Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

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

A New Role for Human Resource Managers: Social Engineering Defense

[Excerpt] The general risk of social engineering attacks to organizations has increased with the rise of digital computing and communications, while for an attacker the risk has decreased. In order to counter the increased risk, organizations should recognize that human resources (HR) professionals have just as much responsibility and capability in preventing this risk as information technology (IT) professionals. Part I of this paper begins by defining social engineering in context and with a brief history pre-digital age attacks. It concludes by showing the intersection of HR and IT through examples of operational attack vectors. In part II, the discussion moves to a series of measures that can be taken to help prevent social engineering attacks

Machine-Readable Privacy Certificates for Services

Privacy-aware processing of personal data on the web of services requires managing a number of issues arising both from the technical and the legal domain. Several approaches have been proposed to matching privacy requirements (on the clients side) and privacy guarantees (on the service provider side). Still, the assurance of effective data protection (when possible) relies on substantial human effort and exposes organizations to significant (non-)compliance risks. In this paper we put forward the idea that a privacy certification scheme producing and managing machine-readable artifacts in the form of privacy certificates can play an important role towards the solution of this problem. Digital privacy certificates represent the reasons why a privacy property holds for a service and describe the privacy measures supporting it. Also, privacy certificates can be used to automatically select services whose certificates match the client policies (privacy requirements). Our proposal relies on an evolution of the conceptual model developed in the Assert4Soa project and on a certificate format specifically tailored to represent privacy properties. To validate our approach, we present a worked-out instance showing how privacy property Retention-based unlinkability can be certified for a banking financial service.Comment: 20 pages, 6 figure