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Clear Reasoning about Security

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 3164

Special Issue Editor

School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, QLD 4350, Australia
Interests: performance evaluation; cybersecurity; network design

Special Issue Information

Dear Colleagues,

In a healthy work environment, an important component of professional practice is rational discussion, in which reasoning is used to find, justify, and explain decisions. In cybersecurity, at present, reasoning is not generally clear, and consequently such a healthy environment of discussion, explanation, and consistent improvement is not widespread.

In pure mathematics, reasoning is closely aligned with the concept of proof. It is generally accepted that a pure mathematical paper or text can, in principle, be entirely constructed from definitions and theorems. The books nominally authored by N. Bourbaki (N. Bourbaki is actually an alias for a group of mathematicians) are the best example of this style. In principle, a text in this form can be re-expressed formally in the predicate calculus, also known as formal logic, or first order logic, and a relatively simple, fast algorithm can then be used to check all of the proofs. The process of completing this translation is tedious and rarely completed, but logicians understand, in principle, how to translate the semi-formal mathematical style to formal logic.

In applied mathematics, computer science, and other sciences, reasoning based on the use of mathematical notation and proof is also used, but the concept of proof is only supported informally, by being expressed in a manner similar to formal mathematics, rather than any translation into logic being contemplated. It is not agreed whether or not first-order logic is the right way to formalise proof in fields other than mathematics. It has been proposed, for example, that modal logic is more suitable for security; however, modal logic is really a family of logics, and the precise choice of modal operators and the axioms which support their use is currently a topic of research.

Surprisingly, therefore, although the term proof is frequently used in engineering, computer science, physics, and other sciences, strictly speaking the concept of proof is not clear, except in pure mathematics. Leaving aside whether reasoning is reducible to proof, if it is not clear what constitutes proof in computer science, it is also not clear what we mean by reasoning.

The fact that reasoning in computer science, or in security to be more specific, is unclear is not merely an academic problem. On a daily basis, in countless workplaces where security must be maintained, cybersecurity professionals must make decisions, adopt practices, install and configure security systems, and explain to their colleagues why they have made these decisions. In many cases, the explanations are not available, and in practice, the real reasons behind the decisions are based on authority, trust, convention, and intuition.

The fact that humans in general, and professionals in particular, base their professional practice on social networks of authority and trust should be expected. No one individual can be expected to have mastered all the knowledge and skills required to maintain the complex systems on which our society is based. Nevertheless, these networks of trust constitute a weakness which makes us vulnerable to attack and exploitation.

The common-sense interpretation of this situation is that cybersecurity is too hard to be able to fully reason about, and so our dependence on trust and authority is understandable and should be excused. However, the purpose of the scientific process is precisely to reduce our dependence on informal, and sometimes invalid, reasoning, and to replace it, wherever possible, by reasoning which is more clear and objectively justifiable. In addition, the networks of authority regarding cybersecurity are subject to self-interested influence and intimidation, authority based on power or other types of social leverage rather than objective expertise. These ineffective social strategies for managing cybersecurity inevitably fill the gap created by the absence of a rigorous, rational understanding of cybersecurity.

So, although it is unrealistic and perhaps even unhealthy not to use networks of trusted authorities as a guide for good practice in security, we should continue to improve our understanding of what constitutes sound reasoning in cybersecurity, so that these networks can be rendered safer and more reliable.

It is an undeniable fact that vague, unsatisfactory and unreliable reasoning about cybersecurity is a frequent occurrence in our workplaces at present. We have all experienced imposition or arbitrary constraints on our use of ICT systems, supposedly justified by “security”. At the same time, the discovery and use of previously undiscovered methods of attack continue to accumulate in our history of cybersecurity failures. The expected protections of the legitimate rights to privacy and security by clients of popular Internet services are regularly revealed to be missing or flawed.

In this Special Issue, we seek studies which contribute to our understanding of what constitutes valid, clear reasoning, including examples of good or bad practice, explanations of what is possible or not possible, the contribution and role, or limitations, of formal methods, and in general any contribution which can assist the academic and professional community to reason more clearly about cybersecurity.

Dr. Ron Addie
Guest Editor

Manuscript Submission Information

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Published Papers (2 papers)

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Research

23 pages, 7840 KiB  
Article
A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System
by Shih-Yu Li, Chun-Hung Lee and Lap-Mou Tam
Sensors 2023, 23(13), 5906; https://doi.org/10.3390/s23135906 - 26 Jun 2023
Cited by 1 | Viewed by 949
Abstract
In this paper, a framework for authorization and personal image protection that applies user accounts, passwords, and personal I-vectors as the keys for ciphering the image content was developed and connected. There were two main systems in this framework. The first involved a [...] Read more.
In this paper, a framework for authorization and personal image protection that applies user accounts, passwords, and personal I-vectors as the keys for ciphering the image content was developed and connected. There were two main systems in this framework. The first involved a speaker verification system, wherein the user entered their account information and password to log into the system and provided a short voice sample for identification, and then the algorithm transferred the user’s voice (biometric) features, along with their account and password details, to a second image encryption system. For the image encryption process, the account name and password presented by the user were applied to produce the initial conditions for hyper-chaotic systems to generate private keys for image-shuffling and ciphering. In the final stage, the biometric features were also applied to protect the content of the image, so the encryption technology would be more robust. The final results of the encryption system were acceptable, as a lower correlation was obtained in the cipher images. The voice database we applied was the Pitch Tracking Database from the Graz University of Technology (PTDB-TUG), which provided the microphone and laryngoscope signals of 20 native English speakers. For image processing, four standard testing images from the University of Southern California–Signal and Image Processing Institute (USC-SIPI), including Lena, F-16, Mandrill, and Peppers, were presented to further demonstrate the effectiveness and efficiency of the smart image encryption algorithm. Full article
(This article belongs to the Special Issue Clear Reasoning about Security)
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15 pages, 3065 KiB  
Article
Use of Machine Learning in Interactive Cybersecurity and Network Education
by Neil Loftus and Husnu S. Narman
Sensors 2023, 23(6), 2977; https://doi.org/10.3390/s23062977 - 9 Mar 2023
Cited by 1 | Viewed by 1895
Abstract
Cybersecurity is a complex subject for students to pursue. Hands-on online learning through labs and simulations can help students become more familiar with the subject at security classes to pursue cybersecurity education. There are several online tools and simulation platforms for cybersecurity education. [...] Read more.
Cybersecurity is a complex subject for students to pursue. Hands-on online learning through labs and simulations can help students become more familiar with the subject at security classes to pursue cybersecurity education. There are several online tools and simulation platforms for cybersecurity education. However, those platforms need more constructive feedback mechanisms, and customizable hands-on exercises for users, or they oversimplify or misrepresent the content. In this paper, we aim to develop a platform for cybersecurity education that can be used either with a user interface or command line and provide auto constructive feedback for command line practices. Moreover, the platform currently has nine levels to practice for different subjects of networking and cybersecurity and a customizable level to create a customized network structure to test. The difficulty of objectives increases at each level. Moreover, an automatic feedback mechanism is developed by using a machine learning model to warn users about their typographical errors while using the command line to practice. A trial was performed with students completing a survey before and after using the application to test the effects of auto-feedback on users’ understanding of the subjects and engagement with the application. The machine learning-based version of the application has a net increase in the user ratings of almost every survey field, such as user-friendliness and overall experience. Full article
(This article belongs to the Special Issue Clear Reasoning about Security)
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