This paper aims to explore the cyber-deception-based approach and to design a novel conceptual model of hybrid threats that includes deception methods. Security programs primarily focus on prevention-based strategies aimed at stopping attackers from getting into the network. These programs attempt to use hardened perimeters and endpoint defenses by recognizing and blocking malicious activities to detect and stop attackers before they can get in. Most organizations implement such a strategy by fortifying their networks with defense-in-depth through layered prevention controls. Detection controls are usually placed to augment prevention at the perimeter, and not as consistently deployed for in-network threat detection. This architecture leaves detection gaps that are difficult to fill with existing security controls not specifically designed for that role. Rather than using prevention alone, a strategy that attackers have consistently succeeded against, defenders are adopting a more balanced strategy that includes detection and response. Most organizations deploy an intrusion detection system (IDS) or next-generation firewall that picks up known attacks or attempts to pattern match for identification. Other detection tools use monitoring, traffic, or behavioral analysis. These reactive defenses are designed to detect once they are attacked yet often fail. They also have some limitations because they are not designed to catch credential harvesting or attacks based on what appears as authorized access. They are also often seen as complex and prone to false positives, adding to analyst alert fatigue. The security industry has focused recent innovation on finding more accurate ways to recognize malicious activity with technologies such as user and entity behavioral analytics (UEBA), big data, artificial intelligence (AI), and deception.

Cybersecurity encompasses a broad range of practices, tools and concepts related closely to those of information and operational technology security. Cybersecurity is distinctive in its inclusion of the offensive use of information technology to attack adversaries. Use of the term “cybersecurity” as a key challenge and a synonym for information security or IT security confuses customers and security practitioners, and obscures critical differences between these disciplines. Recommendation for security leaders is that they should use the term “cybersecurity” to designate only security practices related to the defensive actions involving or relying upon information technology and/or operational technology environments and systems. Cyber defense is a computer network defense mechanism which includes response to actions and critical infrastructure protection and information assurance for organizations, government entities and other possible networks [3]. Within this paper, we investigate how cybersecurity and cyber defense combined may lead to cyber resilience and describe the relationships among cybersecurity, information security, operational technology (OT) security, IT security, and other related disciplines and practices e.g. cyber defense. In this regard ends, ways (processes) and means for achieving cyber resilience in today's conditions of emerging security risks are examined. Within the context of cyber resilience the novel model of cyber resilience is presented.

Information about the paper titled "DIGITAL INTELLIGENCE - NEW CONCEPT IN CONTEXT OF FUTURE OF SCHOOL EDUCATION" at IATED Digital Library

The teaching of practical foundations of computer science is still a big challenge. The course on Data Structures and Algorithms is one of the most important foundational courses that are necessary to be included in the curriculum of future IT experts. The content of this course is quite wide and it differs in many universities. In our teaching process, we identified some interesting problems that could be presented more attractively – using the visualizing software. In this paper, we present a purpose, rôle, design and methodology of our developed software tool for the convenience of teaching and studying the problem of the longest common subsequence.

We present a categorical formalization of a variant of first-order logic. Unlike other texts on this topic, the goal of this paper is to give a very transparent and self-contained account without requiring more background than basic logic and set theory. Our focus is to show how the semantics of first-order formulas can be derived from their usual deduction rules. For understanding the core ideas, it is not necessary to investigate the internal term structure of atomic formulas, thus we abstract atomic formulas to (syntactically opaque) relations; in this sense, our variant of first-order logic is “relational”. While the derived semantics is based on categorical principles (even the duality that arises from a symmetry between two ways of looking at something where there is no reason to choose one over the other), it is nevertheless “constructive” in that it describes explicit computations of the truth values of formulas. We demonstrate this by modeling the categorical semantics in the RISCAL (RISC Algorithm Language) system which allows us to validate the core propositions by automatically checking them in finite models.