Need For Cybersecurity Research Articles

Centralization potential of automotive E/E architectures

Current automotive E/E architectures are subject to significant transformations: Computing-power-intensive advanced driver-assistance systems, bandwidth-hungry infotainment systems, the connection of the vehicle with the internet and the consequential need for cyber-security drives the centralization of E/E architectures. A centralized architecture is often seen as a key enabler to master those challenges. Available research focuses mostly on the different types of E/E architectures and contrasts their advantages and disadvantages. There is a research gap on guidelines for system designers and function developers to analyze the potential of their systems for centralization. The present paper aims to quantify centralization potential reviewing relevant literature and conducting qualitative interviews with industry practitioners. In literature, we identified seven key automotive system properties reaching limitations in current automotive architectures: busload, functional safety, computing power, feature dependencies, development and maintenance costs, error rate, modularity and flexibility. These properties serve as quantitative evaluation criteria to estimate whether centralization would enhance overall system performance. In the interviews, we have validated centralization and its fundament – the conceptual systems engineering – as capabilities to mitigate these limitations. By focusing on practical insights and lessons learned, this research provides system designers with actionable guidance to optimize their systems, addressing the outlined challenges while avoiding monolithic architecture. This paper bridges the gap between theoretical research and practical application, offering valuable takeaways for practitioners.

Cyber Resilience Act 2022: A silver bullet for cybersecurity of IoT devices or a shot in the dark?

Internet of Things (IoT) is an ecosystem of interconnected devices (IoT devices) that is capable of intelligent decision making. IoT devices can include everyday objects such as televisions, cars and shoes. The interconnectedness brought forth by IoT has extended the need for cybersecurity beyond the information security realm into the physical security sphere. However, ensuring cybersecurity of IoT devices is far from straightforward because IoT devices have several cybersecurity challenges associated with them. Some of the pertinent cybersecurity challenges of IoT devices in this regard relate to: (i) Security During Manufacturing, (ii) Identification and Authentication, (iii) Lack of Encryption, (iv) Large Attack Surface, (v) Security During Updates, (vi) Lack of User Awareness and (vii) Diverging Standards and Regulations.Against this background, the Cyber Resilience Act (CRA) has been proposed to complement the existing EU cybersecurity framework consisting of legislations such as the Cybersecurity Act and the NIS2 Directive. However, does the CRA provide a framework for effectively combating the cybersecurity challenges of IoT devices in the EU? The central crux of the CRA is to lay down and enforce the rules required to ensure cybersecurity of ‘products with digital elements’, which includes IoT devices. To this end, several obligations are imposed on manufacturers, importers and distributors of IoT devices. Manufacturers are mandated to ensure that the essential cybersecurity requirements prescribed by the CRA are met before placing IoT devices in the market. While the cybersecurity requirements mandated by the CRA are commendable, the CRA suffers from several ambiguities which can hamper its potential impact. For instance, the CRA could provide guidance to manufacturers on how to conduct cybersecurity risk assessment and could clarify the meanings of terms such as “limit attack surfaces” and “without any known exploitable vulnerabilities”.When the fundamental themes of the CRA is analysed from the prism of the cybersecurity challenges of IoT devices, it becomes clear that the CRA does provide a foundation for effectively addressing the cybersecurity challenges of IoT devices. However, the expansive wording in various parts of the CRA, including in the Annex I Requirements, leaves scope for interpretation on several fronts. Consequently, the effectiveness of the CRA in tackling the Security During Manufacturing Challenge, Identification and Authentication Challenge, Large Attack Surface Challenge and Diverging Standards and Regulations Challenge would be largely contingent on how harmonised standards develop and how the industry adopts them. The CRA seems to be more effective, albeit not fully so, in significantly addressing the Lack of Encryption Challenge, Security During Updates Challenge and Lack of User Awareness Challenge of IoT devices. However, the manner in which the CRA addresses all these cybersecurity challenges could be improved upon if an agency such as the ENISA was given the legal mandate to set elaborate standards for cybersecurity requirements under the CRA.

Transformasi Partisipasi Politik Masyarakat Desa melalui E-Voting dalam Pemilihan Kepala Desa di Desa Sibolangit, Kecamatan Merek

This study aims to examine the transformation of political participation in the village community through e-voting in the election of village heads in Sibolangit Village, Merek Subdistrict. The research method used is qualitative, employing data collection techniques such as interviews, observations, and document analysis. The research participants include village residents, election organizers, and local authorities. The findings reveal that the implementation of e-voting has significantly transformed political participation among the village community. E-voting has increased voter turnout, streamlined the voting process, and enhanced transparency and accountability in the election process. Additionally, it has empowered marginalized groups, such as women and youth, by providing them with easier access to participate in the electoral process. However, challenges such as digital literacy gaps and concerns over cybersecurity need to be addressed to ensure the effectiveness and inclusivity of e-voting. Overall, e-voting has the potential to democratize the electoral process and strengthen grassroots democracy in Sibolangit Village.

Automated Matching Skills to Improve the Accuracy of Job Applicant Selection Using Indonesian National Work Competency Standards

The high number of cyberattack anomalies and data leaks in Indonesia increases the need for cybersecurity in various companies. Cybersecurity capabilities and skills in Indonesia are divided into three categories based on the Indonesian National Work Competency Standards (SKKNI), namely Security Operation Center (SOC), Cybersecurity test/Penetration testing (Pentest), and Information Security Audit. Although various approaches have been applied in different companies to select job applicants, a new method with automated matching is explored in this study. This method matches the skills possessed by prospective job applicants with the profile of their job task requirements based on the SKKNI Decree of the Minister of Manpower of the Republic of Indonesia using Machine Learning (ML) models. The empirical comparison of results comes from automated matchmaking processed by Multinomial Naive Bayes (MNB) and Decision Tree algorithm models. Before modeling, the data is trained and evaluated for testing. Then to assess the most optimal algorithm between MNB and Decision Tree, a confusion matrix is proposed and used to find the best model. From the evaluation results, both models performed well and were highly accurate during training and test evaluation. The Decision Tree model performs slightly better than the MNB model, but both still provide satisfactory results in classifying data based on the Indonesian National Work Competency Standards (SKKNI) categories. This study offers a solution to minimize the number of potential applicants who are not competent in the three SKKNI cybersecurity job categories due to the mismatch of their abilities and skills.

The Need for Cybersecurity in Automotive Industry

This research paper analyzes the importance of cybersecurity in the automotive industry and explains how cybersecurity threats impact the modern world of connected, autonomous, and electrical vehicles. Furthermore, this paper covers in-depth research into the different types of automotive cyber threats such as physical, sensor, software, and network attacks on a vehicle, and various methods to prevent these threats from happening in real-world scenarios. The research paper also helps the reader to gain a broader understanding of cybersecurity in the automotive world. The methodology of this research involved analyzing and collecting information through various external websites, articles, and research papers. Information was collected on automotive cybersecurity incidents from news articles and international cyber security conference presentations. Based on this evidence from various external sources, the research problem was supported by factual data. This paper also talks about all the various solutions to cybersecurity threats in depth such as authentication and encryption, malware detection, software analysis, VPNs (Virtual Private Network), and cryptography. This paper also provides information about some of the new regulations and standards that are currently adopted in the automotive industry. With the rapid change in automotive technology, it is important to be aware that cars can have up to 150 ECUs (Electronic Control Unit) and about 300 million lines of code in near future which could expose more vulnerabilities. (2020, McKinsey & Company). To meet the challenge of these automotive cyber security threats, it is important that awareness should be created among the product engineers and researchers working on future automobiles. This paper attempts at exploring the challenges with automotive cyber security and creating this awareness.

Empowering Security with Machine Learning for Ransomware and Malware Detection

Due to the increase and frequency of network attacks, network security protection needs to be established[1]. The project focuses on using machine learning technology to detect ransomware and malware and aims to improve computer security. This work involves using advanced algorithms and models to analyze different types of data to identify patterns associated with crime. The proposed system extracts relevant features from various data points, including archive behavior, network traffic, and physical interactions. These features are used to train machine learning models to distinguish between good behavior and bad behavior. By constantly learning and updating, the model improves accuracy over time and stays ahead of evolving ransomware and malware threats. This project aims to contribute to the field of cybersecurity by providing efficient and effective methods to detect and mitigate threats. The use of machine learning-based search engines should improve defense against cyber attacks, ultimately protecting sensitive data and ensuring the integrity of computer systems[2]. This research aligns with the growing need for cybersecurity in response to new solutions to combat the evolution of malware. Key Words: Cybersecurity, Ransomware detection, Malware detection, Machine learning techniques, Advanced algorithms, Data analysis, Feature extraction, Model training, Continuous learning, Threat detection, Defence mechanisms

An optimal secure defense mechanism for DDoS attack in IoT network using feature optimization and intrusion detection system

Now, the Cyber security is facing unprecedented difficulties as a result of the proliferation of smart devices in the Internet of Things (IoT) environment. The rapid growth in the number of Internet users over the past two decades has increased the need for cyber security. Users have provided new opportunities for attackers to do harm. Limited security budgets leave IoT devices vulnerable and easily hacked to launch distributed denial-of-service (DDoS) attacks, with disastrous results. Unfortunately, due to the unique nature of the Internet of Things environment, most security solutions and intrusion detection systems (IDS) cannot be directly adapted to the IoT with acceptable security performance and are vulnerable to various attacks that do not benefit. In this paper we propose an optimal secure defense mechanism for DDoS in IoT network using feature optimization and intrusion detection system (OSD-IDS). In OSD-IDS mechanism, first we introduce an enhanced ResNet architecture for feature extraction which extracts more deep features from given traffic traces. An improved quantum query optimization (IQQO) algorithm for is used feature selection to selects optimal best among multiple features which reduces the data dimensionality issues. The selected features have given to the detection and classification module to classify the traffic traces are affected by intrusion or not. For this, we design a fast and accurate intrusion detection mechanism, named as hybrid deep learning technique which combines convolutional neural network (CNN) and diagonal XG boosting (CNN-DigXG) for the fast and accurate intrusion detection in IoT network. Finally, we validate the performance of proposed technique by using different benchmark datasets are BoNeSi-SlowHTTPtest and CIC-DDoS2019. The simulation results of proposed IDS mechanism are compared with the existing state-of-art IDS mechanism and analyze the performance with respects to different statistical measures. The results show that the DDoS detection accuracy of proposed OSD-IDS mechanism is high as 99.476% and 99.078% for BoNeSi-SlowHTTPtest, CICDDoS2019, respectively.

A CNN-RF Hybrid Model for Intrusion Detection System: Analysis, Improvements, and Application

With the rapid development of technologies and the growing need for the internet in most aspects of life, the need for cyber security is also growing. There are various types of cyber intrusions attacks making detecting and identifying these attacks not an easy task. Conventional intrusion detection systems (IDS) lack accuracy, which makes them unreliable and dependable. Recent applications of machine learning techniques have rapidly grown in the recent years, made it a powerful tool that can be utilized for detecting cyber intrusion attack accurately. This paper proposed an enhanced convolution neural networks (CNNs)-based machine learning model for intrusion detection. This model makes use of the characteristics of CNN layers for extracting useful features and the Random Forest model for Robust intrusion attack detection. The model utilizes the NSL-KDD dataset, and it outperforms other deep learning (DL) techniques in the multi-class classification tasks, it can identify intrusion attacks with high precision and reach 99.3% accuracy rate leading for increasing the efficiency of intrusion detection and open new avenues for research.

SİYASİ MANİPÜLASYONUN SİYASİ BİGİ SALGININA DÖNÜŞME RİSKİ: Z KUŞAĞI İÇİN ÖNLEMLER

TThis article examines the notion of infodemic in relation to political manipulation, specifically focusing on Generation Z as a case study. The analysis is based on relevant literature and utilizes an inductive approach. The initial segment emphasizes the significance of mass communication and social media in the dissemination of information. Additionally, the paper delves into artificial intelligence and cybersecurity, specifically addressing the potential dangers of infodemics. Research literature indicates that Generation Z is more vulnerable to disinformation disseminated through social media platforms. Hence, it is imperative for lawmakers and members of Generation Z to actively engage in tackling this matter. Media literacy is promoted to empower Generation Z in discerning between reality and fiction. The article advocates for the development of analytical thinking skills and underscores the significance of discerning between different sources of information and trustworthy news outlets. Furthermore, there is a strong emphasis on adhering to regulations pertaining to the utilization of social media. In essence, it asserts that cooperation is required to safeguard Generation Z against political information breakouts and manipulations that may give rise to issues regarding democratic norms and societal repercussions. Additionally, greater investigation into this subject is important.

Identifying and Protecting Cyber-Physical Systems’ Influential Devices for Sustainable Cybersecurity

For sustainable cyber-physical systems (CPS) security, proactive measures to cybersecurity need to be implemented instead of reactive measures. Towards this, we introduce in this paper a proactive methodology implemented in a system called IDI_CPS. It is based on the observation that CPS devices that have LAN-based network sharing (e.g., via Wi-Fi connections) need first to be clustered using some clustering criterion. Then, the influential and central devices in these clusters need to be identified to pay more attention to their file sharing. These influential devices may have network sharing with devices at the WAN level. Therefore, the influential devices at the WAN level that have network sharing with the influential devices in the clusters need also to be identified to pay more attention to their file sharing. We propose novel techniques for: (1) clustering the devices that have LAN-based network sharing using k-clique modeling, (2) employing clustering coefficient-based techniques for identifying the most influential device in each cluster, and (3) employing Independent Cascades model-based techniques for identifying the influential devices at the WAN level that have network sharing with the influential devices in the clusters. We experimentally evaluated our proposed system IDI_CPS and compared it with four comparable methods. Results showed marked improvement.

Analisis Objek Vital, Pengamanan File, dan Pengamanan Cyber Pada PT. Krakatau Steel Cilegon

Acts of theft at PT Krakatau Steel Cilegon can negatively affect the company's production and operations. Theft activities can also threaten industry sustainability, disrupt supply chains, and affect price stability. So that it can create security vulnerabilities, both in terms of strategic information, as well as in maintaining the security of physical facilities and employees. Cases of theft of national vital objects have increased in recent years. Theft can be committed by internal or external parties, including employees, contractors, or other parties. The motivation for theft can be varied, ranging from gaining profit, to obtaining sensitive information. File security and cyber security need to be carried out by the company PT Krakatau Steel Cilegon to handle cases of theft of the company's physical assets.

Cyber Attacks in Cyber-Physical Microgrid Systems: A Comprehensive Review

The importance of and need for cyber security have increased in the last decade. The critical infrastructure of the country, modeled with cyber-physical systems (CPS), is becoming vulnerable because of a lack of efficient safety measures. Attackers are becoming more innovative, and attacks are becoming undetectable, thereby causing huge risks to these systems. In this scenario, intelligent and evolving detection methods should be introduced to replace basic and outworn methods. The ability of artificial intelligence (AI) to analyze data and predict outcomes has created an opportunity for researchers to explore the power of AI in cyber security. This article discusses new-age intelligence and smart techniques such as pattern recognition models, deep neural networks, generative adversarial networks, and reinforcement learning for cyber security in CPS. The differences between the traditional security methods used in information technology and the security methods used in CPS are analyzed, and the need for a transition into intelligent methods is discussed in detail. A deep neural network-based controller that detects and mitigates cyber attacks is designed for microgrid systems. As a case study, a stealthy local covert attack that overcomes the existing microgrid protection is modeled. The ability of the DNN controller to detect and mitigate the SLCA is observed. The experiment is performed in a simulation and also in real-time to analyze the effectiveness of AI in cyber security.

Security in IoT systems using natural language processing: Future challenges and directions

The internet of things (IoT) is advancing human lives by providing various intelligent services. The advancement of cutting‐edge technologies necessitates an increase in the need for cyber security. In this light, an extensive research has been conducted to address IoT security concerns. However, several security challenges must be addressed before IoT can be utilized to its full potential in real‐time. Motivated by this fact, this study presents a novel integration approach of Natural Language Processing (NLP) with IoT systems to enhance its security. It investigates the current state of NLP and its applications. The key contribution of this paper is the development of a system for identifying malicious behaviors in an IoT environment using n‐gram and word‐embedding techniques. Several security challenges and possible future directions to enhance IoT security using NLP are also addressed in this study.

The Impact of Cyber Attack on Emergency Energy System

An emergency energy system is a backup power system used in critical situations with the aim of protecting lives and property from the consequences of energy loss, as is the case in hospitals (heart monitors, Ventilator,…etc), and also in sensitive facilities (military industries and government buildings). The emergency power system can contain batteries of all kinds, in addition to solar and wind energy equipment and other cheap types of energy. The concept of cyber security arose several decades after the invention of the computer. At first, there was no need for cyber security, as it was difficult for electronic attacks to occur, because access to computers was limited to specific numbers of users, as the devices were giant confined to a room with certain specifications and were not Linked to networks at the time, Energy sectors expose themselves to a range of cyber threats that can damage control systems. So management, engineering, and IT must adhere to a comprehensive approach that includes threat prevention, detection, and elimination. In this research we will try to mitigate the effects of the cyber attack on these systems by applying some algorithms in order to detect, identify and prevent such attacks, and we will see through the results we obtained that we have made remarkable progress in this field.

КІБЕРБЕЗПЕКА ЯК НАПРЯМОК ЗАХИСТУ ІНФОРМАЦІЙНОКОМУНІКАЦІЙНОГО СЕКТОРУ В СУЧАСНИХ УМОВАХ

Ensuring the protection of the information and communication sector is an important component in the country's economic growth and further progress. The issue of cyber security of the information and communication sector stands out as an important direction both at the international and at the state level. In times of war, cyber threats can have serious consequences, including financial losses, reputational damage, legal liabilities, and risks to both national security and individual sectors. It is analyzed the progress of Ukraine in cyber security based on such indicators as general security indicators, basic cyber security indicators, incident and crisis management indicators in the article. According to the Global ICT Regulatory Outlook, Ukraine ranks low in the regulation of the studied area – 78th out of 96 countries. However, Ukraine has made significant progress in cyber security, as highlighted by the Global Cyber Security Index. According to most of the general indicators, full implementation is highlighted, among the basic indicators there is a need to increase the protection of digital services, according to the indicators of incident and crisis management, military cyber operations and cyber crisis management are the least developed. Cyber threats can result in significant consequences during times of war, including financial loss, reputational damage, legal liabilities, and risks to national security. At the beginning of the war, more than 120 powerful cyber attacks on the resources of state authorities and military administration of Ukraine, as well as IT systems of critical infrastructure facilities, communication operators and mass media. Despite the positive developments, the country still faces challenges, especially in the area of protection of digital services, for which there is no competent supervisory authority. The need for cyber security in the information and communication sector and measures that can be taken to increase cyber resilience are highlighted, especially in the area of protection of digital services. Parties should cooperate with the government to improve cyber resilience. Cooperation may include sharing threat information, best practices, and resources, and coordinating incident response and recovery efforts. The issue of cyber defense of the economy in the conditions of a full-scale Russian invasion of Ukraine is gaining special relevance and is allocated to a separate direction of state policy.

A Lurking Threat: Counselor Practices to Guard Against Cyber Threats

As a result of shifts in global power, the growth of cyber capabilities worldwide, and the impact of COVID-19 on the increasing use of technology in varied workplaces, the potential for threat and disruption to mental health facilities is expected to increase. Counselors and their clients are vulnerable to these threats any time they share data online with each other, with third-party payers, and with allied health professionals. In fact, any private information stored digitally is potentially at risk for exploitation or theft. This current environment highlights the need for an intentional process and approach that can help mental health counselors understand their digital assets and vulnerabilities in order to anticipate and protect against potential cyber threats. This type of process can be facilitated through the application of cyber intelligence and cybersecurity principles to online counseling services in order to address ethical and legal obligations of counselors and to assuage client fears about potential privacy breaches. When counselors keep client data safe, Health Information Portability and Accountability Act and Family Educational Rights and Privacy Act violations are less likely to occur in a variety of settings where clients may be seen. An overview of the need for cybersecurity, a framework for bolstering cybersecurity, and specific guidelines for counselors are provided.

INDIA’S GROWING CYBER PARTNERSHIPS AND CHALLENGES FOR PAKISTAN

With the emergence of new technologies, the potential of cyberspace is immense; however, the growing number of cyber-attacks on states’ critical infrastructure has highlighted the need for cyber security. Although it is challenging to achieve foolproof security, states can maximise safety in the cyber domain through cyber partnerships with technologically advanced countries. This study finds that India is maximising its cyber security while enhancing its offensive cyber capabilities by concluding agreements with most cyber-secure states. Furthermore, India’s cyber capabilities are more focused on Pakistan due to longstanding tensions between the two countries. On the other hand, Pakistan lacks focus on cyber security and has yet to take sufficient measures. Pakistan can maximise its cyber security through technological advancements and taking advantage of friendly countries' expertise in the cyber security domain. Cyber security partnerships will strengthen Pakistan against threats emerging from state and non-state actors. Following a qualitative exploratory research design, this study provides a detailed understanding of India’s growing cyber security partnership and cyber posture, besides highlighting Pakistan’s approach towards cyber security. Bibliography Entry Farooq, Ammad and Ahmad Ali. 2022. "India’s Growing Cyber Partnerships and Challenges for Pakistan." Margalla Papers 26 (2): 49-61.

Need for Cybersecurity Awareness in Rural Communities: A Socio-Legal Perspective

The cyberspace and its awareness have been expanding vastly since its entrance into the common world. There is now so much that can be done in the cyberspace and so many ways to use the Internet, wherein there have been rapidly increasing numbers of cyber-crimes and exploitations. Cyber-attacks are becoming more common and it is only the educated and urban communities who have information regarding how to prevent and/or face the attacks. There is an ever-growing need to push the concept of cyber-security to the rural regions in any country, there is a need to educate on the dangers of the cyber-world. As internet connectivity is reaching rural areas now, there is a higher risk of cyber-threats as well. The paper aims to enunciate the dangers of the cyber-space and the need for cyber-security in rural regions in India. It will layout the existing legal framework on cyber-security in India which the author will attempt to critically analyse. The paper will also contain recommendations on how to address the issue and aims to positively make a difference in the use of the cyber-space.

The Need for Cybersecurity in Industrial Revolution and Smart Cities

Cities have grown in development and sophistication throughout human history. Smart cities are the current incarnation of this process, with increased complexity and social importance. This complexity has come to involve significant digital components and has thus come to raise the associated cybersecurity concerns. Major security relevant events can cascade into the connected systems making up a smart city, causing significant disruption of function and economic damage. The present paper aims to survey the landscape of scientific publication related to cybersecurity-related issues in relation to smart cities. Relevant papers were selected based on the number of citations and the quality of the publishing journal as a proxy indicator for scientific relevance. Cybersecurity will be shown to be reflected in the selected literature as an extremely relevant concern in the operation of smart cities. Generally, cybersecurity is implemented in actual cities through the concerted application of both mature existing technologies and emerging new approaches.

Rain Drop Service and Biometric Verification Based Blockchain Technology for Securing the Bank Transactions from Cyber Crimes Using Weighted Fair Blockchain (WFB) Algorithm

Cybercrime is an online crime committing fraud, stealing identities, violating privacy or hacking the personal information. A high level of information security in banking can be attained through striving to achieve an integrity, confidentiality, availability, assurance, and accountability. This Pandemic situation (COVID-19) paved the way for the customers to avoid traditional ways of banking and adapt to digital transactions. This banking digitalization increases in the utilization of cashless transactions like digital money (Cryptocurrency). Cyber security is imperative to preserve sensitive information, therefore, Blockchain technology has been adapted to provide security. Transactions done via Blockchain are tested through every block, which makes transactions secure and helps the banking system to work faster. The proposed algorithm WFB is used to estimate the average queue rate and avoid unwanted block generation. Then the trapezoidal fuzzy technique optimizes the allocation of blocks. An objective of this investigation is to enhance the security in banking systems from Cybercrimes by verifying Rain Drop Service (RDS) and Fingerprint Biometric without the need of any central authority. Once the service is completed, the service is a dropout and the following new service will be provided (Hence the name RDS). For the strong authentication scheme to fight against bank fraud, RSA encryption technique has been implemented successfully. Therefore, Blockchain technology increases the need for cyber security as a part of design architecture which intends to detect the stemming attacks in real time instead of repairing the damage.