Reinforcement learning for efficient network penetration testing

Penetration testing (also known as pentesting or PT) is a common practice for actively assessing the defenses of a computer network by planning and executing all possible attacks to discover and exploit existing vulnerabilities. Current penetration testing methods are increasingly becoming non-standard, composite and resource-consuming despite the use of evolving tools. In this paper, we propose and evaluate an AI-based pentesting system which makes use of machine learning techniques, namely reinforcement learning (RL) to learn and reproduce average and complex pentesting activities. The proposed system is named Intelligent Automated Penetration Testing System (IAPTS) consisting of a module that integrates with industrial PT frameworks to enable them to capture information, learn from experience, and reproduce tests in future similar testing cases. IAPTS aims to save human resources while producing much-enhanced results in terms of time consumption, reliability and frequency of testing. IAPTS takes the approach of modeling PT environments and tasks as a partially observed Markov decision process (POMDP) problem which is solved by POMDP-solver. Although the scope of this paper is limited to network infrastructures PT planning and not the entire practice, the obtained results support the hypothesis that RL can enhance PT beyond the capabilities of any human PT expert in terms of time consumed, covered attacking vectors, accuracy and reliability of the outputs. In addition, this work tackles the complex problem of expertise capturing and re-use by allowing the IAPTS learning module to store and re-use PT policies in the same way that a human PT expert would learn but in a more efficient way

Human-automation collaboration in manufacturing: identifying key implementation factors

Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implementation and reduce development costs for future projects these factors need to be examined. In this paper, a collection of human factors likely to influence human-automation collaboration are identified from current literature. To test the validity of these and explore further factors associated with implementation success, different types of production processes in terms of stage of maturity are being explored via industrial case studies from the project’s stakeholders. Data was collected through a series of semi-structured interviews with shop floor operators, engineers, system designers and management personnel

The development of a Human Factors Readiness Level tool for implementing industrial human-robot collaboration

The concept of industrial human-robot collaboration (HRC) is becoming increasingly attractive as a means for enhancing manufacturing productivity and product. However, due to traditional preventive health and safety standards, there have been few operational examples of true HRC, so it has not been possible to explore the organisational human factors that need to be considered by manufacturing organisations to realise the benefits of industrial HRC until recently. Charalambous, Fletcher and Webb (2015) made the first attempt to identify the key organisational human factors for the successful implementation of industrial HRC through an industrial exploratory case study. This work enabled (i) development of a theoretical framework of key organisational human factors relevant to industrial HRC and (ii) identification of these factors as enablers or barriers. Although identifying the key organisational human factors (HF) was an important step, it presented a crucial question: when should practitioners involved in HRC design and implementation consider these factors? New industrial processes are typically designed and implemented using a maturity or readiness evaluation system, but these do not incorporate of or link to any formal considerations of HF. The aim of this paper is to expand on the previous findings and link the key human factors in the theoretical framework directly to a recognised industrial maturity readiness level system to develop a new Human Factors Readiness Level (HFRL) tool for system design practitioners to optimise successful implementation of industrial HRC

New numerical procedure for the prediction of temperature development in early age concrete structures

A new numerical model for the prediction of temperature development in young concrete structures is briefly presented. With the pre-program. adiabatic hydration curves, which are used to determine the internal heat generation, are calculated. An artificial neural networks approach is used for this purpose. Adiabatic hydration curves, which were included in the learning set, were determined by our own experiments, using the adiabatic calorimeter which uses air as the coupling media. The main program is implemented in the finite element code. This program allows concrete structure designers and contractors to quantify and evaluate the effects of some concrete initial parameters on the adiabatic hydration curves and corresponding temperature development at an arbitrary point in the concrete element. Some examples are also presented and discussed. (C) 2009 Elsevier B.V. All rights reserve

Управління міжнародним бізнесом: Agility Journey для високотехнологічних компаній

The purpose of the article is the development of recommendations for the business maturity determination and measurement in the implementation of the agile approach for high-tech companies. Methods of analysis of documents, observation, personal and in-depth interviews, case studies have been used in the research. The findings of the research: Business Agility Journey has been suggested for defining the state of the maturity of the company and conducting express diagnostics of agility. Agile Project Management Journey has been developed for the identification of weaknesses by the companies in the path to agility, as well as for the determination of events for the transition from the traditional to the agile approach. Personal Agility Checklist has been designed for testing the soft skills of employees for the presence of the agile mindset. Research limitations include the study of the maturity of companies in the IT industry. Practical implications are based on the use of suggested Agility Journeys in defining the state of maturity and main problems on the transition path. Also, Personal Agility Checklist will help to check the agility of the future employees. The originality of the article is based on the uniqueness of the Agility Journey that has been developed for the first time. Further research on this topic should be focused on the development of an agile mindset as a prerequisite for the provision of agility in the company.Метою статті є розробка рекомендацій щодо визначення та вимірювання зрілості бізнесу при впровадженні еджайл-підходу для високотехнологічних компаній. У дослідженні використовуються методи аналізу документів, спостереження, особистого та глибинного інтерв’ю та кейс-стаді. Розроблено Business Agility Journey для визначення стану зрілості компанії та проведення експрес-діагностики еджайльності. Agile Project Management Journey було розроблено для визначення компаніями своїх слабких сторін, а також заходів для переходу від традиційного до еджайльного підходу. Personal Agility Checklist був створений для перевірки «гнучких навичок» (soft skills) співробітників на наявність гнучкого мислення (agile mindset). Обмеження досліджень включають вивчення зрілості компаній ІТ-галузі. Практична значущість ґрунтується на використанні запропонованих Agility Journeys для визначення стану зрілості та основних проблем на шляху переходу. Також Personal Agility Checklist допоможе перевірити еджайльність майбутніх працівників. Оригінальність статті базується на унікальності Agility Journey, яка була розроблена вперше. Подальші дослідження на цю тему доцільно зосередити на розвитку гнучкого мислення як передумови забезпечення еджайльності в компанії