A cyber-kill-chain based taxonomy of crypto-ransomware features

In spite of being just a few years old, ransomware is quickly becoming a serious threat to our digital infrastructures, data and services. Majority of ransomware families are requesting for a ransom payment to restore a custodian access or decrypt data which were encrypted by the ransomware earlier. Although the ransomware attack strategy seems to be simple, security specialists ranked ransomware as a sophisticated attack vector with many variations and families. Wide range of features which are available in different families and versions of ransomware further complicates their detection and analysis. Though the existing body of research provides significant discussions about ransomware details and capabilities, the all research body is fragmented. Therefore, a ransomware feature taxonomy would advance cyber defenders’ understanding of associated risks of ransomware. In this paper we provide, to the best of our knowledge, the first scientific taxonomy of ransomware features, aligned with Lockheed Martin Cyber Kill Chain (CKC) model. CKC is a well-established model in industry that describes stages of cyber intrusion attempts. To ease the challenge of applying our taxonomy in real world, we also provide the corresponding ransomware defence taxonomy aligned with Courses of Action matrix (an intelligence-driven defence model). We believe that this research study is of high value for the cyber security research community, as it provides the researchers with a means of assessing the vulnerabilities and attack vectors towards the intended victims

Best Practices and Recommendations for Cybersecurity Service Providers

This chapter outlines some concrete best practices and recommendations for cybersecurity service providers, with a focus on data sharing, data protection and penetration testing. Based on a brief outline of dilemmas that cybersecurity service providers may experience in their daily operations, it discusses data handling policies and practices of cybersecurity vendors along the following five topics: customer data handling; information about breaches; threat intelligence; vulnerability-related information; and data involved when collaborating with peers, CERTs, cybersecurity research groups, etc. There is, furthermore, a discussion of specific issues of penetration testing such as customer recruitment and execution as well as the supervision and governance of penetration testing. The chapter closes with some general recommendations regarding improving the ethical decision-making procedures of private cybersecurity service providers

Ethical and Unethical Hacking

The goal of this chapter is to provide a conceptual analysis of ethical, comprising history, common usage and the attempt to provide a systematic classification that is both compatible with common usage and normatively adequate. Subsequently, the article identifies a tension between common usage and a normativelyadequate nomenclature. ‘Ethical hackers’ are often identified with hackers that abide to a code of ethics privileging business-friendly values. However, there is no guarantee that respecting such values is always compatible with the all-things-considered morally best act. It is recognised, however, that in terms of assessment, it may be quite difficult to determine who is an ethical hacker in the ‘all things considered’ sense, while society may agree more easily on the determination of who is one in the ‘business-friendly’ limited sense. The article concludes by suggesting a pragmatic best-practice approach for characterising ethical hacking, which reaches beyond business-friendly values and helps in the taking of decisions that are respectful of the hackers’ individual ethics in morally debatable, grey zones

Global Risks 2014, Ninth Edition.

The Global Risks 2014 report highlights how global risks are not only interconnected but also have systemic impacts. To manage global risks effectively and build resilience to their impacts, better efforts are needed to understand, measure and foresee the evolution of interdependencies between risks, supplementing traditional risk-management tools with new concepts designed for uncertain environments. If global risks are not effectively addressed, their social, economic and political fallouts could be far-reaching, as exemplified by the continuing impacts of the financial crisis of 2007-2008

The Ethics of Cybersecurity

This open access book provides the first comprehensive collection of papers that provide an integrative view on cybersecurity. It discusses theories, problems and solutions on the relevant ethical issues involved. This work is sorely needed in a world where cybersecurity has become indispensable to protect trust and confidence in the digital infrastructure whilst respecting fundamental values like equality, fairness, freedom, or privacy. The book has a strong practical focus as it includes case studies outlining ethical issues in cybersecurity and presenting guidelines and other measures to tackle those issues. It is thus not only relevant for academics but also for practitioners in cybersecurity such as providers of security software, governmental CERTs or Chief Security Officers in companies

An Empirical Assessment of the Effectiveness of Deception for Cyber Defense

The threat of cyber attacks is a growing concern across the world, leading to an increasing need for sophisticated cyber defense techniques. The Tularosa Study, was designed and conducted to understand how defensive deception, both cyber and psychological, affects cyber attackers Ferguson-Walter et al. [2019c]. More specifically, for this empirical study, cyber deception refers to a decoy system and psychological deception refers to false information of the presence of defensive deception techniques on the network. Over 130 red teamers participated in a network penetration test over two days in which we controlled both the presence of and explicit mention of deceptive defensive techniques. To our knowledge, this represents the largest study of its kind ever conducted on a skilled red team population. In addition to the abundant host and network data collected, we conducted a battery of questionnaires, e.g., experience, personality; and cognitive tasks, e.g., fluid intelligence, working memory; as well as physiological measures, e.g., galvanic skin response (GSR), heart rate, to be correlated with the cyber events at a later date. The design and execution of this study and the lessons learned are a major contribution of this thesis. I investigate the effectiveness of decoy systems for cyber defense by comparing performance across all experimental conditions. Results support a new finding that the combination of the presence of deception and the true information that deception is present has the greatest effect on cyber attackers, when compared to a control condition in which no deception was used. Evidence of cognitive biases in the red teamers’ behavior is then detailed and explained, to further support our theory of oppositional human factors (OHF). The final chapter discusses how elements of the experimental design contribute to the validity of assessing the effectiveness of cyber deception and reviews trade-offs and lessons learned

Wide spectrum attribution: Using deception for attribution intelligence in cyber attacks

Modern cyber attacks have evolved considerably. The skill level required to conduct a cyber attack is low. Computing power is cheap, targets are diverse and plentiful. Point-and-click crimeware kits are widely circulated in the underground economy, while source code for sophisticated malware such as Stuxnet is available for all to download and repurpose. Despite decades of research into defensive techniques, such as firewalls, intrusion detection systems, anti-virus, code auditing, etc, the quantity of successful cyber attacks continues to increase, as does the number of vulnerabilities identified. Measures to identify perpetrators, known as attribution, have existed for as long as there have been cyber attacks. The most actively researched technical attribution techniques involve the marking and logging of network packets. These techniques are performed by network devices along the packet journey, which most often requires modification of existing router hardware and/or software, or the inclusion of additional devices. These modifications require wide-scale infrastructure changes that are not only complex and costly, but invoke legal, ethical and governance issues. The usefulness of these techniques is also often questioned, as attack actors use multiple stepping stones, often innocent systems that have been compromised, to mask the true source. As such, this thesis identifies that no publicly known previous work has been deployed on a wide-scale basis in the Internet infrastructure. This research investigates the use of an often overlooked tool for attribution: cyber de- ception. The main contribution of this work is a significant advancement in the field of deception and honeypots as technical attribution techniques. Specifically, the design and implementation of two novel honeypot approaches; i) Deception Inside Credential Engine (DICE), that uses policy and honeytokens to identify adversaries returning from different origins and ii) Adaptive Honeynet Framework (AHFW), an introspection and adaptive honeynet framework that uses actor-dependent triggers to modify the honeynet envi- ronment, to engage the adversary, increasing the quantity and diversity of interactions. The two approaches are based on a systematic review of the technical attribution litera- ture that was used to derive a set of requirements for honeypots as technical attribution techniques. Both approaches lead the way for further research in this field

Human Factors in Secure Software Development

While security research has made significant progress in the development of theoretically secure methods, software and algorithms, software still comes with many possible exploits, many of those using the human factor. The human factor is often called ``the weakest link'' in software security. To solve this, human factors research in security and privacy focus on the users of technology and consider their security needs. The research then asks how technology can serve users while minimizing risks and empowering them to retain control over their own data. However, these concepts have to be implemented by developers whose security errors may proliferate to all of their software's users. For example, software that stores data in an insecure way, does not secure network traffic correctly, or otherwise fails to adhere to secure programming best practices puts all of the software's users at risk. It is therefore critical that software developers implement security correctly. However, in addition to security rarely being a primary concern while producing software, developers may also not have extensive awareness, knowledge, training or experience in secure development. A lack of focus on usability in libraries, documentation, and tools that they have to use for security-critical components may exacerbate the problem by blowing up the investment of time and effort needed to "get security right". This dissertation's focus is how to support developers throughout the process of implementing software securely. This research aims to understand developers' use of resources, their mindsets as they develop, and how their background impacts code security outcomes. Qualitative, quantitative and mixed methods were employed online and in the laboratory, and large scale datasets were analyzed to conduct this research. This research found that the information sources developers use can contribute to code (in)security: copying and pasting code from online forums leads to achieving functional code quickly compared to using official documentation resources, but may introduce vulnerable code. We also compared the usability of cryptographic APIs, finding that poor usability, unsafe (possibly obsolete) defaults and unhelpful documentation also lead to insecure code. On the flip side, well-thought out documentation and abstraction levels can help improve an API's usability and may contribute to secure API usage. We found that developer experience can contribute to better security outcomes, and that studying students in lieu of professional developers can produce meaningful insights into developers' experiences with secure programming. We found that there is a multitude of online secure development advice, but that these advice sources are incomplete and may be insufficient for developers to retrieve help, which may cause them to choose un-vetted and potentially insecure resources. This dissertation supports that (a) secure development is subject to human factor challenges and (b) security can be improved by addressing these challenges and supporting developers. The work presented in this dissertation has been seminal in establishing human factors in secure development research within the security and privacy community and has advanced the dialogue about the rigorous use of empirical methods in security and privacy research. In these research projects, we repeatedly found that usability issues of security and privacy mechanisms, development practices, and operation routines are what leads to the majority of security and privacy failures that affect millions of end users

Unveiling the core of IoT: comprehensive review on data security challenges and mitigation strategies

The Internet of Things (IoT) is a collection of devices such as sensors for collecting data, actuators that perform mechanical actions on the sensor's collected data, and gateways used as an interface for effective communication with the external world. The IoT has been successfully applied to various fields, from small households to large industries. The IoT environment consists of heterogeneous networks and billions of devices increasing daily, making the system more complex and this need for privacy and security of IoT devices become a major concern. The critical components of IoT are device identification, a large number of sensors, hardware operating systems, and IoT semantics and services. The layers of a core IoT application are presented in this paper with the protocols used in each layer. The security challenges at various IoT layers are unveiled in this review paper along with the existing mitigation strategies such as machine learning, deep learning, lightweight encryption techniques, and Intrusion Detection Systems (IDS) to overcome these security challenges and future scope. It has been concluded after doing an intensive review that Spoofing and Distributed Denial of Service (DDoS) attacks are two of the most common attacks in IoT applications. While spoofing tricks systems by impersonating devices, DDoS attacks flood IoT systems with traffic. IoT security is also compromised by other attacks, such as botnet attacks, man-in-middle attacks etc. which call for strong defenses including IDS framework, deep neural networks, and multifactor authentication system