Two Heads are Better than One: A Theoretical Model for Cybersecurity Intelligence Sharing (CIS) between Organisations

So-called ‘social bots’ have garnered a lot of attention lately. Previous research showed that they attempted to influence political events such as the Brexit referendum and the US presidential elections. It remains, however, somewhat unclear what exactly can be understood by the term ‘social bot’. This paper addresses the need to better understand the intentions of bots on social media and to develop a shared understanding of how ‘social’ bots differ from other types of bots. We thus describe a systematic review of publications that researched bot accounts on social media. Based on the results of this literature review, we propose a scheme for categorising bot accounts on social media sites. Our scheme groups bot accounts by two dimensions – Imitation of human behaviour and Intent

Threat Intelligence Sharing Platforms: An Exploratory Study of Software Vendors and Research Perspectives

In the last couple of years, organizations have demonstrated an increased willingness to exchange information and knowledge regarding vulnerabilities, threats, incidents and mitigation strategies in order to collectively protect against today’s sophisticated cyberattacks. As a reaction to this trend, software vendors started to create offerings that facilitate this exchange and appear under the umbrella term “Threat Intelligence Sharing Platforms”. To which extent these platforms provide the needed means for exchange and information sharing remains unclear as they lack a common definition, innovation in this area is mostly driven by vendors and empirical research is rare. To close this gap, we examine the state-of-the-art software vendor landscape of these platforms, identify gaps and present arising research perspectives. Therefore, we conducted a systematic study of 22 threat intelligence sharing platforms and compared them. We derived eight key findings and discuss how existing gaps should be addressed by future research

How Good is Your Data? Investigating the Quality of Data Generated During Security Incident Response Investigations

An increasing number of cybersecurity incidents prompts organizations to explore alternative security solutions, such as threat intelligence programs. For such programs to succeed, data needs to be collected, validated, and recorded in relevant datastores. One potential source supplying these datastores is an organization’s security incident response team. However, researchers have argued that these teams focus more on eradication and recovery and less on providing feedback to enhance organizational security. This prompts the idea that data collected during security incident investigations may be of insufficient quality for threat intelligence analysis. While previous discussions focus on data quality issues from threat intelligence sharing perspectives, minimal research examines the data generated during incident response investigations. This paper presents the results of a case study identifying data quality challenges in a Fortune 500 organization’s incident response team. Furthermore, the paper provides the foundation for future research regarding data quality concerns in security incident response

Distributed Ledger Technology for the systematic Investigation and Reduction of Information Asymmetry in Collaborative Networks

Costs, risks and inefficiencies in Collaborative Networks (CNs) resulting from information asymmetries have been discussed in the scientific community for years. In this work, supply chain networks, as common representative of CNs, are used as object of investigation. Therein, problems and requirements of interorganizational information exchange are elaborated as well as the potential role Distributed Ledger Technology (DLT) could play to address them. As major challenge, convincing all relevant network partners to resolve asymmetric information by sharing sensitive data is identified. To face this issue, the value of shared information is prioritized as a motivational aspect. Finally, we propose a search process to systematically assess the benefits of information sharing in collaborative networks. To coordinate and implement this process regarding the derived requirements of CNs we propose system components based on DLT design patterns

Navigating the Cyber Threat Landscape: A Comprehensive Analysis of Attacks and Security in the Digital Age

In this contemporary digital age, cybersecurity stands as a crucial linchpin amid the expanding role of technology in our lives, encountering numerous challenges. This review addresses the imperative need for robust cybersecurity measures as malicious actors continually innovate methods to exploit vulnerabilities in computer systems, networks, and data. The exploration delves into the multifaceted realm of cybersecurity attacks, unveiling the evolving threat landscape and their profound implications. From cybercriminals utilizing phishing attacks to the covert tactics of malware and the disruptive potential of Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks, including Phishing, Zero-Day Exploits, Man-in-the-Middle, and SQL Injection Attacks, the cybersecurity battleground is ever-expanding. The study systematically categorizes cyber threats, scrutinizes their distinctive characteristics, and elucidates the modus operandi of each attack type. Through a meticulous dissection of cybercriminal methods and motivations and a comprehensive evaluation of countermeasure efficacy, this review offers indispensable insights for securing our digital future in an era marked by escalating interconnectivity and technological dependence

A comparative analysis of cyber-threat intelligence sources, formats and languages

The sharing of cyber-threat intelligence is an essential part of multi-layered tools used to protect systems and organisations from various threats. Structured standards, such as STIX, TAXII and CybOX, were introduced to provide a common means of sharing cyber-threat intelligence and have been subsequently much-heralded as the de facto industry standards. In this paper, we investigate the landscape of the available formats and languages, along with the publicly available sources of threat feeds, how these are implemented and their suitability for providing rich cyber-threat intelligence. We also analyse at a sample of cyber-threat intelligence feeds, the type of data they provide and the issues found in aggregating and sharing the data. Moreover, the type of data supported by various formats and languages is correlated with the data needs for several use cases related to typical security operations. The main conclusions drawn by our analysis suggest that many of the standards have a poor level of adoption and implementation, with providers opting for custom or traditional simple formats

Exploring Incentives and Challenges for Cybersecurity Intelligence Sharing (CIS) across Organizations: A Systematic Review

Cybersecurity intelligence sharing (CIS) has gained significance as an organizational function to protect critical information assets, manage cybersecurity risks, and improve cybersecurity operations. However, few studies have synthesized accumulated scholarly knowledge on CIS practices across disciplines. Synthesizing the pertinent literature through a structured literature review, we investigated the incentives and challenges that influence organizations around adopting CIS practices. We used the overarching TOE framework to categorize these factors and propose a theoretical framework to establish common ground for future studies. We also developed a holistic and inclusive definition for cybersecurity intelligence that we present in the paper. We found 46 papers on CIS in different disciplines and analyzed them to answer our research questions. We identified 35 factors that we classified according to the TOE framework. With this paper, we facilitate further theory development by overviewing theories that researchers can use as a basis for CIS studies, suggesting future directions, providing a reference source, and developing a reference CIS framework for IS scholars

Cyber threat intelligence sharing: Survey and research directions

Cyber Threat Intelligence (CTI) sharing has become a novel weapon in the arsenal of cyber defenders to proactively mitigate increasing cyber attacks. Automating the process of CTI sharing, and even the basic consumption, has raised new challenges for researchers and practitioners. This extensive literature survey explores the current state-of-the-art and approaches different problem areas of interest pertaining to the larger field of sharing cyber threat intelligence. The motivation for this research stems from the recent emergence of sharing cyber threat intelligence and the involved challenges of automating its processes. This work comprises a considerable amount of articles from academic and gray literature, and focuses on technical and non-technical challenges. Moreover, the findings reveal which topics were widely discussed, and hence considered relevant by the authors and cyber threat intelligence sharing communities