Malware propagation effects on SCADA system and smart power grid

Akhtar, Tafseer; Gupta, Brij B.; Yamaguchi, Shingo

doi:10.1109/icce.2018.8326281

Cited by 14 publications

(6 citation statements)

References 11 publications

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“…The decentralised automation management and remote control are helpful to ensure the reliability of power supply and lower the maintenance costs of the network. There are four main parts in a typical SCADA system (Akhtar et al 2018) (a) data interface appliance like remote terminal units (RTUs) and programmable logic controllers (PLCs); (b) communication network; (c) central master terminal unit (MTU); and (d) human-machine interfaces (HMIs). RTUs and PLCs are extremely important in SCADA system.…”

Section: Key Components Of Slesmentioning

confidence: 99%

Cybersecurity in smart local energy systems: requirements, challenges, and standards

et al. 2022

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Smart local energy system (SLES) can support tailored regional solutions through the orchestration of cyber physical architectures, coordinating distributed technologies, with operational and forecasting models across all energy actors. Unprecedented access to new information, data streams and remotely accessible control can substantially benefit the multi-objective optimisation of multiple performance metrics. Given the expansion of this internet of things (IoT) and cyber-physical system (CPS), it is important to not only design effective detection and management of potential cybersecurity issues, but also to address the challenges in having affective and adaptive governance—built on standards to ensure the security of the IoT to minimise risks and harms to all users. This study conducts an extensive and critical investigation into the existing standards and identifies areas to focus on as to support the expansive adoption of cyber physical networks. Although existing standards and protocols are highly fragmented, our findings suggest that many of them can meet the requirements of the applications and infrastructures of SLES. Additionally, many standards have been introduced to protect information security and personal privacy due to their increasing importance. The research also suggests that the industry needs to produce more affordable and cyber-secured devices and services. For the government and regulators, relevant guidelines on the minimum function and security requirements for applications should be provided. Additionally, compliance testing and certifications should be in place and carried out by an independent third party to ensure the components of SLES ecosystem with a satisfied security level by design.

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Section: Key Components Of Slesmentioning

confidence: 99%

Cybersecurity in smart local energy systems: requirements, challenges, and standards

et al. 2022

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“…Sharafeev et al [1] develop an algorithm to monitor electrical power systems (EPS) cyber-attacks. A framework for assessing critical infrastructure in an attack was created by Akhtar, et al [49]. Sarangan, et al [50] Analyzed cyber-attacks of the power grid in considering the ill-effects of increasing renewable penetration [39].…”

Section: G Related Workmentioning

confidence: 99%

Predicting Cyber-Attack using Cyber Situational Awareness: The Case of Independent Power Producers (IPPs)

Matey¹,

Danquah²,

Koi-Akrofi³

2022

IJACSA

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The increasing critical dependencies on Internetof-Things (IoT) have raised security concerns; its application on the critical infrastructures (CIs) for power generation has come under massive cyber-attack over the years. Prior research efforts to understand cybersecurity from Cyber Situational Awareness (CSA) perspective fail to critically consider the various Cyber Situational Awareness (CSA) security vulnerabilities from a human behavioural perspective in line with the CI. This study evaluates CSA elements to predict cyber-attacks in the power generation sector. Data for this research article was collected from IPPs using the survey method. The analysis method was employed through Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the proposed model. The results revealed negative effects on people and cyber-attack, but significant in predicting cyber-attacks. The study also indicated that information handling is significant and positively influences cyber-attack. The study also reveals no mediation effect between the association of People and Attack and Information and Attack. It could result from an effective cyber security control implemented by the IPPs. Finally, the study also shows no sign of network infrastructure cyber-attack predictions. The reasons could be because managers of IPPs had adequate access policies and security measures in place.

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“…Malware has seen significant development in recent years, making it more complex than ever. Malware has impacted domains as diverse as cloud services, smart grids, financial institutions, and cryptocurrency mining [40][41][42] . Due to the widespread usage of Android OS-based smart devices (70% market share in the mobile OS industry), they have become a prime target for malware developers.…”

Section: Related Workmentioning

confidence: 99%

AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems

Rafiq

Aslam

Aleem

et al. 2022

Sci Rep

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Due to the widespread usage of Android smartphones in the present era, Android malware has become a grave security concern. The research community relies on publicly available datasets to keep pace with evolving malware. However, a plethora of apps in those datasets are mere clones of previously identified malware. The reason is that instead of creating novel versions, malware authors generally repack existing malicious applications to create malware clones with minimal effort and expense. This paper investigates three benchmark Android malware datasets to quantify repacked malware using package names-based similarity. We consider 5560 apps from the Drebin dataset, 24,533 apps from the AMD and 695,470 apps from the AndroZoo dataset for analysis. Our analysis reveals that 52.3% apps in Drebin, 29.8% apps in the AMD and 42.3% apps in the AndroZoo dataset are repacked malware. Furthermore, we present AndroMalPack, an Android malware detector trained on clones-free datasets and optimized using Nature-inspired algorithms. Although trained on a reduced version of datasets, AndroMalPack classifies novel and repacked malware with a remarkable detection accuracy of up to 98.2% and meagre false-positive rates. Finally, we publish a dataset of cloned apps in Drebin, AMD, and AndrooZoo to foster research in the repacked malware analysis domain.

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Malware propagation effects on SCADA system and smart power grid

Cited by 14 publications

References 11 publications

Cybersecurity in smart local energy systems: requirements, challenges, and standards

Cybersecurity in smart local energy systems: requirements, challenges, and standards

Predicting Cyber-Attack using Cyber Situational Awareness: The Case of Independent Power Producers (IPPs)

AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems

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