Biblio

A digital signature is a type of asymmetric cryptography that is used to ensure that the recipient receives the actual received message from the intended sender. Problems that often arise conventionally when requiring letter approval from the authorized official, and the letter concerned is very important and urgent, often the process of giving the signature is hampered because the official concerned is not in place. With these obstacles, the letter that should be distributed immediately becomes hampered and takes a long time in terms of signing the letter. The purpose of this study is to overcome eavesdropping and data exchange in sending data using Digital Signature as authentication of data authenticity and minimizing fake signatures on letters that are not made and authorized by relevant officials based on digital signatures stored in the database. This research implements the Rivest Shamir Adleman method. (RSA) as outlined in an application to provide authorization or online signature with Digital Signature. The results of the study The application of the Rivest Shamir Adleman (RSA) algorithm can run on applications with the Digital Signature method based on ISO 9126 testing by expert examiners, and the questionnaire distributed to users and application operators obtained good results from an average value of 79.81 based on the scale table ISO 9126 conversion, the next recommendation for encryption does not use MD5 but uses Bcrypt secure database to make it stronger.

Technology plays a vital role in our lives to meet basic hygiene necessities. Currently, the whole world is facing an epidemic situation and the practice of using sanitizers is common nowadays. Sanitizers are used by people to sanitize their hands and bodies. It is also used for sanitizing objects that come into contact with the machine. While sanitizing a small area, people manage to sanitize via pumps, but it becomes difficult to sanitize the same area every day. One of the most severe sanitation concerns is a simple, economic and efficient method to adequately clean the indoor and outdoor environments. In particular, effective sanitization is required for people working in a clinical environment. Recently, some commonly used sanitizer techniques include electric sanitizer spray guns, electric sanitizer disinfectants, etc. However, these sanitizers are not automated, which means a person is required to roam personally with the device to every place to spray the disinfectant or sanitize an area. Therefore, a novel, cost-effective automatic sanitizing machine (ASM) named ASMBoT is designed that can dispense the sanitizer effectively by solving the aforementioned problems.

Connected Autonomous Vehicle (CAV) applications have shown the promise of transformative impact on road safety, transportation experience, and sustainability. However, they open large and complex attack surfaces: an adversary can corrupt sensory and communication inputs with catastrophic results. A key challenge in development of security solutions for CAV applications is the lack of effective infrastructure for evaluating such solutions. In this paper, we address the problem by designing an automated, flexible evaluation infrastructure for CAV security solutions. Our tool, CAVELIER, provides an extensible evaluation architecture for CAV security solutions against compromised communication and sensor channels. The tool can be customized for a variety of CAV applications and to target diverse usage models. We illustrate the framework with a number of case studies for security resiliency evaluation in Cooperative Adaptive Cruise Control (CACC).

This article describes an analysis of the key technologies currently applied to improve the quality, efficiency, safety and sustainability of Smart Grid systems and identifies the tools to optimize them and possible gaps in this area, considering the different energy sources, distributed generation, microgrids and energy consumption and production capacity. The research was conducted with a qualitative methodological approach, where the literature review was carried out with studies published from 2019 to 2022, in five (5) databases following the selection of studies recommended by the PRISMA guide. Of the five hundred and four (504) publications identified, ten (10) studies provided insight into the technological trends that are impacting this scenario, namely: Internet of Things, Big Data, Edge Computing, Artificial Intelligence and Blockchain. It is concluded that to obtain the best performance within Smart Grids, it is necessary to have the maximum synergy between these technologies, since this union will enable the application of advanced smart digital technology solutions to energy generation and distribution operations, thus allowing to conquer a new level of optimization.

The intrusion detection systems are vital for the sustainability of Cooperative Intelligent Transportation Systems (C-ITS) and the detection of sybil attacks are particularly challenging. In this work, we propose a novel approach for the detection of sybil attacks in C-ITS environments. We provide an evaluation of our approach using extensive simulations that rely on real traces, showing our detection approach's effectiveness.

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.

In the recent years, sustainability has becoming an important topic in agro-food supply chain. Moreover, these supply chains are more vulnerable due to different interrelated risks from man-made and natural disasters. However, most of the previous studies consider less about interrelation in assessing sustainability risks. The purpose of this research is to develop a framework to assess supply chain sustainability risks by rnking environmental risks, economic risks, social risks and operational risks. To solve this problem, the proposed methodology is an integrated rough decision- making and trial evaluation laboratory (DEMA℡) method that consider the interrelationship between different risks and the group preference diversity. In order to evaluate the applicability of the proposed method, a real-world case study of Tunisian agro-food company is presented. The results show that the most important risks are corruption, inflation and uncertainty in supply and demand.

Traffic Signal Control using Reinforcement Learning has been proved to have potential in alleviating traffic congestion in urban areas. Although research has been conducted in this field, it is still an open challenge to find an effective but low-cost solution to this problem. This paper presents multiple deep reinforcement learning-based traffic signal control systems that can help regulate the flow of traffic at intersections and then compares the results. The proposed systems are coupled with SUMO (Simulation of Urban MObility), an agent-based simulator that provides a realistic environment to explore the outcomes of the models.

In this research a secured framework is developed to support effective digital service delivery for government to stakeholders. It is developed to provide secured network to the remote area of Bangladesh. The proposed framework has been tested through the rough simulation of the network infrastructure. Each and every part of the digital service network has been analyzed in the basis of security purpose. Through the simulation the security issues are identified and proposed a security policy framework for effective service. Basing on the findings the issues are included and the framework has designed as the solution of security issues. A complete security policy framework has prepared on the basis of the network topology. As the output the stakeholders will get a better and effective data service. This model is better than the other expected network infrastructure. Till now in Bangladesh none of the network infrastructure are security policy based. This is needed to provide the secured network to remote area from government.

Cyber-attacks detection in modern power systems is undoubtedly indispensable to enhance their resilience and guarantee the continuous production of electricity. As the number of attacks is very small compared to normal events, and attacks are unpredictable, it is not obvious to build a model for attacks. Here, only anomaly-free measurements are utilized to build a reference model for intrusion detection. Specifically, this study presents an unsupervised intrusion detection approach using the k-nearest neighbor algorithm and exponential smoothing monitoring scheme for uncovering attacks in modern power systems. Essentially, the k-nearest neighbor algorithm is implemented to compute the deviation between actual measurements and the faultless (training) data. Then, the exponential smoothing method is used to set up a detection decision-based kNN metric for anomaly detection. The proposed procedure has been tested to detect cyber-attacks in a two-line three-bus power transmission system. The proposed approach has been shown good detection performance.

Measuring software complexity is key in managing the software lifecycle and in controlling its maintenance. While there are well-established and comprehensive metrics to measure the complexity of the software code, assessment of the complexity of software designs remains elusive. Moreover, there are no clear guidelines to help software designers chose alternatives that reduce design complexity, improve design comprehensibility, and improve the maintainability of the software. This paper outlines a language independent approach to measuring software design complexity using objective and deterministic metrics. The paper outlines the metrics for two major software design notations; UML Class Diagrams and UML State Machines. The approach is based on the analysis of the design elements and their mutual interactions. The approach can be extended to cover other UML design notations.

The tremendous growth of cloud computing and large-scale data analytics highlight the importance of reducing datacenter power consumption and environmental impact of brown energy. While many Internet service operators have at least partially powered their datacenters by green energy, it is challenging to effectively utilize green energy due to the intermittency of renewable sources, such as solar or wind. We find that the geographical diversity of internet-scale services can be carefully scheduled to improve the efficiency of applying green energy in datacenters. In this paper, we propose a holistic heterogeneity-aware cloud workload management approach, sCloud, that aims to maximize the system goodput in distributed self-sustainable datacenters. sCloud adaptively places the transactional workload to distributed datacenters, allocates the available resource to heterogeneous workloads in each datacenter, and migrates batch jobs across datacenters, while taking into account the green power availability and QoS requirements. We formulate the transactional workload placement as a constrained optimization problem that can be solved by nonlinear programming. Then, we propose a batch job migration algorithm to further improve the system goodput when the green power supply varies widely at different locations. Finally, we extend sCloud by integrating a flexible batch job manager to dynamically control the job execution progress without violating the deadlines. We have implemented sCloud in a university cloud testbed with real-world weather conditions and workload traces. Experimental results demonstrate sCloud can achieve near-to-optimal system performance while being resilient to dynamic power availability. sCloud with the flexible batch job management approach outperforms a heterogeneity-oblivious approach by 37 percent in improving system goodput and 33 percent in reducing QoS violations.

The penalization of the objective function due to energy deficits is a key element for determining the operational policy of hydroelectric reservoirs. Its definition impacts not only operations, but also system expansion. Brazil historically defined these penalties with basis on a proxy of the economic deficit cost, a value in \$/MWh obtained with aid of the Input-Output Matrix. We propose an approach where these penalties are obtained in order to minimize the operation cost and cost of rationing of the system, considering a criterion of security of supply. A case study with data from the Brazilian System illustrates its application.

Paper proposed an approach to estimating the sustainability of cyber-physical systems based on system state analysis. Authors suggested that sustainability is the system ability to reconfigure for recovering from attacking influences. Proposed a new criterion for cyber-physical systems sustainability assessment based on spectral graph theory. Numerical calculation of the criterion is based on distribution properties of the graph spectrum - the set of eigenvalues of the adjacency matrix corresponding to the graph. Experimental results have shown dependency of change in Δσ, difference between initial value of σstart and final σstop, on working route length, and on graph connectivity was revealed. This parameter is proposed to use as a criterion for CPS sustainability.

Smart Farming is driven by the emergence of precise positioning systems and Internet of Things technologies which have already enabled site-specific applications, sustainable resource management, and interconnected machinery. Nowadays, so-called Farm Management Information Systems (FMISs) enable farm-internal interconnection of agricultural machines and implements and, thereby, allow in-field data exchange and the orchestration of collaborative agricultural processes. Machine data is often directly logged during task execution. Moreover, interconnection of farms, agricultural contractors, and marketplaces ease the collaboration. However, current FMISs lack in security and particularly in user authentication. In this paper, we present a security architecture for a decentralized, manufacturer-independent, and open-source FMIS. Special attention is turned on the Radio Frequency Identification (RFID)-based continuous user authentication which greatly improves security and credibility of automated documentation, while at the same time preserves usability in practice.

Every company may be located at the junction of several Supply Chains (SCs) to meet the requirements of many different end customers. To achieve a sustainable competitive advantage over its business rivals, a company needs to continuously improve its relations to its different stakeholders as well as its performance in terms of integrating its decision processes and hence, its communication and information systems. Furthermore, customers' growing awareness of green and sustainable matters and new national and international regulations force enterprises to rethink their whole system. In this paper we propose a model to quantify the identified potential risks to assist in designing or re-designing a supply chain. So that managers may take adequate decisions to have the continuing ability of satisfying customers' requirements. A case study, developed at kuehne + nagel Luxembourg is provided.

Earth provides natural resources, such as fossil fuels and minerals, that are vital for Europe's economy. As the global demand grows, especially for strategic metals, commodity prices rapidly rise and there is an identifiable risk of an increasing supply shortage of some metals, including those identified as critical to Europe's high technology sector. Hence a major element in any economy's long-term strategy must be to respond to the increasing pressure on natural resources to ensure security of supply for these strategic metals. In today's rapidly changing global economic landscape, mining in the deep sea, specifically at extinct hydrothermal vents and the vast areas covered by polymetallic nodules, has gone from a distant possibility to a likely reality within just a decade. The extremely hostile conditions found on the deep-ocean floor pose specific challenges, both technically and environmentally, which are demanding and entirely different from land-based mining. At present, European offshore industries and marine research institutions have significant experience and technology and are well positioned to develop engineering and knowledge-based solutions to resource exploitation in these challenging and sensitive environments. However, to keep this position there is a need to initiate pilot studies to develop breakthrough methodologies for the exploration, assessment and extraction of deep-sea minerals, as well as investigate the implications for economic and environmental sustainability. The Blue Mining project will address all aspects of the entire value chain in this field, from resource discovery to resource assessment, from exploitation technologies to the legal and regulatory framework.

The convergence of the Internet and mobile computing enables personalised access to online services anywhere and anytime. This potent access capability creates opportunities for new business models which stimulates vigorous investment and rapid innovation. Unfortunately, this innovation also produces new vulnerabilities and threats, and the new business models also create incentives for attacks, because criminals will always follow the money. Unless the new threats are balanced with appropriate countermeasures, growth in the Internet and mobile services will encounter painful setbacks. Security and trust are two fundamental factors for sustainable development of identity management in online markets and communities. The aim of this study is to present an overview of the central aspects of identity management in the Internet and mobile computing with respect to security and trust.