A survey on technical threat intelligence in the age of sophisticated cyber attacks

Cyber-physical systems and their security issues

The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high-performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to address issues such as scalability, elasticity, reliability, security, sustainability, and application models. The proposed manifesto addresses them by identifying the major open challenges in Cloud computing, emerging trends, and impact areas. It then offers research directions for the next decade, thus helping in the realisation of Future Generation Cloud Computing.

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A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade

Threats that have been primarily targeting nation states and their associated entities have expanded the target zone to include the private and corporate sectors. This class of threats, well known as advanced persistent threats (APTs), are those that every nation and well-established organization fears and wants to protect itself against. While nation-sponsored APT attacks will always be marked by their sophistication, APT attacks that have become prominent in corporate sectors do not make it any less challenging for the organizations. The rate at which the attack tools and techniques are evolving is making any existing security measures inadequate. As defenders strive to secure every endpoint and every link within their networks, attackers are finding new ways to penetrate into their target systems. With each day bringing new forms of malware, having new signatures and behavior that is close to normal, a single threat detection system would not suffice. While it requires time and patience to perform APT, solutions that adapt to the changing behavior of APT attacker(s) are required. Several works have been published on detecting an APT attack at one or two of its stages, but very limited research exists in detecting APT as a whole from reconnaissance to cleanup, as such a solution demands complex correlation and fine-grained behavior analysis of users and systems within and across networks. Through this survey paper, we intend to bring all those methods and techniques that could be used to detect different stages of APT attacks, learning methods that need to be applied and where to make your threat detection framework smart and undecipherable for those adapting APT attackers. We also present different case studies of APT attacks, different monitoring methods, and mitigation methods to be employed for fine-grained control of security of a networked system. We conclude this paper with different challenges in defending against APT and opportunities for further research, ending with a note on what we learned during our writing of this paper.

A Survey on Advanced Persistent Threats: Techniques, Solutions, Challenges, and Research Opportunities

Combating advanced persistent threats

A Problem Shared is a Problem Halved: A Survey on the Dimensions of Collective Cyber Defense Through Security Information Sharing

Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection

Today's Industrial Control Systems (ICSs) operating in critical infrastructures (CIs) are becoming increasingly complex; moreover, they are extensively interconnected with corporate information systems for cost-efficient monitoring, management and maintenance. This exposes ICSs to modern advanced cyber threats. Existing security solutions try to prevent, detect, and react to cyber threats by employing security measures that typically do not cross the organization's boundaries. However, novel targeted multi-stage attacks such as Advanced Persistent Threats (APTs) take advantage of the interdependency between organizations. By exploiting vulnerabilities of various systems, APT campaigns intrude several organizations using them as stepping stones to reach the target infrastructure. A coordinated effort to timely reveal such attacks, and promptly deploy mitigation measures is therefore required. Organizations need to cooperatively exchange security-relevant information to obtain a broader knowledge on the current cyber threat landscape and subsequently obtain new insight into their infrastructures and timely react if necessary. Cyber security operation centers (SOCs), as proposed by the European NIS directive, are being established worldwide to achieve this goal. CI providers are asked to report to the responsible SOCs about security issues revealed in their networks. National SOCs correlate all the gathered data, analyze it and eventually provide support and mitigation strategies to the affiliated organizations. Although many of these tasks can be automated, human involvement is still necessary to enable SOCs to adequately take decisions on occurring incidents and quickly implement counteractions. In this paper we present a collaborative approach to cyber incident information management for gaining situational awareness on interconnected European CIs. We provide a scenario and an illustrative use-case for our approach; we propose a system architecture for a National SOC, defining the functional components and interfaces it comprises. We further describe the functionalities provided by the different system components to support SOC operators in performing incident management tasks.

A collaborative cyber incident management system for European interconnected critical infrastructures

Threats to modern ICT systems are rapidly changing these days. Organizations are not mainly concerned about virus infestation, but increasingly need to deal with targeted attacks. This kind of attacks are specifically designed to stay below the radar of standard ICT security systems. As a consequence, vendors have begun to ship self-learning intrusion detection systems with sophisticated heuristic detection engines. While these approaches are promising to relax the serious security situation, one of the main challenges is the proper evaluation of such systems under realistic conditions during development and before roll-out. Especially the wide variety of configuration settings makes it hard to find the optimal setup for a specific infrastructure. However, extensive testing in a live environment is not only cumbersome but usually also impacts daily business. In this paper, we therefore introduce an approach of an evaluation setup that consists of virtual components, which imitate real systems and human user interactions as close as possible to produce system events, network flows and logging data of complex ICT service environments. This data is a key prerequisite for the evaluation of modern intrusion detection and prevention systems. With these generated data sets, a system's detection performance can be accurately rated and tuned for very specific settings.

Giuseppe Settanni

Papers

Combating advanced persistent threats

A Problem Shared is a Problem Halved: A Survey on the Dimensions of Collective Cyber Defense Through Security Information Sharing

Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection

A collaborative cyber incident management system for European interconnected critical infrastructures

Semi-synthetic data set generation for security software evaluation