Characterizing the IRC-based Botnet Phenomenon

Botnets, networks of compromised machines that can be remotely controlled by an attacker, are one of the most common attack platforms nowadays. They can, for example, be used to launch distributed denial-of-service (DDoS) attacks, steal sensitive information, or send spam emails. A long-term measurement study of botnet activities is useful as a basis for further research on global botnet mitigation and disruption techniques. We have built a distributed and fully-automated botnet measurement system which allows us to collect data on the botnet activity we observe in China. Based on the analysis of tracking records of 3,290 IRC-based botnets during a period of almost twelve months, this paper presents several novel results of botnet activities which can only be measured via long-term measurements. These include. amongst others, botnet lifetime, botnet discovery trends and distributions, command and control channel distributions, botnet size and end-host distributions. Furthermore, our measurements confirm and extend several previous results from this area. Our results show that the botnet problem is of global scale, with a scattered distribution of the control infrastructure and also a scattered distribution of the victims. Furthermore, the control infrastructure itself is rather flexible, with an average lifetime of a Command \& Control server of about 54 days. These results can also leverage research in the area of botnet detection, mitigation, and disruption: only by understanding the problem in detail, we can develop efficient counter measures

A Covert Data Transport Protocol

Both enterprise and national firewalls filter network connections. For data forensics and botnet removal applications, it is important to establish the information source. In this paper, we describe a data transport layer which allows a client to transfer encrypted data that provides no discernible information regarding the data source. We use a domain generation algorithm (DGA) to encode AES encrypted data into domain names that current tools are unable to reliably differentiate from valid domain names. The domain names are registered using (free) dynamic DNS services. The data transmission format is not vulnerable to Deep Packet Inspection (DPI).Comment: 8 pages, 10 figures, conferenc

Flooding attacks to internet threat monitors (ITM): Modeling and counter measures using botnet and honeypots

The Internet Threat Monitoring (ITM),is a globally scoped Internet monitoring system whose goal is to measure, detect, characterize, and track threats such as distribute denial of service(DDoS) attacks and worms. To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address flooding attack against ITM system in which the attacker attempt to exhaust the network and ITM's resources, such as network bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. Based on this model we generalize the flooding attacks and propose an effective attack detection using Honeypots

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

A Threat to Cyber Resilience : A Malware Rebirthing Botnet

This paper presents a threat to cyber resilience in the form of a conceptual model of a malware rebirthing botnet which can be used in a variety of scenarios. It can be used to collect existing malware and rebirth it with new functionality and signatures that will avoid detection by AV software and hinder analysis. The botnet can then use the customized malware to target an organization with an orchestrated attack from the member machines in the botnet for a variety of malicious purposes, including information warfare applications. Alternatively, it can also be used to inject known malware signatures into otherwise non malicious code and traffic to overloading the sensors and processing systems employed by intrusion detection and prevention systems to create a denial of confidence of the sensors and detection systems. This could be used as a force multiplier in asymmetric warfare applications to create confusion and distraction whilst attacks are made on other defensive fronts

Reaction to New Security Threat Class

Each new identified security threat class triggers new research and development efforts by the scientific and professional communities. In this study, we investigate the rate at which the scientific and professional communities react to new identified threat classes as it is reflected in the number of patents, scientific articles and professional publications over a long period of time. The following threat classes were studied: Phishing; SQL Injection; BotNet; Distributed Denial of Service; and Advanced Persistent Threat. Our findings suggest that in most cases it takes a year for the scientific community and more than two years for industry to react to a new threat class with patents. Since new products follow patents, it is reasonable to expect that there will be a window of approximately two to three years in which no effective product is available to cope with the new threat class

Using Botnet Technologies to Counteract Network Traffic Analysis

Botnets have been problematic for over a decade. They are used to launch malicious activities including DDoS (Distributed-Denial-of-Service), spamming, identity theft, unauthorized bitcoin mining and malware distribution. A recent nation-wide DDoS attacks caused by the Mirai botnet on 10/21/2016 involving 10s of millions of IP addresses took down Twitter, Spotify, Reddit, The New York Times, Pinterest, PayPal and other major websites. In response to take-down campaigns by security personnel, botmasters have developed technologies to evade detection. The most widely used evasion technique is DNS fast-flux, where the botmaster frequently changes the mapping between domain names and IP addresses of the C&C server so that it will be too late or too costly to trace the C&C server locations. Domain names generated with Domain Generation Algorithms (DGAs) are used as the \u27rendezvous\u27 points between botmasters and bots. This work focuses on how to apply botnet technologies (fast-flux and DGA) to counteract network traffic analysis, therefore protecting user privacy. A better understanding of botnet technologies also helps us be pro-active in defending against botnets. First, we proposed two new DGAs using hidden Markov models (HMMs) and Probabilistic Context-Free Grammars (PCFGs) which can evade current detection methods and systems. Also, we developed two HMM-based DGA detection methods that can detect the botnet DGA-generated domain names with/without training sets. This helps security personnel understand the botnet phenomenon and develop pro-active tools to detect botnets. Second, we developed a distributed proxy system using fast-flux to evade national censorship and surveillance. The goal is to help journalists, human right advocates and NGOs in West Africa to have a secure and free Internet. Then we developed a covert data transport protocol to transform arbitrary message into real DNS traffic. We encode the message into benign-looking domain names generated by an HMM, which represents the statistical features of legitimate domain names. This can be used to evade Deep Packet Inspection (DPI) and protect user privacy in a two-way communication. Both applications serve as examples of applying botnet technologies to legitimate use. Finally, we proposed a new protocol obfuscation technique by transforming arbitrary network protocol into another (Network Time Protocol and a video game protocol of Minecraft as examples) in terms of packet syntax and side-channel features (inter-packet delay and packet size). This research uses botnet technologies to help normal users have secure and private communications over the Internet. From our botnet research, we conclude that network traffic is a malleable and artificial construct. Although existing patterns are easy to detect and characterize, they are also subject to modification and mimicry. This means that we can construct transducers to make any communication pattern look like any other communication pattern. This is neither bad nor good for security. It is a fact that we need to accept and use as best we can