Biblio

Big data continues to grow in the manufacturing domain due to increasing interconnectivity on the shop floor in the course of the fourth industrial revolution. The optimization of machines based on either real-time or historical machine data provides benefits to both machine producers and operators. In order to be able to make use of these opportunities, it is necessary to access the machine data, which can include sensitive information such as intellectual property. Employing the use case of machine tools, this paper presents a solution enabling industrial data sharing and cloud collaboration while protecting sensitive information. It employs the edge computing paradigm to apply differential privacy to machine data in order to protect sensitive information and simultaneously allow machine producers to perform the necessary calculations and analyses using this data.

This article describes a research work in progress, in which a methodology for the development of computerized educational materials based on augmented reality is proposed. The development of the proposal is preceded by a systematic review of the literature in which the convenience of having a methodology that assists teachers and developers interested in the development of educational materials related to augmented reality technology is concluded. The proposed methodology consists of four stages: (1) initiation, (2) design of the learning scenario, (3) implementation and (4) evaluation, as well as specific elements that must be considered in each of them for their correct fulfillment. Finally, the article briefly describes the validation strategy designed to evaluate this methodological proposal.

Space systems provide many critical functions to the military, federal agencies, and infrastructure networks. Nation-state adversaries have shown the ability to disrupt critical infrastructure through cyber-attacks targeting systems of networked, embedded computers. Moving target defenses (MTDs) have been proposed as a means for defending various networks and systems against potential cyber-attacks. MTDs differ from many cyber resilience technologies in that they do not necessarily require detection of an attack to mitigate the threat. We devised a MTD algorithm and tested its application to a real-time network. We demonstrated MTD usage with a real-time protocol given constraints not typically found in best-effort networks. Second, we quantified the cyber resilience benefit of MTD given an exfiltration attack by an adversary. For our experiment, we employed MTD which resulted in a reduction of adversarial knowledge by 97%. Even when the adversary can detect when the address changes, there is still a reduction in adversarial knowledge when compared to static addressing schemes. Furthermore, we analyzed the core performance of the algorithm and characterized its unpredictability using nine different statistical metrics. The characterization highlighted the algorithm has good unpredictability characteristics with some opportunity for improvement to produce more randomness.

With the advancement of network technology, users can now easily gain access to and benefit from networks. However, the number of network violations is increasing. The main issue with this violation is that irresponsible individuals are infiltrating the network. Network intrusion can be interpreted in a variety of ways, including cyber criminals forcibly attempting to disrupt network connections, gaining unauthorized access to valuable data, and then stealing, corrupting, or destroying the data. There are already numerous systems in place to detect network intrusion. However, the systems continue to fall short in detecting and counter-attacking network intrusion attacks. This research aims to enhance the detection of Denial of service (DoS) by identifying significant features and identifying abnormal network activities more accurately. To accomplish this goal, the study proposes an Intrusion Analysis System for detecting Denial of service (DoS) network attacks using machine learning. The accuracy rate of the proposed method using random forest was demonstrated in our experimental results. It was discovered that the accuracy rate with each dataset is greater than 98.8 percent when compared to traditional approaches. Furthermore, when features are selected, the detection time is significantly reduced.

A threat of eavesdropping display screen image of information device is caused by unintended EM leakage emanation. QR bar-code is capable of error correction, and its information is possibly read from a damaged screen image from EM leakage. A new design of QR bar-code proposed in this paper uses selected colors in consideration of correlation between the EM wave leakage and display color. Proposed design of QR bar-code keeps error correction of displayed image, and makes it difficult to read information on the eavesdropped image.

Security in today's world is one of the most important considerations when one wants to send, receive and store files containing private information or files simply too large for an email attachment. People are becoming more and more dependent on their mobile phones for performing the mentioned critical functionalities. Therefore, it is very important to protect sensitive information when the mobile is lost or stolen. There are many algorithms and methods used to accomplish data security in mobile devices. In general, cryptography and steganography are two common methods used to secure communications. Recently, the field of biology has been combined with the field of cryptography to produce a new field called deoxyribonucleic acid (DNA) cryptography which is one of the most powerful tools to solve security problems.This paper proposes a DNA cryptography technique for securing data stored offline in the Android device where users are not aware of the confidentiality of their private data. It is very difficult to predict the one-time pad key that is used as randomly generated and just for one-time. The proposed algorithm uses DNA mapping for dealing with the data as a DNA sequence. Two approaches have been proposed for achieving desired outcomes.

Underwater wireless optical communications are studied through single photon detection, photon states modulation and quantum key encryption. These studies will promote the development of optical communication applications in underwater vehicles and underwater sensor networks.

Internet of Things (IoT) wireless devices has the capability to interconnect small footprint devices and its key purpose is to have seamless connection without operational barriers. It is built upon a three-layer (Perception, Transportation and Application) protocol stack architecture. A multitude of security principles must be imposed at each layer for the proper and efficient working of various IoT applications. In the forthcoming years, it is anticipated that IoT devices will be omnipresent, bringing several benefits. The intrinsic security issues in conjunction with the resource constraints in IoT devices enables the proliferation of security vulnerabilities. The absence of specifically designed IoT frameworks, specifications, and interoperability issues further exacerbate the challenges in the IoT arena. This paper conducts an investigation in IoT wireless security with a focus on the major security challenges and considerations from an IoT protocol stack perspective. The vulnerabilities in the IoT protocol stack are laid out along with a gap analysis, evaluation, and the discussion on countermeasures. At the end of this work, critical issues are highlighted with the aim of pointing towards future research directions and drawing conclusions out of it.

The increase of size, capabilities, and speed of FPGAs enables the shared usage of reconfigurable resources by multiple applications and even operating systems. While research on FPGA virtualization in HPC-datacenters and cloud is already well advanced, it is a rather new concept for embedded systems. The necessity for FPGA virtualization of embedded systems results from the trend to integrate multiple environments into the same hardware platform. As multiple guest operating systems with different requirements, e.g., regarding real-time, security, safety, or reliability share the same resources, the focus of research lies on isolation under the constraint of having minimal impact on the overall system. Drivers for this development are, e.g., computation intensive AI-based applications in the automotive or medical field, embedded 5G edge computing systems, or the consolidation of electronic control units (ECUs) on a centralized MPSoC with the goal to increase reliability by reducing complexity. This survey outlines key concepts of hypervisor-based virtualization of embedded reconfigurable systems. Hypervisor approaches are compared and classified into FPGA-based hypervisors, MPSoC-based hypervisors and hypervisors for distributed embedded reconfigurable systems. Strong points and limitations are pointed out and future trends for virtualization of embedded reconfigurable systems are identified.

USB flash drives are used widely to store or transfer data among the employees in the company. There was greater concern about leaks of information especially company crown jewel or intellectual property data inside the USB flash drives because of theft, loss, negligence or fraud. This study is a real case in XYZ company which aims to find remaining the company’s crown jewel or intellectual property data inside the USB flash drives that belong to the employees. The research result showed that sensitive information (such as user credentials, product recipes and customer credit card data) could be recovered from the employees’ USB flash drives. It could obtain a high-risk impact on the company as reputational damage and sabotage product from the competitor. This result will help many companies to increase security awareness in protecting their crown jewel by having proper access control and to enrich knowledge regarding digital forensic for investigation in the company or enterprise.

Nowadays, peoples are very concerned about their data privacy. Hence, all the current security methods should be improved to stay relevant in this fast-growing technology world. Visual Cryptography (VC) is a cryptographic technique that using the image processing method. The implementation of VC can be varying and flexible to be applied to the system that requires an extra security precaution as it is one of the effective solutions in securing the data exchange between two or more parties. The main purpose of the development of V-CRYPT System is to improve the current VC technique and make it more complex in the encryption and decryption process. V-CRYPT system will let the user enter the key, then select the image that they want to encrypt, and the system will split the image into four shares: share0, share1, share2, share3. Each pixel of the image will be splatted into a smaller block of subpixels in each of the four shares and encrypted as two subpixels in each of the shares. The decryption will work only when the user selects all the shares, and the correct text key is entered. The system will superimpose all the shares and producing one perfect image. If the incorrect key is entered, the resulted image will be unidentified. The results show that V- CRYPT is a valuable alternative to existing methods where its security level is higher in terms of adding a secure key and complexity.

SMS (Short Message Service)-based authentication is widely used as a simple and secure multi-factor authentication, where OTP (One Time Password) is sent to user’s mobile phone via SMS. However, SMS authentication is vulnerable to Password Reset Man in the Middle Attack (PRMitM). In this attack, the attacker makes a victim perform password reset OTP for sign-up verification OTP. If the victim enters OTP to a malicious man-in-the-middle site, the attacker can overtake the victim’s account.We find new smartphone useful functions may increase PR-MitM attack risks. SMS push notification informs us an arrival of message by showing only beginning of the message. Hence, those who received SMS OTP do not notice the cautionary notes and the name of the sender that are supposed to show below the code, which may lead to be compromised. Auto-fill function, which allow us to input authentication code with one touch, is also vulnerable for the same reason.In this study, we conduct a user study to investigate the effect of new smartphone functions incurring PRMitM attack.

Over the last few years, the deployment of Internet of Things (IoT) is attaining much more concern on smart computing devices. With the exponential growth of small devices and at the same time cheap prices of these sensing devices, there raises an important question for the security of the stored information as these devices generate a large amount of private data for observing and controlling purposes. Distributed Denial of Service (DDoS) attacks are current examples of major security threats to IoT devices. As yet, no standard protocol can fully ensure the security of IoT devices. But adaptive decision making along with elasticity and incessant monitoring is required. These difficulties can be resolved with the assistance of Software Defined Networking (SDN) which can viably deal with the security dangers to the IoT devices in a powerful and versatile way without hampering the lightweightness of the IoT devices. Although SDN performs quite well for managing and controlling IoT devices, security is still an open concern. Nonetheless, there are a few challenges relating to the mitigation of DDoS attacks in IoT systems implemented with SDN architecture. In this paper, a brief overview of some of the popular DDoS attack mitigation techniques and their limitations are described. Also, the challenges of implementing these techniques in SDN-based architecture to IoT devices have been presented.

The main objective of the proposed work is to build a reliable and secure architecture for cloud servers where users may safely store and transfer their data. This platform ensures secure communication between the client and the server during data transfer. Furthermore, it provides a safe method for sharing and transferring files from one person to another. As a result, for ensuring safe data on cloud servers, this research work presents a secure architecture combining three DNA cryptography, HMAC, and a third party Auditor. In order to provide security by utilizing various strategies, a number of traditional and novel cryptographic methods are investigated. In the first step, data will be encrypted with the help of DNA cryptography, where the encoded document will be stored in the cloud server. In next step, create a HMAC value of encrypted file, which was stored on cloud by using secret key and sends to TPA. In addition, Third Party Auditor is used for authenticate the purity of stored documents in cloud at the time of verification TPA also create HMAC value from Cloud stored data and verify it. DNA-based cryptographic technique, hash based message authentic code and third party auditor will provide more secured framework for data security and integrity in cloud server.

Internet of things as a technology that connect internet and physical world has been implemented in many diverse fields and has been proven very useful and flexible. In every implementation of technology that involve internet, security must be a great concern, including the implementation of IoT technology. A lot of alternatives can be used to achieve security of IoT. Ming et al. has proposed novel signcryption scheme to secure IoT of monitoring health data. In this work, proposed signcryption scheme from Ming et al. has been successfully implemented using Raspberry Pi and ESP32 and has proven work in securing IoT data.

The most representative method of deep learning is data-driven learning. These methods are often data-dependent, and lack of data leads to poor learning. There is a GAN method that creates a likely image as a way to solve a problem that lacks data. The GAN determines that the discriminator is fake/real with respect to the image created so that the generator learns. However, overfitting problems when the discriminator becomes overly dependent on the learning data. In this paper, we explain overfitting problem when the discriminator decides to fake/real using xAI. Depending on the area of the described image, it is possible to limit the learning of the discriminator to avoid overfitting. By doing so, the generator can produce similar but more diverse images.

With the rapid development and application of emerging information technology, the traditional network security architecture is more and more difficult to support flexible dynamic and a wider range of business data access requirements. Zero trust technology can truly realize the aggregation of security and business by building an end-to-end dynamic new boundary based on identity, which puts forward a new direction for the upgrade and evolution of enterprise network security architecture. This paper mainly includes access control and identity authentication management functions. The goal of access control system is to ensure that legitimate and secure users can use the system normally, and then protect the security of enterprise network and server. The functions of the access control system include identifying the user's identity (legitimacy), evaluating the security characteristics (Security) of the user's machine, and taking corresponding response strategies.

In this paper we propose a security and cost aware scheduling heuristic for real-time workflow jobs that process Internet of Things (IoT) data with various security requirements. The environment under study is a four-tier architecture, consisting of IoT, mist, fog and cloud layers. The resources in the mist, fog and cloud tiers are considered to be heterogeneous. The proposed scheduling approach is compared to a baseline strategy, which is security aware, but not cost aware. The performance evaluation of both heuristics is conducted via simulation, under different values of security level probabilities for the initial IoT input data of the entry tasks of the workflow jobs.

Secret-related carrier intelligent management and control system uses the Internet of Things and artificial intelligence to solve the transformation of secret-related carrier management and control from manual operation to automatic detection, precise monitoring, and intelligent decision-making, and use technical means to resolve security risks. However, the coexistence of multiple heterogeneous networks will lead to various network security problems in the secret carrier intelligent management and control. Aiming at the actual requirements of the intelligent management and control of secret-related carriers, this paper proposes a system structure including device domain, network domain, platform domain and user domain, and conducts a detailed system security analysis, and introduces intelligent agent technology, and proposes a distributed system. The hierarchical system structure of the secret-related carrier intelligent management and control security protection model has good robustness and portability.

In recent years, blockchain-based cryptocurren-cies have attracted much attention. Attacks targeting cryptocurrencies and related services directly profit an attacker if successful. Related studies have reported attacks targeting configuration-vulnerable nodes in Ethereum using a method called honeypots to observe malicious user attacks. They have analyzed 380 million observed requests and showed that attacks had to that point taken at least 4193 Ether. However, long-term observations using honeypots are difficult because the cost of maintaining honeypots is high. In this study, we analyze the behavior of malicious users using our honeypot system. More precisely, we clarify the pre-investigation that a malicious user performs before attacks. We show that the cost of maintaining a honeypot can be reduced. For example, honeypots need to belong in Ethereum's P2P network but not to the mainnet. Further, if they belong to the testnet, the cost of storage space can be reduced.

With the rapid development of urbanization, community security and public security have become an important social issue. As conventional patrol methods can not effectively ensure effective supervision, this paper studies the application of NFC (Near Field Communication) technology in intelligent security system, designs and constructs a set of intelligent security system suitable for public security patrol or security patrol combined with current cloud service technology. The system can not only solve the digital problem of patrol supervision in the current public security, but also greatly improve the efficiency of security and improve the service quality of the industry through the application of intelligent technology.

The existing education system, which incorporates school assessments, has some flaws. Conventional teaching methods give students no immediate feedback, also make teachers to spend hours grading repetitive assignments, and aren't very constructive in showing students how to improve in their academics, and also fail to take advantage of digital opportunities that can improve learning outcomes. In addition, since a single teacher has to manage a class of students, it gets difficult to focus on each and every student in the class. Furthermore, with the help of a management system for better learning, educational organizations can now implement administrative analytics and execute new business intelligence using big data. This data visualization aids in the evaluation of teaching, management, and study success metrics. In this paper, there is put forward a discussion on how Data Mining and Data Analytics can help make the experience of learning and teaching both, easier and accountable. There will also be discussion on how the education organization has undergone numerous challenges in terms of effective and efficient teachings, student-performance. In addition development, and inadequate data storage, processing, and analysis will also be discussed. The research implements Python programming language on big education data. In addition, the research adopted an exploratory research design to identify the complexities and requirements of big data in the education field.

Biometric data is prone to attacks and threats from hackers who are professionals in cyber-crimes. Therefore, securing the data is very essential. Steganographic approach, which is a process of concealing data, is proposed as a solution to this. Biometrics are hidden inside other biometrics for safe storage and secure transmission. Also, it is designed to be robust against attacks, and cannot be detected easily. The intention of this paper is to highlight a method of hiding one image in another image by using mid position value(mpv) technique. Here we have to choose the secret biometric on which Arnold transform will be applied resulting in a scrambled version of the secret biometric. This will be enveloped inside cover image which results in a stego-image. Lastly, hidden secret biometric will be decoded from this stego image, which will first result in a scrambled secret biometric. Inverse Arnold Transform will be applied on this to finally result in the decoded secret biometric. The paper further explains the working and processes in detail.

This paper is devoted to boundary control design for urban traffic described on a macroscopic scale. The state corresponds to vehicle density that evolves on a continuum two-dimensional domain that represents a continuous approximation of a urban network. Its parameters are interpolated as a function of distance to physical roads. The dynamics are governed by a new macroscopic multi-directional traffic model that encompasses a system of four coupled partial differential equations (PDE) each describing density evolution in one direction layer: North, East, West and South (NEWS). We analyse the class of desired states that the density governed by NEWS model can achieve. Then a boundary control is designed to drive congested traffic to an equilibrium with the minimal congestion level. The result is validated numerically using the real structure of Grenoble downtown (a city in France).

The rise of artificial intelligence plays an important role in social progress and economic development, which is a hot topic in the Internet industry. In the past few years, the Chinese government has vigorously increased policy support to promote the golden age of artificial intelligence. However, with the rapid development of artificial intelligence, the copyright protection and intellectual property legislation of artificial intelligence products have brought some challenges.