available. There are many ways for a hacker to find out what systems are available on the network and how vulnerable they are to attacks. The rapid advancement of network technology necessitated IDS to focus on the detection of assaults using contextual analysis from signature matching processes. Using machine learning to detect and prevent intrusions, the IDS is a critical part of protecting data systems. Network intrusion detection is the focus of this paper, which examines and shows various machine learning techniques. [ABSTRACT FROM AUTHOR]

The industrial internet of things (IIoT) has grown in recent years, which makes it possible to publicize recent technological innovations and be able to integrate them with each other, such as smart cities, among other applications such as health, education, transit and others, but at the same time there is a problem that is security, due to the fact that incidents related to IIoT have been registered against data networks, for this reason it is necessary to generate intelligent solutions in cybersecurity, which allow to give a satisfactory solution. The objective of this work was to propose an intelligence technique adaptable to a cybersecurity framework with the ability to solve cybersecurity problems in networks of IIoT devices, for the development of which the research-action methodology (I-A), which consists of merging theory with practice in such a way that the researcher can generate accurate conclusions about the practices carried out. In this sense, with this methodology it is intended to provide solutions to specific problems in a given situation. Based on the above, a systematic literature review of the different artificial intelligence techniques was carried out, to finally determine the most appropriate ones and proceed to carry out the respective validations until the appropriate one was selected. Where it was found that there is a great variety of intelligence techniques such as Deep Learning (Deep Learning), who obtained a very high score in the characterization that was carried out due to its great possibilities when integrating the algorithm into the field of cybersecurity, it was identified that they are very poorly characterized; however, in the initial research that was done, the result was how to work with this technology and how to adapt it to cybersecurity. There are different ways to analyze and secure data on the network, one of these is learning techniques, in this research several techniques were identified that with their respective algorithms provided the basis for adaptability with a framework related to IIoT technologies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has forced much education to move into a distance learning (DL) model. The problem addressed in the paper is related to the increased necessity for the capacity of data, secure infrastructure, Wi-Fi possibilities, and equipment, learning resources which are needed when students connect to systems managed by institutional, national, and international organizations. Meanwhile, there have been cases when learners were not able to use technology in a secure manner, since they were requested to connect to external learning objects or systems. The research aims to develop a sustainable strategy based on a security concept model that consists of three main components: (1) security assurance; (2) users, including administration, teachers, and learners; and (3) DL organizational processes. The security concept model can be implemented at different levels of security. We modelled all the possible levels of security. To implement the security concept model, we introduce a framework that consists of the following activities: plan, implement, review, and improve. These activities were performed in a never-ending loop. We provided the technical measures required to implement the appropriate security level of DL infrastructure. The technical measures were provided at the level of a system administrator. We enriched the framework by joining technical measures into appropriate activities within the framework. The models were validated by 10 experts from different higher education institutions. The feasibility of the data collection instrument was determined by a Cronbach's alpha coefficient that was above 0.9. [ABSTRACT FROM AUTHOR]

This work is a review on existing authenticated key exchange (AKE) security models and protocols mainly based on Diffie-Hellman Key Exchange (DHKE). We provide a discussion on the various security models of AKEs, such as the Bellare Rogaway (BR) model, Canetti Krawczyk (CK) model and their variants. Then we provide a review covering over ninety protocols in chronological order. The security models' security features and protocol examples that fit in those security models are exhibited. [ABSTRACT FROM AUTHOR]

As the IoT adoption is growing in several fields, cybersecurity attacks involving low-cost end-user devices are increasing accordingly, undermining the expected deployment of IoT solutions in a broad range of scenarios. To address this challenge, emerging Network Function Virtualization (NFV) and Software Defined Networking (SDN) technologies can introduce new security enablers, thereby endowing IoT systems and networks with higher degree of scalability and flexibility required to cope with the security of massive IoT deployments. In this sense, honeynets can be enhanced with SDN and NFV support, to be applied into IoT scenarios thereby strengthening the overall security. IoT honeynets are virtualized services simulating real IoT networks deployments, so that attackers can be distracted from the real target. In this paper, we present a novel mechanism leveraging SDN and NFV aimed to autonomously deploy and enforce IoT honeynets. The system follows a security policy-based approach that facilitates management, enforcement and orchestration of the honeynets and it has been successfully implemented and tested in the scope of H2020 EU project ANASTACIA, showing its feasibility to mitigate cyber-attacks. [ABSTRACT FROM AUTHOR]

Typically, secure channels are constructed from an authenticated key exchange (AKE) protocol, which authenticates the communicating parties based on long-term public keys and establishes secret session keys. In this paper we address the partial leakage of long-term secret keys of key exchange protocol participants due to various side-channel attacks. Security models for two-party authenticated key exchange protocols have been developed over time to provide security even when the adversary learns certain secret values. This paper combines and extends the advances of security modelling for AKE protocols addressing more granular partial leakage of long-term secrets of protocol participants. Further, we fix some flaws in security proofs of previous leakage-resilient key exchange protocols.

This paper closes a definitional gap in the context of modeling cryptographic two-party channels. We note that, while most security models for channels consider exclusively unidirectional communication, real-world protocols like TLS and SSH are rather used for bidirectional interaction. The motivational question behind this paper is: Can analyses conducted with the unidirectional setting in mind—including the current ones for TLS and SSH—also vouch for security in the case of bidirectional channel usage? And, in the first place, what does security in the bidirectional setting actually mean? After developing confidentiality and integrity notions for bidirectional channels, we analyze a standard way of combining two unidirectional channels to realize one bidirectional channel. Although it turns out that this construction is, in general, not as secure as commonly believed, we confirm that for many practical schemes security is provided also in the bidirectional sense.

Randomness plays an important role in multiple applications in cryptography. It is required in fundamental tasks such as key generation, masking and hiding values, nonces and initialization vectors generation. Pseudo-random number generators have been studied by numerous authors, either to propose clear security notions and associated constructions or to point out potential vulnerabilities. In this systematization of knowledge paper, we present the three notions of generators that have been successively formalized: standard generators, stateful generators and generators with input. For each notion, we present expected security properties, where adversaries have increasing capabilities (including access to partial information on the internal variables) and we propose secure and efficient constructions, all based on the block cipher AES. In our description of generators with input, we revisit the notions of accumulator and extractor and we point out that security crucially relies on the independence between the randomness source and the seeds of the accumulator and the extractor. To illustrate this requirement, we identify a potential vulnerability of the NIST standard CTR_DRBG.

The modern financial world has seen a significant rise in the use of cryptocurrencies in recent years, partly due to the convincing lure of anonymity promised by these schemes. Bitcoin, despite being considered as the most widespread among all, is claimed to have significant lapses in relation to its anonymity. Unfortunately, studies have shown that many cryptocurrency transactions can be traced back to their corresponding participants through the analysis of publicly available data, to which the cryptographic community has responded by proposing new constructions with improved anonymity claims. Nevertheless, the absence of a common metric for evaluating the level of anonymity achieved by these schemes has led to numerous disparate ad hoc anonymity definitions, making comparisons difficult. The multitude of these notions also hints at the surprising complexity of the overall anonymity landscape. In this study, we introduce such a common framework to evaluate the nature and extent of anonymity in (crypto) currencies and distributed transaction systems, thereby enabling one to make meaningful comparisons irrespective of their implementation. Accordingly, our work lays the foundation for formalizing security models and terminology across a wide range of anonymity notions referenced in the literature, while showing how “anonymity” itself is a surprisingly nuanced concept, as opposed to existing claims that are drawn upon at a higher level, thus missing out on the elemental factors underpinning anonymity.

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• Wireless channels have become more vulnerable with rise in technology. • Layering of security concepts can improve robustness against attacks. • Combining cryptography and steganography can provide enhanced security. • Security algorithms achieve better randomness with the use of chaotic maps. • Hybrid security algorithms perform better even under adverse environments. This paper proposes a novel security algorithm which combines the concepts of Cryptography and Steganography to provide enhanced security to digital images. The proposed algorithm, named CIEST, enciphers the secret image (cryptography) which is hidden into the cover image (steganography) for secured transfer of information. A two-stage encryption process, with one of the stages being DNA encoding is used here. The cover image is also modified before the data embedding phase to improve the effectiveness of the algorithm. Multiple Combined Chaotic maps are utilised in the encryption and embedding stages to improve the randomness of the algorithm. The use of chaotic maps also makes the algorithm more robust to different types of attacks. The CIEST scheme is shown to be robust, offering high embedding capacity with high sensitivity with a near zero correlation value, information entropy value of 7.9972, maximum SSIM of 0.9992, and a maximum PSNR of 56.1071. The experimental results presented establish the immunity of the proposed method against attacks along with the feasibility and effectiveness of the algorithm in real time. [Display omitted] [ABSTRACT FROM AUTHOR]