A dynamic resource allocation decision model for IT security
Today, with the continued growth in using information and communication technologies (ICT) for business purposes, business organizations become increasingly dependent on their information systems. Thus, they need to protect them from the different attacks exploiting their vulnerabilities. To do so, the organization has to use security technologies, which may be proactive or reactive ones. Each security technology has a relative cost and addresses specific vulnerabilities. Therefore, the organization has to put in place the appropriate security technologies set that minimizes the information system s vulnerabilities with a minimal cost. This bi objective problem will be considered as a resources allocation problem (RAP) where security technologies represent the resources to be allocated. However, the set of vulnerabilities may change, periodically, with the continual appearance of new ones. Therefore, the security technologies set should be flexible to face these changes, in real time, and the problem becomes a dynamic one. In this paper, we propose a harmony search based algorithm to solve the bi objective dynamic resource allocation decision model. This approach was compared to a genetic algorithm and provided good results.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Contrasting the optimal resource allocation to cybersecurity and cyber insurance using prospect theory versus expected utility theory
Protecting against cyber-threats is vital for every organization and can be done by investing in cybersecurity controls and purchasing cyber insurance. However, these are interlinked since insurance premiums could be red…
Decision MakingSecure Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless MEC Networks
This paper proposes a blockchain-secured deep reinforcement learning (BC-DRL) optimization framework for {data management and} resource allocation in decentralized {wireless mobile edge computing (MEC)} networks. In our …
Deep Reinforcement LearningEdge-computingManagementRL-Driven Security-Aware Resource Allocation Framework for UAV-Assisted O-RAN
The integration of Unmanned Aerial Vehicles (UAVs) into Open Radio Access Networks (O-RAN) enhances communication in disaster management and Search and Rescue (SAR) operations by ensuring connectivity when infrastructure…
Reinforcement LearningGraph Neural Network Aided Deep Reinforcement Learning for Resource Allocation in Dynamic Terahertz UAV Networks
Terahertz (THz) unmanned aerial vehicle (UAV) networks with flexible topologies and ultra-high data rates are expected to empower numerous applications in security surveillance, disaster response, and environmental monit…
Deep Reinforcement LearningDisaster ResponseGraph Neural NetworkSecure Resource Allocation via Constrained Deep Reinforcement Learning
The proliferation of Internet of Things (IoT) devices and the advent of 6G technologies have introduced computationally intensive tasks that often surpass the processing capabilities of user devices. Efficient and secure…
Deep Reinforcement LearningDistributed ComputingEdge-computingreinforcement-learning+1