From the Editors

Special Issue: Legal, Social, and Technical Considerations for Cyber Security 
in the Digital Revolution

The current digital revolution is often synonymous with the Fourth Industrial Revolution, where there is increasing focus on the use of artificial intelligence and machine learning, big data and data science, and cyber-physical systems with particular focus on the Internet of Things (IoT). The introduction of new technologies has the potential to increase the attack surface as well as the legal liabilities of security flaws and failures with or by the technology. In addition, there exist gaps in terms of cybersecurity governance and policy that need to be addressed.

The Cambridge Analytica scandal illustrated how big data can be misused to aid in potentially influencing the outcomes of voting, with severe social and legal repercussions for the organisation when their role was discovered (Meredith 2018). In addition, big data is often not as helpful as expected; Lui (2016) indicates that 32% of organisations found big data made decision-making more problematic.

The security concerns with IoT were demonstrated when a casino was hacked through the Inter-net-connected sensors for the lobby fish tank (Schiffer 2017). At a larger scale, distributed denial of service attacks from the Mirai botnet (consisting of compromised IoT devices) targeted Dyn and disrupted access to social media across the U.S. and Western Europe (Woolf 2016), and then essentially severed Liberia from the Internet (Kirk 2019). The varying scale of the attacks means that there is a greater need to consider both national laws and regulations, as wells as international laws. An example of the growing efforts for common international frameworks includes the Paris Call (Macron 2018) and the norms proposed by the Global Commission for the Stability of Cyberspace (2019).

This special issue invited authors who presented papers at three mini-tracks (chaired by the editors for this special issue) at the 2019 International Conference on Cyber Warfare and Security to expand upon their work by including additional content and contributions not presented at the conference. The papers submitted to this issue have undergone a double-blind peer review process in addition to the review process for the conference. Of ten papers invited, eight have been selected for inclusion in this special issue.

Abstract: 

Cyberattacks on industrial companies have increased in the last years. The Industrial Internet of Things increases production efficiency at the cost of an enlarged attack surface. Physi-cal separation of productive networks has fallen prey to the paradigm of interconnectivity, present-ed by the Industrial Internet of Things. This leads to an increased demand for industrial intrusion detection solutions. There are, however, challenges in implementing industrial intrusion detection. There are hardly any data sets publicly available that can be used to evaluate intrusion detection algorithms. The biggest threat for industrial applications arises from state-sponsored and crim-inal groups.

Abstract: 

This article advocates the use of automated model checking to find vulnerabilities in cyber-physical systems. Cyber-physical systems are increasingly prevalent in daily life. Smart grids, in particular, are becoming more interconnected and autonomously run. While there are advantages to the evolving critical infrastructure, new challenges arise in designing fault-toler-ant cyber-physical systems. Tools for automated model checking are a key asset in designing and evaluating cyber-physical systems and their components to maximize robustness and to pinpoint vulnerabilities so that they can be mitigated as early in the design process as possible. As a proof of concept for this model checking concept, this paper tests the fault tolerance of a Wide-Area Backup Protection System (WABPS). Each line in the WABPS incorporates a pair of autonomous agents, hosted on intelligent electronic devices (IEDs), which monitor the status of the line and make decisions regarding the safety of the grid.

Abstract: 

The developments of the fourth industrial revolution with the fusion of technologies to Cyber-Physical Production System (CPPS), accompanied by the growing (wireless) interconnection of a multitude of different components (sensors, actuators, and machines, for example) opens up a multitude of risks, attack vectors and security threats. The Physical Layer Security (PhySec) approach proposed in this paper enables an efficient and resource-saving yet sound and secure safeguarding of industrial networks. The elaborated results of the Secret Key Generation (SKG) algorithms to establish Symmetric Key Cryptography (SKC) in wireless networks on the one hand and the SRAM-based Physically Unclonable Functions (PUFs) to derive hardware-intrinsic cryptographic credentials, on the other hand, demonstrate the appropriateness of the PhySec principle.

Abstract: 

The transportation sector is evolving with the introduction of the Internet of Things (IoT) and Industrial Internet of Things (IIoT). IIoT devices are used in the monitoring and control of industrial and related processes and have many useful applications in the transportation sector. This article provides a comparison between IoT and IIoT, and an overview of the threats, vulnerabilities, risks, and incidents related to their use in the transport infrastructure. A guideline for security standards, frameworks, and controls to govern and secure IoT and IIoT specific to transport infrastructure is proposed, with a focus on the rail and maritime sectors.

Abstract: 

New technologies are creating a massive concern for the shipping industry as cyberat-tacks on board ships and in ports continue to rise. More than 90% of world trade is carried by the shipping industry; and, as of 2018, there are more than 53,000 merchant ships sailing the cyber seas. At the same time, these systems are very vulnerable to cyberattacks. Through empirical research, this paper explores the global maritime cybersecurity legal landscape and advances recommendations for policy and legal frameworks essential to ensure safety and security on the cyber sea.

Abstract: 

Cybercrime is increasing at a rate few individuals would have predicted. IBM estimated in 2016 that, in 2019, the cost of cybercrime would reach $2 trillion, a threefold increase from the 2015 estimate of $500 billion. The growth of the Internet and the rapid development of technology provide enormous economic and social benefits but at the same time provide platforms for cyber-criminals to exploit. Organised crime is using more sophisticated techniques, which require highly skilled and specialised law enforcement responses. 

Abstract: 

Although International Humanitarian Law (IHL) is considered applicable to all forms of warfare including future warfare, it does not regulate cyberwarfare in its current form. The South African government has introduced the National Cybersecurity Policy Framework and the Cybercrimes Bill in addition to existing Information Communications Technology legislation. However, the areas of jus in bello (just war) and jus ad bellum (the right to go to war) have not been sufficiently addressed regarding cyberwarfare. This paper seeks to explore the interaction between cyberattacks and IHL and its applicability to the South African cyber environment with an overview of South Africa’s cybersecurity posture and framework within a global context.

Abstract:

In the recent past, some Internet users questioned the reliability of online news, but not necessarily the role of search engines in programming public discourse. In 2018, South African Twitter users accused Google of peddling misinformation when Google Image searches for the phrase “squatter camps in South Africa” displayed images of white squatter camps. Many analysts blamed Google’s algorithm for displaying bias. In this article, the authors use this example in comparing the findings of six different search engines to counter this argument. Search engines that are diverse in their scope and origin are used to prove that is it not the algorithm, but rather the data that is biased.