Malware Detection: Issues and Challenges Naseer, Muchammad; Rusdi, Jack Febrian; Shanono, Nuruddeen Musa ...
Journal of physics. Conference series,
04/2021, Letnik:
1807, Številka:
1
Journal Article
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Abstract
Malware is a severe threat that makes computer security more vulnerable. Many studies have been conducted to improve the capability of detection techniques. However, there is a lack of ...analysis of the current trend of IDS. This paper is about extracting and analyzing the latest detection techniques which had been conducted by various studies. This paper will also emphasize the current challenges of malware deployment from recent studies. Finally, the similarities and differences between the detection techniques will be exposed, and the issues and problems related to detection techniques will highlight as well. In the future, this paper outcome can be used to highlight the current topic addressed in malware research.
Big data analytics are gaining popularity in medical engineering and healthcare use cases. Stakeholders are finding big data analytics reduce medical costs and personalise medical services for each ...individual patient. Big data analytics can be used in large-scale genetics studies, public health, personalised and precision medicine, new drug development, etc. The introduction of the types, sources, and features of big data in healthcare as well as the applications and benefits of big data and big data analytics in healthcare is key to understanding healthcare big data and will be discussed in this article. Major methods, platforms and tools of big data analytics in medical engineering and healthcare are also presented. Advances and technology progress of big data analytics in healthcare are introduced, which includes artificial intelligence (AI) with big data, infrastructure and cloud computing, advanced computation and data processing, privacy and cybersecurity, health economic outcomes and technology management, and smart healthcare with sensing, wearable devices and Internet of things (IoT). Current challenges of dealing with big data and big data analytics in medical engineering and healthcare as well as future work are also presented.
As the deployment of Internet of Things (IoT) is experiencing an exponential growth, it is no surprise that many recent cyber attacks are IoT-enabled : the attacker initially exploits some vulnerable ...IoT technology as a first step toward compromising a critical system that is connected, in some way, with the IoT. For some sectors, like industry, smart grids, transportation, and medical services, the significance of such attacks is obvious, since IoT technologies are part of critical back-end systems. However, in sectors where IoT is usually at the end-user side, like smart homes, such attacks can be underestimated, since not all possible attack paths are examined. In this paper, we survey IoT-enabled cyber attacks, found in all application domains since 2010. For each sector, we emphasize on the latest, verified IoT-enabled attacks, based on known real-world incidents and published proof-of-concept attacks. We methodologically analyze representative attacks that demonstrate direct, indirect, and subliminal attack paths against critical targets. Our goal is threefold: 1) to assess IoT-enabled cyber attacks in a risk-like approach, in order to demonstrate their current threat landscape; 2) to identify hidden and subliminal IoT-enabled attack paths against critical infrastructures and services; and 3) to examine mitigation strategies for all application domains.
To ensure the safety and security of Automated Vehicles (Avs), the interaction between the Functional Safety (FuSa) and the Cybersecurity (CS) domains needs to be managed systematically. There is a ...demand to develop effective and structured management systems to support the homologation process. From this motivation, identifying the interaction between the Safety Management System (SMS) and the Cybersecurity Management System (CSMS) is a fundamental aspect and needs to be improved for HAD systems. Hence, the classical Decision Making Trial and Evaluation Laboratory (DEMATEL) method and fuzzy DEMATEL are applied to evaluate the influential factors that can impact the safety and security of the HAD systems. This paper proposes a list of influencing factors focusing on the interaction between SMS and CSMS for HAD systems. Additionally, the results of an anonymously conducted survey among experts from industry and research are presented and used as inputs for the methods. This work helps to understand the relationship between influencing factors and provides a simplified, easy-to-visualized, and valuable guide for developing HAD systems. The result of this study shows that the most important influential factor is F13. Moreover, the cause and effect of the factors are illustrated numerically and graphically. The influential factors F1 to F7 are identified as the cause and F8 to F13 are reasoned to effect. Finally, a circular representation of the influential factors and their interaction is presented in this paper.
•Identify the factors influencing the interaction between SMS and CSMS.•Classical and fuzzy DEMATEL methods are applied, and results are compared.•The cause and effect of the influential factors are presented.•The most important influential factor is determined.
Blockchain technology has seen adoption in many industries and most predominantly in finance through the use of cryptocurrencies. However, the technology is viable in cybersecurity. This paper looked ...at several use cases of Blockchain in the cybersecurity industry as envisioned by 30 researchers. It found that most researchers are concentrating on the adoption of Blockchain to protect IoT (Internet of Things) devices, networks, and data. The paper examined the ways highlighted by previous researchers through which Blockchain can afford security to the three problematic areas in IT. Lastly, the paper recommended that future researchers focus on a single Blockchain on which to develop cybersecurity applications to allow for integration and uniformity among solutions.
Technical developments in communication technology and measurement synchronization have facilitated the design of advanced protection schemes, such as Line Current Differential Relays (LCDRs). ...However, the superior performance of LCDRs is achieved at the expense of exposing them to cyber-threats, since cyber-induced intrusions against protective relays-which take advantage of the direct control of relays over circuit-breakers-can cause protection system mis-operations. To address this problem, this paper presents a Learning-based Framework (LBF) for detecting False Data Injection Attacks (FDIAs) and Time Synchronization Attacks (TSAs) against LCDRs, and for differentiating them from faults. In the proposed LBF, a Multi-Layer Perceptron (MLP) model is trained based on differential and super-imposed features, which are selected using the Recursive Feature Elimination method. After implementing the proposed LBF in LCDRs, when an LCDR picks up, it initially extracts the features and sends them to the trained MLP model. The LCDR trips the line if the proposed LBF confirms a fault. The performance of the proposed LBF is corroborated using the IEEE 39-bus test system. Evaluation results show that the proposed LBF (i) works independently of a system's operating point and configuration, (ii) is not considerably affected by instrumentation errors, and (iii) can accurately detect FDIAs and TSAs.
The development of the complexity and connectivity of modern automobiles has caused a massive rise in the security risks of in-vehicle networks (IVNs). Nevertheless, existing IVN designs (e.g., ...controller area network) lack cybersecurity consideration. Intrusion detection, an effective method for defending against cyberattacks on IVNs while providing functional safety and real-time communication guarantees, aims to address this issue. Therefore, the necessity of its research has risen. In this paper, an IVN environment is introduced, and the constraints and characteristics of an intrusion detection system (IDS) design for IVNs are presented. A survey of the proposed IDS designs for the IVNs is conducted, and the corresponding drawbacks are highlighted. Various optimization objectives are considered and comprehensively compared. Lastly, the trend, open issues, and emerging research directions are described.
•Examination of six dairy farms uncovered significant problems in farm cybersecurity.•Systematic evaluation of the farms was used as a method.•Farmers considered cyber security important, and did not ...invest in it.•There is clear need to improve cyber security at individual farms.
Agricultural cybersecurity is a rising concern because farming is becoming ever more reliant on computers and Internet access. During the last few years, the agrotechnology community, public sector, and researchers have been alerted to the problem and a significant amount of research has focused on the issue. However, the majority of the existing work focuses on external threats or specific parts of the farm technology ecosystem. This work examines the cybersecurity capabilities of individual farms and focuses on the farm local area network; the network and connected devices of six dairy farms in Finland are examined in detail. In addition, the farmers were interviewed in order to ascertain their opinions and understanding of agricultural cybersecurity. The results of the reviews were mixed. The physical cabling, for example, was all in good condition and followed appropriate regulations. On the other hand, network topology, malware protection, and system backups were not handled appropriately. Surveillance cameras typically did not work as expected. Often, the farmers did not know the network topology, the connected devices, or the details of individual devices in the network. In summary, the cybersecurity on the farms reviewed in this work was not handled optimally and significant improvements would be needed in order to secure the reviewed systems. However, since the approach of this work is qualitative in nature, care must be taken when generalizing the results. In conclusion, there is a significant need for improvements in agricultural cybersecurity on the level of individual farms. Many of the threats faced by farms are caused by their own activity or the physical environment and thus, emphasis must be put on improving their own situations.
•A comprehensive overview reflecting the emergence of Cognitive Computing (CC) and functional features of CC-based frameworks.•Identifies, summarizes, and analyses existing CC approaches in the areas ...of healthcare, cybersecurity, big data, and IoT.•Discusses open issues in contemporary research on cognitive approaches, their solutions and future scope.
Human Intelligence is considered superior compared to Artificial Intelligence (AI) because of its ability to adapt faster to changes. Due to increasing data deluge, it is cumbersome for humans to analyse the vast amount of data and hence AI systems are in demand in today's world. However, these AI systems lack self-awareness, social skills, multitasking and faster adaptability. Cognitive Computing (CC), a subset of AI, acts as an effective solution in solving these challenges by serving as an important driver for knowledge-rich automation work. Knowing the latest research and state of the art in CC is one of the initial steps needed for researchers to make progress in this front. Thus, this paper presents a comprehensive survey of prior research in the CC domain along with the challenges, solutions and future research directions. Specifically, CC-based techniques solving real-world problems in four widely-researched application areas, namely, healthcare, cybersecurity, big data and IoT, have been reviewed in detail and the open research issues are discussed.
Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was ...coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain technology from the technical perspective. We have extracted 41 primary papers from scientific databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.
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