scholarly journals Tracking Advanced Persistent Threats in Critical Infrastructures Through Opinion Dynamics

2018 ◽  
pp. 555-574 ◽  
Author(s):  
Juan E. Rubio ◽  
Rodrigo Roman ◽  
Cristina Alcaraz ◽  
Yan Zhang
Keyword(s):  
Opinion Dynamics ◽  
Critical Infrastructures ◽  
Advanced Persistent Threats

scholarly journals Cyber-Attack Scoring Model Based on the Offensive Cybersecurity Framework

2021 ◽  
Vol 11 (16) ◽  
pp. 7738
Author(s):  
Kyounggon Kim ◽  
Faisal Abdulaziz Alfouzan ◽  
Huykang Kim
Keyword(s):  
Cyber Security ◽  
Personal Information ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Infrastructures ◽  
Cyber Attack ◽  
Security Framework ◽  
Scoring Model ◽  
Advanced Persistent Threats ◽  
The World

Cyber-attacks have become commonplace in the world of the Internet. The nature of cyber-attacks is gradually changing. Early cyber-attacks were usually conducted by curious personal hackers who used simple techniques to hack homepages and steal personal information. Lately, cyber attackers have started using sophisticated cyber-attack techniques that enable them to retrieve national confidential information beyond the theft of personal information or defacing websites. These sophisticated and advanced cyber-attacks can disrupt the critical infrastructures of a nation. Much research regarding cyber-attacks has been conducted; however, there has been a lack of research related to measuring cyber-attacks from the perspective of offensive cybersecurity. This motivated us to propose a methodology for quantifying cyber-attacks such that they are measurable rather than abstract. For this purpose, we identified each element of offensive cybersecurity used in cyber-attacks. We also investigated the extent to which the detailed techniques identified in the offensive cyber-security framework were used, by analyzing cyber-attacks. Based on these investigations, the complexity and intensity of cyber-attacks can be measured and quantified. We evaluated advanced persistent threats (APT) and fileless cyber-attacks that occurred between 2010 and 2020 based on the methodology we developed. Based on our research methodology, we expect that researchers will be able to measure future cyber-attacks.

scholarly journals Expert knowledge and data analysis for detecting advanced persistent threats

2017 ◽  
Vol 15 (1) ◽  
pp. 1108-1122 ◽  
Author(s):  
Juan Ramón Moya ◽  
Noemí DeCastro-García ◽  
Ramón-Ángel Fernández-Díaz ◽  
Jorge Lorenzana Tamargo
Keyword(s):  
Data Analysis ◽  
Public Administration ◽  
Expert Knowledge ◽  
Synthetic Data ◽  
Critical Infrastructures ◽  
Data Traffic ◽  
It Infrastructure ◽  
Effective Learning ◽  
Advanced Persistent Threats ◽  
Log Files

Abstract Critical Infrastructures in public administration would be compromised by Advanced Persistent Threats (APT) which today constitute one of the most sophisticated ways of stealing information. This paper presents an effective, learning based tool that uses inductive techniques to analyze the information provided by firewall log files in an IT infrastructure, and detect suspicious activity in order to mark it as a potential APT. The experiments have been accomplished mixing real and synthetic data traffic to represent different proportions of normal and anomalous activity.

Country-Independence of Moral Arguments and Moral Opinion Dynamics

2019 ◽  
Author(s):  
Irina Vartanova ◽  
Kimmo Eriksson ◽  
Pontus Strimling
Keyword(s):  
Opinion Dynamics ◽  
Moral Arguments

scholarly journals Attack Categorisation for IoT Applications in Critical Infrastructures, a Survey

2021 ◽  
Vol 11 (16) ◽  
pp. 7228
Author(s):  
Edward Staddon ◽  
Valeria Loscri ◽  
Nathalie Mitton
Keyword(s):  
Critical Infrastructure ◽  
Attack Detection ◽  
Critical Infrastructures ◽  
Cyber Attack ◽  
Specific System ◽  
Iot Applications ◽  
War Zone ◽  
Clear Vision ◽  
The Internet Of Things ◽  
Do So

With the ever advancing expansion of the Internet of Things (IoT) into our everyday lives, the number of attack possibilities increases. Furthermore, with the incorporation of the IoT into Critical Infrastructure (CI) hardware and applications, the protection of not only the systems but the citizens themselves has become paramount. To do so, specialists must be able to gain a foothold in the ongoing cyber attack war-zone. By organising the various attacks against their systems, these specialists can not only gain a quick overview of what they might expect but also gain knowledge into the specifications of the attacks based on the categorisation method used. This paper presents a glimpse into the area of IoT Critical Infrastructure security as well as an overview and analysis of attack categorisation methodologies in the context of wireless IoT-based Critical Infrastructure applications. We believe this can be a guide to aid further researchers in their choice of adapted categorisation approaches. Indeed, adapting appropriated categorisation leads to a quicker attack detection, identification, and recovery. It is, thus, paramount to have a clear vision of the threat landscapes of a specific system.

Opinion Dynamics Optimization by Varying Susceptibility to Persuasion via Non-Convex Local Search

2021 ◽  
Vol 16 (2) ◽  
pp. 1-34
Author(s):  
Rediet Abebe ◽  
T.-H. HUBERT Chan ◽  
Jon Kleinberg ◽  
Zhibin Liang ◽  
David Parkes ◽  
...  
Keyword(s):  
Local Search ◽  
Objective Function ◽  
Iterative Process ◽  
Large Scale ◽  
Opinion Dynamics ◽  
Theoretical Models ◽  
Global Optimum ◽  
Local Optimum ◽  
Opinion Formation ◽  
Long Line

A long line of work in social psychology has studied variations in people’s susceptibility to persuasion—the extent to which they are willing to modify their opinions on a topic. This body of literature suggests an interesting perspective on theoretical models of opinion formation by interacting parties in a network: in addition to considering interventions that directly modify people’s intrinsic opinions, it is also natural to consider interventions that modify people’s susceptibility to persuasion. In this work, motivated by this fact, we propose an influence optimization problem. Specifically, we adopt a popular model for social opinion dynamics, where each agent has some fixed innate opinion, and a resistance that measures the importance it places on its innate opinion; agents influence one another’s opinions through an iterative process. Under certain conditions, this iterative process converges to some equilibrium opinion vector. For the unbudgeted variant of the problem, the goal is to modify the resistance of any number of agents (within some given range) such that the sum of the equilibrium opinions is minimized; for the budgeted variant, in addition the algorithm is given upfront a restriction on the number of agents whose resistance may be modified. We prove that the objective function is in general non-convex. Hence, formulating the problem as a convex program as in an early version of this work (Abebe et al., KDD’18) might have potential correctness issues. We instead analyze the structure of the objective function, and show that any local optimum is also a global optimum, which is somehow surprising as the objective function might not be convex. Furthermore, we combine the iterative process and the local search paradigm to design very efficient algorithms that can solve the unbudgeted variant of the problem optimally on large-scale graphs containing millions of nodes. Finally, we propose and evaluate experimentally a family of heuristics for the budgeted variant of the problem.

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