Special Issue on “Advances in Self Protecting Systems”
• 大类 : 工程技术 - 2区
• 小类 : 计算机：理论方法 - 2区
Effectively protecting computer systems from cyber-attacks is a challenging task due to their large scale and the heterogeneity of the underlying hardware and software components. Furthermore, when trying to defend from an attack, the time factor is critical, and any non-guided human resolution attempt could introduce a significant stress and delay to the execution of the proper response. This situation provides the attackers more time to accomplish their objectives.
Several organizations, including the National Institute of Standards and Technology (NIST), have released guidelines and best practices to manage cyber-security related risk (e.g., the NIST Cybersecurity Framework 1.1). However, despite a growing interest in the area in the last 4-5 years, automation of cyber-security operations is still at its early stages.
Automatically defending a computer system encompasses a large number of activities, that range from data capture, management and analysis, to automated decision making and automated system operations.
In this special issue, we solicit high quality contributions that fit with the overarching idea of creating a fully automated protection system based on the Monitor, Analyze, Plan, Execute (MAPE) loop, control theory, bio-inspired solutions, Self-Regenerative Systems, and the like.
Selected papers of the 1st Int. Workshop on Self-Protecting Systems (SPS-2019) are invited to submit an extended version of their work.
Topics of interest for the special issue are:
Distributed and secure data collection and storage for sensing/monitoring
Automated Feature Selection approaches to reduce data dimensionality on cyber-security relevant data
Techniques for automatic correlation of data streams
Self-Evolving Anomaly-Based and Signature-Based Network/Host Intrusion Detection Systems
Attack and defense modeling for threats detection and risk management
Self-Evolving Model-based and Model-free Intrusion response
Attack and defense modeling for reactive and proactive intrusion response
Foundational results for self-protecting systems: Algorithms, artificial intelligence, biological-inspired techniques, control theory, machine learning, operation research, probability and stochastic processes, queueing theory, rule-based systems, and socially-inspired techniques
Software engineering for self-protecting systems: System architectures, services, components and platforms, Goal specification and policies, modeling of security-level agreements, behavior enforcement, IT governance, and security-driven IT management
Self-organizing and organic computing for self-protecting systems: Self-organization principles and organic computing principles borrowed from systems theory, control theory, game theory, decision theory, social theories, biological theories, etc. ; Self-organization, emergent behavior, decentralized control, individual and social/organizational learning, scalability, robustness, goal- and norm-governed behavior, online self-integration for trustworthy self-organizing and organic systems; Infrastructures and architectures for self-organizing systems and organic computing systems.
Implementation of prototypes that integrate cutting edge technologies, e.g., Software Defined Networks, Cloud/Fog/edge computing, Artificial Intelligence, micro-services
Holistic perspective on self-protecting systems i.e., researches that consider the overall picture and propose novel software architectures, frameworks and technologies to ease the realization of self-protecting systems.