2 resultados para security of supply
em Repository Napier
Resumo:
Many multinational companies are supposedly viewing Europe as one region and re-shaping their approach to the supply of products to customers. Several factors are thought to be driving this trend, notably the degree of merger and acquisitions activity; the need for improved financial performance; the pressure to reduce inventories and costs, facilitated by improvements in communication and information technology systems. All of this is in the context of European market and monetary harmonisation. This paper investigates the extent and effect of the amanegement of supply chains on a pan-European baisis by multinational business. A survey was used to examine changes, both made and anticipated. to operational strategies, processes, organisational structures and physical infrastructure across a range of businesses and industry sectors. Cost reducation, driven by the need for profit and shreholder return, was found to be the priority for developments in supply chains.Many businesses reported consolidation of manufacturing and distribution activities whilst retaining discrete country-by-country organisational structures for managing customers and markets.Logistics Service Providers were seen in a traditional role as suppliers of commodity warehousing and transport services and lacked true pan-European capability. Despite the often-vaunted concept of a pan-European business model, individual businesses wwere seen to be negotiating their own path to balancing economies of scale with customers' service needs and expectations.
Resumo:
SQL Injection Attack (SQLIA) remains a technique used by a computer network intruder to pilfer an organisation’s confidential data. This is done by an intruder re-crafting web form’s input and query strings used in web requests with malicious intent to compromise the security of an organisation’s confidential data stored at the back-end database. The database is the most valuable data source, and thus, intruders are unrelenting in constantly evolving new techniques to bypass the signature’s solutions currently provided in Web Application Firewalls (WAF) to mitigate SQLIA. There is therefore a need for an automated scalable methodology in the pre-processing of SQLIA features fit for a supervised learning model. However, obtaining a ready-made scalable dataset that is feature engineered with numerical attributes dataset items to train Artificial Neural Network (ANN) and Machine Leaning (ML) models is a known issue in applying artificial intelligence to effectively address ever evolving novel SQLIA signatures. This proposed approach applies numerical attributes encoding ontology to encode features (both legitimate web requests and SQLIA) to numerical data items as to extract scalable dataset for input to a supervised learning model in moving towards a ML SQLIA detection and prevention model. In numerical attributes encoding of features, the proposed model explores a hybrid of static and dynamic pattern matching by implementing a Non-Deterministic Finite Automaton (NFA). This combined with proxy and SQL parser Application Programming Interface (API) to intercept and parse web requests in transition to the back-end database. In developing a solution to address SQLIA, this model allows processed web requests at the proxy deemed to contain injected query string to be excluded from reaching the target back-end database. This paper is intended for evaluating the performance metrics of a dataset obtained by numerical encoding of features ontology in Microsoft Azure Machine Learning (MAML) studio using Two-Class Support Vector Machines (TCSVM) binary classifier. This methodology then forms the subject of the empirical evaluation.