Biblio
Increasing consumer experience and companies inner quality presents a direct demand of different requirements on supply chain traceability. Typically, existing solutions have separate data storages which eventually provide limited support when multiple individuals are included. Therefore, the block-chain-based methods are utilized to defeat these deficiencies by generating digital illustrations of real products to following several objects at the same time. Nevertheless, they actually cannot identify the change of products in manufacturing methods. The connection between components included in the production decreased, whereby the ability to follow a product’s origin reduced consequently. In this paper, a methodology is recommended which involves using a Block-chain in Supply Chain Traceability, to solve the issues of manipulations and changes in data and product source. The method aims to improve the product’s origin transparency. Block-chain technology produces a specific method of storing data into a ledger, which is raised on many end-devices such as servers or computers. Unlike centralized systems, the records of the present system are encrypted and make it difficult to be manipulated. Accordingly, this method manages the product’s traceability changes. The recommended system is performed for the cheese supply chain. The result were found to be significant in terms of increasing food security and distributors competition.
In recent years, Counterfeit goods play a vital role in product manufacturing industries. This Phenomenon affects the sales and profit of the companies. To ensure the identification of real products throughout the supply chain, a functional block chain technology used for preventing product counterfeiting. By using a block chain technology, consumers do not need to rely on the trusted third parties to know the source of the purchased product safely. Any application that uses block chain technology as a basic framework ensures that the data content is “tamper-resistant”. In view of the fact that a block chain is the decentralized, distributed and digital ledger that stores transactional records known as blocks of the public in several databases known as chain across many networks. Therefore, any involved block cannot be changed in advance, without changing all subsequent block. In this paper, counterfeit products are detected using barcode reader, where a barcode of the product linked to a Block Chain Based Management (BCBM) system. So the proposed system may be used to store product details and unique code of that product as blocks in database. It collects the unique code from the customer and compares the code against entries in block chain database. If the code matches, it will give notification to the customer, otherwise it gets information from the customer about where they bought the product to detect counterfeit product manufacturer.
With the rapid development of IoT in recent years, IoT is increasingly being used as an endpoint of supply chains. In general, as the majority of data is now being stored and shared over the network, information security is an important issue in terms of secure supply chain management. In response to cyber security breaches and threats, there has been much research and development on the secure storage and transfer of data over the network. However, there is a relatively limited amount of research and proposals for the security of endpoints, such as IoT linked in the supply chain network. In addition, it is difficult to ensure reliability for IoT itself due to a lack of resources such as CPU power and storage. Ensuring the reliability of IoT is essential when IoT is integrated into the supply chain. Thus, in order to secure the supply chain, we need to improve the reliability of IoT, the endpoint of the supply chain. In this work, we examine the use of IoT gateways, client certificates, and IdP as methods to compensate for the lack of IoT resources. The results of our qualitative evaluation demonstrate that using the IdP method is the most effective.
Focusing on security management for supply chain under emergencies, this paper analyzes the characteristics of supply chain risk, clarifies the relationship between business continuity management and security management for supply chain, organizational resilience and security management for supply chain separately, so as to propose suggestions to promote the realization of security management for supply chain combined these two concepts, which is of guiding significance for security management for supply chain and quality assurance of products and services under emergencies.
Supply chain security threats pose new challenges to security risk modeling techniques for complex ICT systems such as the IoT. With established techniques drawn from attack trees and reliability analysis providing needed points of reference, graph-based analysis can provide a framework for considering the role of suppliers in such systems. We present such a framework here while highlighting the need for a component-centered model. Given resource limitations when applying this model to existing systems, we study various classes of uncertainties in model development, including structural uncertainties and uncertainties in the magnitude of estimated event probabilities. Using case studies, we find that structural uncertainties constitute a greater challenge to model utility and as such should receive particular attention. Best practices in the face of these uncertainties are proposed.
In an agricultural supply chain, farmers, food processors, transportation agencies, importers, and exporters must comply with different regulations imposed by one or more jurisdictions depending on the nature of their business operations. Supply chain stakeholders conventionally transport their goods, along with the corresponding documentation via regulators for compliance checks. This is generally followed by a tedious and manual process to ensure the goods meet regulatory requirements. However, supply chain systems are changing through digitization. In digitized supply chains, data is shared with the relevant stakeholders through digital supply chain platforms, including blockchain technology. In such datadriven digital supply chains, the regulators may be able to leverage digital technologies, such as artificial intelligence and machine learning, to automate the compliance verification process. However, a barrier to progress is the risk that information will not be credible, thus reversing the gains that automation could achieve. Automating compliance based on inaccurate data may compromise the safety and credibility of the agricultural supply chain, which discourages regulators and other stakeholders from adopting and relying on automation. Within this article we consider the challenges of digital supply chains when we describe parts of the compliance management process and how it can be automated to improve the operational efficiency of agricultural supply chains. We introduce assisted autonomy as a means to pragmatically automate the compliance verification process by combining the power of digital systems while keeping the human in-the-loop. We argue that autonomous compliance is possible, but that the need for human led inspection processes will never be replaced by machines, however it can be minimised through “assisted autonomy”.
The open-source nature of the Android OS makes it possible for manufacturers to ship custom versions of the OS along with a set of pre-installed apps, often for product differentiation. Some device vendors have recently come under scrutiny for potentially invasive private data collection practices and other potentially harmful or unwanted behavior of the preinstalled apps on their devices. Yet, the landscape of preinstalled software in Android has largely remained unexplored, particularly in terms of the security and privacy implications of such customizations. In this paper, we present the first large- scale study of pre-installed software on Android devices from more than 200 vendors. Our work relies on a large dataset of real-world Android firmware acquired worldwide using crowd-sourcing methods. This allows us to answer questions related to the stakeholders involved in the supply chain, from device manufacturers and mobile network operators to third- party organizations like advertising and tracking services, and social network platforms. Our study allows us to also uncover relationships between these actors, which seem to revolve primarily around advertising and data-driven services. Overall, the supply chain around Android's open source model lacks transparency and has facilitated potentially harmful behaviors and backdoored access to sensitive data and services without user consent or awareness. We conclude the paper with recommendations to improve transparency, attribution, and accountability in the Android ecosystem.
The globalization of supply chain makes semiconductor chips susceptible to various security threats. Design obfuscation techniques have been widely investigated to thwart intellectual property (IP) piracy attacks. Key distribution among IP providers, system integration team, and end users remains as a challenging problem. This work proposes an orthogonal obfuscation method, which utilizes an orthogonal matrix to authenticate obfuscation keys, rather than directly examining each activation key. The proposed method hides the keys by using an orthogonal obfuscation algorithm to increasing the key retrieval time, such that the primary keys for IP cores will not be leaked. The simulation results show that the proposed method reduces the key retrieval time by 36.3% over the baseline. The proposed obfuscation methods have been successfully applied to ISCAS'89 benchmark circuits. Experimental results indicate that the orthogonal obfuscation only increases the area by 3.4% and consumes 4.7% more power than the baseline1.