Layer Security Research Articles

GRU-based digital twin framework for data allocation and storage in IoT-enabled smart home networks

In recent years, the Internet of Things (IoT) devices utilization with Information Communication Technology (ICT) has grown exponentially in various Smart City applications, including Smart Homes, Smart Enterprises, and others. The fusion of IoT, ICT, and Smart Home delivers interactive solutions to reduce costs and resource consumption, enhance performance, and engage people's needs more virtually and proactively. A smart home has numerous advantages with the integration of emerging advanced technologies. Big data, centralization, data and resource allocation, security, and privacy issues persist as challenges in IoT-enabled Smart Home Networks. To address these challenges, in this paper, we propose a GRU-based Digital Twin Framework for Data Allocation in IoT-enabled Smart Home Networks. Data and resource allocation of smart home applications are completed at the virtual twin layer using Gated Recurrent Unit (GRU)-based Digital Twin Networks. Low-priority data is stored and processed at the Macro-based Stations (MBSs), and high-priority data is transferred to the upper (Security) layer for authentication and validation. Blockchain-based distributed networks are utilized for Smart Home Data authentication at the security layer with a Proof of Authentication (PoAh) Consensus Algorithm; Data is stored at the cloud layer after validation. The validation results of the proposed framework demonstrate superior performance as the quantitative analysis with accuracy 0.9412, Root Mean Square Error (RMSE) 0.0588 for IoT-enable Smart Home compared to existing works as LSTM-based Digital Twin network and provide a secure environment in IoT-enabled Smart Home.

Chance-constrained vulnerability assessment of smart water distribution systems against stealthy false data injection attacks

Smart water distribution systems (SWDSs) have not only enhanced the monitoring and control of the entire water infrastructure but have also jeopardized its security and resilience. The state-of-the-art examined the uncertainties in the water supply network to obtain optimal design parameters to ensure hydraulic integrity. However, the investigations of uncertainties in SWDSs from the cybersecurity perspective remain unexplored. To address this limitation, this paper utilizes a robust chance-constrained optimization strategy to scrutinize the vulnerable location of SWDSs against False Data Injection (FDI) attacks. This is achieved by factoring in the probabilistic behavior of water demand at junctions that can potentially facilitate stealthy FDI attacks on the hourly measurements of the pump’s flow rate. The proposed nonlinear model is validated with several case studies reflecting the real-world cyberattack consequences including cutoff water supply of the network, enhanced power consumption of the pump, and the undesirable pressure surge in the system at strategic locations of SWDSs. As a result of the studied cases, the cyberattack consequences on the entire water supply network are obtained while highlighting the threat-prone regions of the network. This paper contributes to embedding additional security layers to the existing water infrastructure at the vulnerable links and junctions.

Physical Layer Security in IRS-Assisted Cache-Enabled Satellite Communication Networks

This paper presents a comprehensive analysis of the physical layer security performance of a cache-enabled satellite communication network that incorporates intelligent reflecting surfaces (IRS) in the presence of a passive eavesdropper. In the proposed system, content caches are deployed at both the ground station and the satellite, which can improve system performance by reducing latency and transmission overhead. Moreover, the use of IRS provides an additional layer of security by enabling the manipulation of the reflected signals to impede eavesdropping. Practical channel models are used to derive connection probability and secrecy probability for both the ground station-IRS-user and the satellite-IRS-user links. The obtained results are then used to evaluate the system’s secure transmission probability, which is maximized subject to the caching probabilities and transmission rate constraints. The paper presents numerical results to demonstrate the accuracy of the analysis and the effectiveness of deploying IRS and caching to support secure content delivery. The findings provide valuable insights into the potential benefits of utilizing IRS and caching technologies in satellite communication networks for improved physical layer security.

Low complexity physical layer security approach for 5G internet of things

<span lang="EN-US">Fifth-generation (5G) massive machine-type communication (mMTC) is expected to support the cellular adaptation of internet of things (IoT) applications for massive connectivity. Due to the massive access nature, IoT is prone to high interception probability and the use of conventional cryptographic techniques in these scenarios is not practical considering the limited computational capabilities of the IoT devices and their power budget. This calls for a lightweight physical layer security scheme which will provide security without much computational overhead and/or strengthen the existing security measures. Here a shift based physical layer security approach is proposed which will provide a low complexity security without much changes in baseline orthogonal frequency division multiple access (OFDMA) architecture as per the low power requirements of IoT by systematically rearranging the subcarriers. While the scheme is compatible with most fast Fourier transform (FFT) based waveform contenders which are being proposed in 5G especially in mMTC and ultra-reliable low latency communication (URLLC), it can also add an additional layer of security at physical layer to enhanced mobile broadband (eMBB).</span>

Blockchain Voting: A Step Towards Inclusive Democracy

Abstract: The online voting system that incorporates blockchain technology aims to transform the voting process by introducing upgraded trust, transparency and security. Through the utilization of a decentralized blockchain network, the proposed system ensures that each vote is securely recorded and verified, thereby establishing an immutable and tamper-resistant voting mechanism. One of the fundamental feature of the system is eligible voter verification. By leveraging blockchain's distributed nature, the system can verify the identity and eligibility of each voter, ensure that eligible individuals can only participate in the voting system. This authentication process adds an additional layer of security and helps prevent fraudulent activities. Secure vote casting is another crucial component of the proposed voting system. Through the utilization of blockchain, each and every vote is encrypted and securely stored in a decentralized manner. This ensures that votes cannot be altered or manipulated, providing a high level of integrity to the voting process. Additionally, the system emphasizes transparent result tallying. The decentralized nature of blockchain technology allows for the public verification of votes, enabling anyone to audit the voting process. This transparency enhances trust among voters, as it provides them with the ability to independently verify the accuracy of the election results. Overall, the proposed online voting system, empowered by blockchain technology, offers a transparent, secure and tamper-resistant solution for conducting elections. By leveraging the benefits of blockchain, such as decentralization and immutability, the system addresses the challenges faced by traditional voting systems and provides a more reliable and trustworthy platform for the democratic process. It has the potential to enhance the integrity of elections, increase voter turnout, and foster trust in the electoral system.

Plasma disinfection procedures for surfaces in emergency service vehicles: a field trial at the German Red Cross

The demand for thorough disinfection within ambulances is essential, given the in-vehicle medical procedures and the potential high risk of infections due to patients' open wounds. One solution that can address this hygiene challenge involves the application of reactive products generated from atmospheric (air) oxygen and water vapor, activated through the use of cold plasma. Cold plasma's charged particles perforate the cell membranes of microorganisms. This process does not work in human cells, as proteins in the form of enzymes within the body break down the cold plasma and protect the cells. The study was done on an ambulance that was contaminated in eight places. Samples were taken from each site, and two surfaces measuring approximately 8 × 8 cm were carefully sealed and marked. These surfaces were deliberately contaminated by applying an Enterococcus faecium suspension of 8.5 × 107 CFU/mL using a sterile cotton swab. It was followed by the disinfection procedure, that was initiated with the PLASMOCAR device. It was positioned on the front workspace and operated for a duration of 30 min, utilizing the vehicle's onboard voltage. Throughout the operation, all doors and windows were closed and the vehicle's air conditioning system remained active. After the completion of the disinfection process, samples were collected from the surfaces for bacterial counts. A reduction of 3.73 log levels in initial bacteria was accomplished within the rescue vehicle for Enterococcus faecium, equivalent to a 10–fourfold reduction in bacteria, eliminating up to 99.99% of the initial microorganisms. This success makes the process well-suited and convenient as an ongoing "background" procedure to enhance the established disinfection procedures. The established disinfection procedures outlined in the hygiene plan must be promptly implemented whenever mechanical surface cleaning is required. The use of PLASMOCAR offers an extra layer of protection and security, significantly decreasing the risk of microorganism transmission through cross-contamination and aerosols. This is a significant benefit for the well-being of both staff and patients.

Comparative Study of Healthcare Systems using RBAC Alone versus Integrating RBAC with Digital Watermarking for Enhanced Data Security

This comparative study examines the effectiveness of Role-Based Access Control (RBAC) alone versus its integration with digital watermarking in enhancing data security within healthcare systems. RBAC is employed widely to regulate access based on user roles, while digital watermarking adds an additional layer of security by embedding imperceptible markers for data integrity verification. The study evaluates security incidents, operational efficiency, regulatory compliance, and user satisfaction across two groups: healthcare systems using RBAC alone (Group A) and those integrating RBAC with digital watermarking (Group B). Findings indicate that Group B exhibits reduced unauthorized access and enhanced detection of tampering attempts compared to Group A. Group B also demonstrates improved compliance with healthcare regulations and maintains operational efficiency despite minimal processing overhead from watermarking. User feedback suggests initial adaptation to digital watermarking but highlights perceived security benefits and trust in data integrity. This study underscores the value of integrating RBAC with digital watermarking to bolster data security in healthcare settings, offering insights into optimizing security strategies for sensitive healthcare.

Video and Image Steganography

Video steganography, a technique for embedding secret information within video sequences, has gained prominence in the domain of covert communication. By exploiting the inherent redundancy and high capacity of video data, this approach enables secure data transmission without raising suspicion. This paper delves into the intricacies of AES-based video steganography, with a particular focus on the integration of the Advanced Encryption Standard (AES) algorithm. The AES algorithm, renowned for its robust encryption capabilities, serves as a cornerstone of this steganographic approach. By encrypting the secret data prior to embedding it within the video frames, an additional layer of security is introduced, safeguarding the confidentiality of the hidden information

DEVELOPMENT OF IoT SYSTEMS FOR FIRE DETECTION TOOLS USING ESP 8266 AND TELEGRAM NOTIFICATIONS

This research describes the process of making and developing a fire detection system using IoTtechnology. The background for making this tool is because the existing tool at the research site, namely at the Captive Power Plant of PT Indorama, is still a conventional device with an ordinary smoke sensor system and notifications only via a buzzer. This system combines telegram notification mode. Using three sensors namely temperature sensor, smoke sensor and fire sensor is a very effective combination as an early warning system. The test results show that the system provides notification via telegram when there is a significant increase in temperature above 31oC. The smoke sensor is tested with three smoke conditions, namely thin, medium and thick with a value of 704-803 ppm. The sensor response is less than 2 seconds, notification instructions to telegrams are sent directly without any delay. In the fire sensor test, six test conditions were carried out with variations in distance ranging from 10-100 cm, the sensor response was under 2 seconds, immediately activated the buzzer and a telegram notification was sent. The results of this study contribute to the hope that with the three sensor combinations the security layer will be more optimal and in real terms it can be used in industrial buildings which are prone to fire.

Enhancing Confidentiality and Privacy Preservation in e-Health to Enhanced Security

Electronic health (e-health) system use is growing, which has improved healthcare services significantly but has created questions about the privacy and security of sensitive medical data. This research suggests a novel strategy to overcome these difficulties and strengthen the security of e-health systems while maintaining the privacy and confidentiality of patient data by utilising machine learning techniques. The security layers of e-health systems are strengthened by the comprehensive framework we propose in this paper, which incorporates cutting-edge machine learning algorithms. The suggested framework includes data encryption, access control, and anomaly detection as its three main elements. First, to prevent unauthorised access during transmission and storage, patient data is secured using cutting-edge encryption technologies. Second, to make sure that only authorised staff can access sensitive medical records, access control mechanisms are strengthened using machine learning models that examine user behaviour patterns. This research's inclusion of machine learning-based anomaly detection is its most inventive feature. The technology may identify variations from typical data access and usage patterns, thereby quickly spotting potential security breaches or unauthorised activity, by training models on past e-health data. This proactive strategy improves the system's capacity to successfully address new threats. Extensive experiments were carried out employing a broad dataset made up of real-world e-health scenarios to verify the efficacy of the suggested approach. The findings showed a marked improvement in the protection of confidentiality and privacy, along with a considerable decline in security breaches and unauthorised access events.

금융권의 제로 트러스트 보안모델 적용방안에 관한 연구

The changed hybrid work environment such as the expansion of cloud computing technology and the increase in telecommuting due to the coronavirus infection (COVID-19), has brought about new security problems. The traditional perimeter security model has limitations in protecting various devices and environments because it is difficult to clearly distinguish network boundaries. The Zero Trust model, which has been proposed as an alternative security strategy to overcome this, is based on the premise that there is no trust in the assets and actors that are connected components when configuring corporate infrastructure and workflow. The financial sector is actively seeking to introduce the zero trust security model as a means of strengthening security. Demand for responding to advanced cyber-security threats, strengthening security policies, and applicability and necessity of a zero trust security model in the financial sector has expanded. This study proposed the components of a zero trust security model to be applied to the financial world based on financial governance and zero trust principles, components of the maturity model, and the results of expert interviews. The zero trust security model in the financial sector consists of four layers and eight detailed steps: perimeter security layer, authority definition layer, behavior detection layer, and internal control layer. This zero trust security model for the financial sector is expected to provide guidelines for key elements and construction steps to be considered when introducing zero trust in the financial sector.

VoteBlock: Blockchain Based E-Voting System

In the contemporary digital landscape, where the ease of hacking and system breaches prevails, the potential for data tampering looms, resulting in unfavourable circumstances. To mitigate this rick, blockchain technology emerges as steadfast solution, characterised by its near- impenetrable security features, rendering data alteration virally impossible. The act of voting, integral to any nation’s democratic process, stands as a cornerstone of societal decision making. The consequences of vote miscalculation or manipulation by external forces are dire, emphasising the need for a secure and reliable system. It is in this context that blockchain technology plays a cubical role, offering an avenue to enhance the integrity and accessibility of the voting process. This paper presents a comprehensive proposal for decentralised national e-voting system build upon blockchain technology. The system incorporates an administrative panel designed to facilitate the scheduling of elections, candidate management, and the declaration of election results. Concurrently, a user-friendly web application empowers citizens with an interface for inputting their personal details, including their name, mobile number, and a live photo captured during the voting process. To maintain the integrity of the voting system, voter eligibility is rigorously verified at the point of User ID entry. A crucial layer of security is added by confirming eligible voters through their registers phone numbers using One Time Passwords (OTPs). Subsequently, individual voters gain the privilege to cast their votes, with their actions monitored through a webcam or front cameras. Votes are securely recorded within a blockchain ledger, immune to tapering, while the system checks the voter’s addressed corresponding constituency in the backend. The voting results are diligently declared on a predefined date and managed by the administrator, with graphical representations available to provide clarity and transparency. This holistic system not only upholds the sanctity of the voting process but also offers citizens a technologically advanced and secure means to exercise their democratic rights

Enhancing IoT Data Security through Multilayered Approach: Chaotic Map, DNA Sequencing, Blockchain Intergration

The rapid proliferation of the Internet of Things (IoT) devices has ushered in an era of unprecedented connectivity, yet it also poses significant challenges in terms of data security and privacy. In this research, a robust and innovative approach is proposed to address these challenges by introducing a multi-layered security model integrating three powerful technologies: chaotic maps, DNA computing, and block chain technology to fortify IoT data protection. The key objective of proposed technique is to offer security to data at multiple levels while minimizing the Encryption Time (ET) and Decryption Time (DT). In the proposed work, two types of inputs i.e., textual data and medical image data is taken upon which proposed technique is implemented. The key innovation lies in the generation of binary keys from chaotic maps, making it different from traditional chaotic key methods, thereby establishing a unique and robust foundation for encryption. Furthermore, to enhance the encryption process, a dual layer of security is implemented through DNA sequencing and blockchain, ensuring an unprecedented level of data integrity and confidentiality. Notably, the blockchain phase utilizes SHA-256 for generating hash values, fortifying the blocks with an additional layer of cryptographic strength. This novel approach offers a comprehensive and sophisticated solution, effectively mitigating security concerns in IoT ecosystems. By combining the power of chaotic maps, DNA encoding, and blockchain technology, proposed model stands at the forefront of IoT data security, providing a resilient defence against contemporary and future threats.The performance of proposed approach is examined and validated in terms of ET and DT in MATLAB software. Simulating results revealed that proposed model is outperforming other similar models by attaining lowest ET and DT time for both text and image data.

Dark Web Marketplaces: Data for Collaborative Threat Intelligence

The dark web has become an increasingly important landscape for the sale of illicit cyber goods. Given the prevalence of malware and tools that are used to steal data from individuals on these markets, it is crucial that every company, governing body, and cyber professional be aware of what information is sold on these marketplaces. Knowing this information will allow these entities to protect themselves against cyber attacks and from information breaches. In this article, we announce the public release of a data set on dark web marketplaces’ cybersecurity-related listings. We spent multiple years seeking out websites that sold illicit digital goods and collected data on the available products. Due to the marketplaces’ varied and complex layers of security, we leveraged the flexible Selenium WebDriver with Python to navigate the web pages and collect data. We present analysis of categories of malicious cyber goods sold on marketplaces, prices, persistent vendors, ratings, and other basic information on marketplace storefronts. Additionally, we share the tools and techniques we’ve compiled, enabling others to scrape dark web marketplaces at a significantly lower risk. We invite professionals who opt to gather data from the dark web to contribute to the publicly shared threat intelligence resource.

Heart disease severity level identification system on Hyperledger consortium network.

Electronic Health Records (EHRs) play a vital role in the healthcare domain for the patient survival system. They can include detailed information such as medical histories, medications, allergies, immunizations, vital signs, and more. It can help to reduce medical errors, improve patient safety, and increase efficiency in healthcare delivery. EHR approaches are proven to be an efficient and successful way of sharing patients' personal health information. These kinds of highly sensitive information are vulnerable to privacy and security associated threats. As a result, new solutions must develop to meet the privacy and security concerns in health information systems. Blockchain technology has the potential to revolutionize the way electronic health records (EHRs) are stored, accessed, and utilized by healthcare providers. By utilizing a distributed ledger, blockchain technology can help ensure that data is immutable and secure from tampering. In this article, a Hyperledger consortium network has been developed for sharing health records with enhanced privacy and security. The attribute based access control (ABAC) mechanism is used for controlling access to electronic health records. The use of ABAC on the network provides EHRs with an extra layer of security and control, ensuring that only authorized users have access to sensitive data. By using attributes such as user identity, role, and health condition, it is possible to precisely control access to records on blockchain. Besides, a Gaussian naïve Bayes algorithm has been integrated with this consortium network for prediction of cardiovascular disease. The prediction of cardiovascular is difficult due to its correlated risk factors. This system is beneficial for both patients and physicians as it allows physicians to quickly identify high-risk patients and easily provide them with patient severity level using feature weight prediction algorithms. Dynamic emergency access control privileges are used for the emergency team and will be withdrawn once the emergency has been resolved, depending on the severity score. The system is implemented with the following medical datasets: the heart disease dataset, the Pima Indian diabetes dataset, the stroke prediction dataset, and the body fat prediction dataset. The above datasets are obtained from the Kaggle repository. This system evaluates system performance by simulating various operations using the Hyperledger Caliper benchmarking tool. The performance metrics such as latency, transaction rate, resource utilization, etc. are measured and compared with the benchmark.

End to End Encrypted Smart Lock Using RSA based on Opinion from Social Media Review Comments

In the modern era, from big apartments to small houses, startups to corporate buildings, protecting assets or preventing unauthorized persons are crucial problems. Often traditional locks like padlocks are prone to security risks since they can be easily bypassed. Existing smart lock systems are prone to Man in middle Attacks where digital keys can easily be duplicated. The review comments about prevailing smart locks technologies have been collected from various sources such as blogs and microblogs. The data set is analyzed to discover the opinion of the people about the smartlock product. In this proposed system, an innovative smartlock system prototype is designed using current technologies. A smart lock system has been proposed which is encrypted end-to-end using the RSA algorithm. This system uses a one-time password sent to registered users combined with the master code to unlock the door. This system is designed as such only the users who are connected to a wireless local area network are able to access the smart lock system, this adds an additional layer of security. It is connected to the cloud and logs all the activity from booting to shutting down. The breach detection system along with image capture is also included to detect forced intrusions. The client functionality can be easily ported to any platform which supports HTTP protocol which tends to be the major advantage of the proposed work.

Safety Extension Proposal using IO-Link Wireless

This article descibes an enhancement of IO-LinkWireless with an additional safety and security communication layer employing the black channel principle to fulfill safety requirements with respect to IEC 61784-3:2021. An extended channel model based on uniformly distributed segments (UDS) superimposed with the binary symmetric channel (BSC) is applied to simplify the residual error probability (REP) calculation, to detect additional error patterns, and to consider BSC-preserved cryptographic algorithms. Also, the REP with respect to the underlying security layer as well as the probability of failure per hour are quantified.

PHY Security Design for Mobile Crowd Computing in ICV Networks Based on Multi-Agent Reinforcement Learning

In this paper, we propose a multi-roadside unit (RSU) assisted mobile crowd computing framework for intelligently connected vehicle (ICV) networks, where vehicles within RSUs’ coverage act as workers to provide their computation and communication resources for computing resource limited vehicle user equipments (VUEs). Physical (PHY) layer security is used to secure computation task offloading and results feedback in time-varying vehicular channels. Artificial noise (AN) assisted adaptive wiretap coding is adopted to enhance the security of offloading links. With PHY security, the intended receiver can decode secret message while eavesdropper cannot. A modified exhaustive two-dimensional (2D) search algorithm is proposed to optimize transmission rate and secrecy rate in an effective secrecy throughput maximization problem, and a multi-agent twin delayed deep deterministic policy gradient algorithm (MATD3) is utilized to assign VUEs’ tasks without a central controller, where a reward function is defined according to the computing costs, including execution time, energy consumption, and price paid for computing. Finally, simulations verify the effectiveness of the proposed framework.

Design of a Single-Element Dynamic Antenna for Secure Wireless Applications

We introduce a new technique for secure wireless applications using a single dynamic antenna. The dynamic antenna supports a constantly and rapidly changing current distribution that generates a radiation pattern that is static in a desired direction and dynamic elsewhere. This imparts additional modulation on the signal and obscures information transmitted or received outside of the information beam, thus achieving directional modulation. Dynamic currents are supported by a single feed that is switched between separate ports on a single antenna, generating two different radiation patterns without changing the physical shape of the antenna. We introduce the theoretical concept by exploring an ideal complex dynamic radiation pattern that remains static in a narrow desired direction and is dynamic elsewhere. The impact on the transmission of information is analyzed, showing that the information beam narrows as the modulation order increases, and design constraints on the spatial width of the information beam as a function of modulation format are determined. We design and analyze a 2.3 GHz two-state dynamic dipole antenna and experimentally demonstrate secure wireless transmission. We demonstrate the ability to change the information beamwidth and steer the information beam experimentally in real time, and to maintain high throughput in the information beam while obscuring the information elsewhere. In contrast to multiport or array-based antennas, our approach introduces a novel rapidly switched single-element technique for secure wireless applications that can be used independently from the rest of the wireless system, essentially operating as a “black box” for an additional layer of security.

Hybrid Encryption using LSB steganography and RSA

Abstract: In the present world of communication, computers and the internet are the major media that connects different parts of the world as one global virtual world. So we can easily exchange lots of information within seconds of time, but the confidential data that needs to be transferred should be kept confidential. Thus, in order to aid this, we have proposed a new encryption technique by combining Image steganography (LSB) with the cryptographic RSA algorithm for providing more security to our data as well as imperceptibility. The expected outcome would be a properly secure combination of encryption models that uses steganography to hide the message content in a cover image, and also encrypts the message using the cryptographic algorithm, as an additional security layer, in case the content was retrieved from the cover image.