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

Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

Advanced monitoring in P2P botnets

Botnets are increasingly being held responsible for most of the cybercrimes that occur nowadays. They are used to carry out malicious activities like banking credential theft and Distributed Denial of Service (DDoS) attacks to generate profit for their owner, the botmaster. Traditional botnets utilized centralized and decentralized Command-and-Control Servers (C2s). However, recent botnets have been observed to prefer P2P-based architectures to overcome some of the drawbacks of the earlier architectures. A P2P architecture allows botnets to become more resilient and robust against random node failures and targeted attacks. However, the distributed nature of such botnets requires the defenders, i.e., researchers and law enforcement agencies, to use specialized tools such as crawlers and sensor nodes to monitor them. In return to such monitoring, botmasters have introduced various countermeasures to impede botnet monitoring, e.g., automated blacklisting mechanisms. The presence of anti-monitoring mechanisms not only render any gathered monitoring data to be inaccurate or incomplete, it may also adversely affect the success rate of botnet takedown attempts that rely upon such data. Most of the existing monitoring mechanisms identified from the related works only attempt to tolerate anti-monitoring mechanisms as much as possible, e.g., crawling bots with lower frequency. However, this might also introduce noise into the gathered data, e.g., due to the longer delay for crawling the botnet. This in turn may also reduce the quality of the data. This dissertation addresses most of the major issues associated with monitoring in P2P botnets as described above. Specifically, it analyzes the anti-monitoring mechanisms of three existing P2P botnets: 1) GameOver Zeus, 2)Sality, and 3) ZeroAccess, and proposes countermeasures to circumvent some of them. In addition, this dissertation also proposes several advanced anti-monitoring mechanisms from the perspective of a botmaster to anticipate future advancement of the botnets. This includes a set of lightweight crawler detection mechanisms as well as several novel mechanisms to detect sensor nodes deployed in P2P botnets. To ensure that the defenders do not loose this arms race, this dissertation also includes countermeasures to circumvent the proposed anti-monitoring mechanisms. Finally, this dissertation also investigates if the presence of third party monitoring mechanisms, e.g., sensors, in botnets influences the overall churn measurements. In addition, churn models for Sality and ZeroAccess are also derived using fine-granularity churn measurements. The works proposed in this dissertation have been evaluated using either real-world botnet datasets, i.e., that were gathered using crawlers and sensor nodes, or simulated datasets. Evaluation results indicate that most of the anti-monitoring mechanisms implemented by existing botnets can either be circumvented or tolerated to obtain monitoring data with a better quality. However, many crawlers and sensor nodes in existing botnets are found vulnerable to the antimonitoring mechanisms that are proposed from the perspective of a botmaster in this dissertation. Analysis of the fine-grained churn measurements for Sality and ZeroAccess indicate that churn in these botnets are similar to that of regular P2P file-sharing networks like Gnutella and Bittorent. In addition, the presence of highly responsive sensor nodes in the botnets are found not influencing the overall churn measurements. This is mainly due to low number of sensor nodes currently deployed in the botnets. Existing and future botnet monitoring mechanisms should apply the findings of this dissertation to ensure high quality monitoring data, and to remain undetected from the bots or the botmasters

Large-Scale Distributed Coalition Formation

The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the ability to efficiently locate agents by resources that agents possess. Combined with a task model defined for CyberCraft, this technology feeds into an algorithm that constructs task coalitions in a large-scale DMAS. Experiments reveal the flexibility and effectiveness of these concepts for achieving maximum work throughput in a simulated CyberCraft environment