Understanding the Impact of Cyber Security Risks on Safety

Izuakor, Christine

doi:10.5220/0005796805090513

Cited by 2 publications

(2 citation statements)

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“…The risk management process involves three major steps, that is, risk identification, risk assessment, and risk mitigation. 19 Risk identification can be done via misuse cases, by applying safety hazard analysis methods including fault tree analysis, 20 systematic theoretic process analysis, 21 hazard operative, 22 and failure mode effect analysis, 23 among others. In CPS, risks can be introduced through intrusions from hackers, malfunctioning, software issues, hardware, or network failure.…”

Section: Related Workmentioning

confidence: 99%

“…The related work consists of three parts based on the literature: safety security risk management process, safety security requirements and related standards. The risk management process involves three major steps, that is, risk identification, risk assessment, and risk mitigation 19 . Risk identification can be done via misuse cases, by applying safety hazard analysis methods including fault tree analysis, 20 systematic theoretic process analysis, 21 hazard operative, 22 and failure mode effect analysis, 23 among others.…”

Section: Related Workmentioning

confidence: 99%

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Safety and security risks management process for cyber‐physical systems: A case study

Inayat

Farooq

Inayat

2022

J Software Evolu Process

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Cyber‐physical systems (CPS) are applicable in emerging industries such as health, energy, autonomous vehicles, and Industrial Internet of Things (IIOT). In CPS the physical assets, that is, actuators and sensors, etc. communicate with each other over a messaging protocol. This communication process of CPS makes them vulnerable to cyber‐attacks which challenge the system safety, making security and safety two major concerns for CPS. Both safety and security risks are considered separately in literature. However, the International Society of Automation (ISA) focuses on the alignment of security and safety risks of CPS. Weak or no alignment in safety and security of a system may result in an inefficient or partially protected system which could end up in disasters. This pressed the need for an integrated safety‐security risk management process. For this purpose, we used a tetra packaging case study to (i) examine the vulnerabilities of CPS by running the risk management process, (ii) identify safety‐security requirements, and (iii) align retrieved safety‐security requirements with the relevant standards. The results show (i) safety hazards and security risks along with their severity and priority, (ii) mitigation guidelines are provided by consulting IEC 61508, and (iii) 15 safety‐security requirements are identified and are aligned with ISO9001 Packaging and labeling machine standard.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Safety and security risks management process for cyber‐physical systems: A case study

Inayat

Farooq

Inayat

2022

J Software Evolu Process

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A hybrid machine learning method for increasing the performance of network intrusion detection systems

Megantara

Ahmad

2021

J Big Data

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The internet has grown enormously for many years. It is not just connecting computer networks but also a group of devices worldwide involving big data. The internet provides an opportunity to make various innovations for any sector, such as education, health, public facility, financial technology, and digital commerce. Despite its advantages, the internet may contain dangerous activities and cyber-attacks that may happen to anyone connected through the internet. To detect any cyber-attack intrudes on the network system, an intrusion detection system (IDS) is applied, which can identify those incoming attacks. The intrusion detection system works in two mechanisms: signature-based detection and anomaly-based detection. In anomaly-based detection, the quality of the machine learning model obtained is influenced by the data training process. The biggest challenge of machine learning methods is how to build an appropriate model to represent the dataset. This research proposes a hybrid machine learning method by combining the feature selection method, representing the supervised learning and data reduction method as the unsupervised learning to build an appropriate model. It works by selecting relevant and significant features using feature importance decision tree-based method with recursive feature elimination and detecting anomaly/outlier data using the Local Outlier Factor (LOF) method. The experimental results show that the proposed method achieves the highest accuracy in detecting R2L (i.e., 99.89%) and keeps higher for other attack types than most other research in the NSL-KDD dataset. Therefore, it has a more stable performance than the others. More challenges are experienced in the UNSW-NB15 dataset with binary classes.

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Understanding the Impact of Cyber Security Risks on Safety

Cited by 2 publications

References 0 publications

Safety and security risks management process for cyber‐physical systems: A case study

Safety and security risks management process for cyber‐physical systems: A case study

A hybrid machine learning method for increasing the performance of network intrusion detection systems

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