Security Aspects of Internet of Things aided Smart Grids: a Bibliometric Survey

The integration of sensors and communication technology in power systems, known as the smart grid, is an emerging topic in science and technology. One of the critical issues in the smart grid is its increased vulnerability to cyber threats. As such, various types of threats and defense mechanisms are proposed in literature. This paper offers a bibliometric survey of research papers focused on the security aspects of Internet of Things (IoT) aided smart grids. To the best of the authors' knowledge, this is the very first bibliometric survey paper in this specific field. A bibliometric analysis of all journal articles is performed and the findings are sorted by dates, authorship, and key concepts. Furthermore, this paper also summarizes the types of cyber threats facing the smart grid, the various security mechanisms proposed in literature, as well as the research gaps in the field of smart grid security.Comment: The paper is published in Elsevier's Internet of Things journal. 25 pages + 20 pages of reference

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

On Malfunction, Mechanisms and Malware Classification

Malware has been around since the 1980s and is a large and expensive security concern today, constantly growing over the past years. As our social, professional and financial lives become more digitalised, they present larger and more profitable targets for malware. The problem of classifying and preventing malware is therefore urgent, and it is complicated by the existence of several specific approaches. In this paper, we use an existing malware taxonomy to formulate a general, language independent functional description of malware as transformers between states of the host system and described by a trust relation with its components. This description is then further generalised in terms of mechanisms, thereby contributing to a general understanding of malware. The aim is to use the latter in order to present an improved classification method for malware

The Threat of Offensive AI to Organizations

AI has provided us with the ability to automate tasks, extract information from vast amounts of data, and synthesize media that is nearly indistinguishable from the real thing. However, positive tools can also be used for negative purposes. In particular, cyber adversaries can use AI to enhance their attacks and expand their campaigns. Although offensive AI has been discussed in the past, there is a need to analyze and understand the threat in the context of organizations. For example, how does an AI-capable adversary impact the cyber kill chain? Does AI benefit the attacker more than the defender? What are the most significant AI threats facing organizations today and what will be their impact on the future? In this study, we explore the threat of offensive AI on organizations. First, we present the background and discuss how AI changes the adversary’s methods, strategies, goals, and overall attack model. Then, through a literature review, we identify 32 offensive AI capabilities which adversaries can use to enhance their attacks. Finally, through a panel survey spanning industry, government and academia, we rank the AI threats and provide insights on the adversaries

Invesitigation of Malware and Forensic Tools on Internet

Malware is an application that is harmful to your forensic information. Basically, malware analyses is the process of analysing the behaviours of malicious code and then create signatures to detect and defend against it.Malware, such as Trojan horse, Worms and Spyware severely threatens the forensic security. This research observed that although malware and its variants may vary a lot from content signatures, they share some behaviour features at a higher level which are more precise in revealing the real intent of malware. This paper investigates the various techniques of malware behaviour extraction and analysis. In addition, we discuss the implications of malware analysis tools for malware detection based on various techniques

An Assessment of North Korean Threats and Vulnerabilities in Cyberspace

This thesis answers the fundamental questions of what North Korean capabilities and intent in cyberspace are and what North Korean threats and vulnerabilities are associated with these. It argues that although North Korea’s cyberspace resources and capabilities have increased and reached a level that represents an advanced persistent threat, its cyberspace operations have remained restrained and regional. It also argues that North Korea’s valuable assets include its ability to control cyberspace within North Korea and its ability to engage in cyberspace activities and operations from abroad. The thesis recommends that the United States government exploit these assets by denying and disrupting the use of cyberspace by covert cyber units outside of North Korea, as well as by enabling and ensuring the less monitored and less controlled use of cyberspace by civilians inside of North Korea