Biblio
Demand response has emerged as one of the most promising methods for the deployment of sustainable energy systems. Attempts to democratize demand response and establish programs for residential consumers have run into scalability issues and risks of leaking sensitive consumer data. In this work, we propose a privacy-friendly, incentive-based demand response market, where consumers offer their flexibility to utilities in exchange for a financial compensation. Consumers submit encrypted offer which are aggregated using Computation Over Encrypted Data to ensure consumer privacy and the scalability of the approach. The optimal allocation of flexibility is then determined via double-auctions, along with the optimal consumption schedule for the users with respect to the day-ahead electricity prices, thus also shielding participants from high electricity prices. A case study is presented to show the effectiveness of the proposed approach.
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.
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”.
Employees' compliance with information security policies (ISP) which may minimize the information security threats has always been a major concern for organizations. Numerous research and theoretical models had been investigated in the related field of study to identify factors that influence ISP compliance behavior. The study presented in this paper is the first to apply the Theory of Interpersonal Behavior (TIB) for predicting ISP compliance, despite a few studies suggested its strong explanatory power. Taking on the prior results of the literature review, we adopt the TIB and aim to further the theoretical advancement in this field of study. Besides, previous studies had only focused on individuals as well as organizations in which the role of government, from the aspect of its effectiveness in enforcing data protection regulation, so far has not been tested on its influence on individuals' intention to comply with ISP. Hence, we propose an exploratory study to integrate government effectiveness with TIB to explain ISP compliance in a Malaysian context. Our results show a significant influence of government effectiveness in ISP compliance, and the TIB is a promising model as well as posing strong explanatory power in predicting ISP compliance.
Firewall is the first defense line for network security. Packet filtering is a basic function in firewall, which filter network packets according to a series of rules called firewall policy. The design of firewall policy is invariably under the instruction of security policy, which is a generic guideline that lists the needs for network access permissions. The design of firewall policy should observe the regulations of security policy. However, even for IPv4 firewall policy, it is extremely difficult to keep the consistency between security policy and firewall policy. Some consistency decision methods of security policy and IPv4 firewall policy were proposed. However, the address space of IPv6 address is a very large, the existing consistency decision methods can not be directly used to deal with IPv6 firewall policy. To resolve the above problem, in this paper, we use a formal technique to decide the consistency between IPv6 firewall policy and security policy effectively and rapidly. We also developed a prototype model and evaluated the effectiveness of the proposed method.