Adaptive Traffic Fingerprinting for Darknet Threat Intelligence

Darknet technology such as Tor has been used by various threat actors for organising illegal activities and data exfiltration. As such, there is a case for organisations to block such traffic, or to try and identify when it is used and for what purposes. However, anonymity in cyberspace has always been a domain of conflicting interests. While it gives enough power to nefarious actors to masquerade their illegal activities, it is also the cornerstone to facilitate freedom of speech and privacy. We present a proof of concept for a novel algorithm that could form the fundamental pillar of a darknet-capable Cyber Threat Intelligence platform. The solution can reduce anonymity of users of Tor, and considers the existing visibility of network traffic before optionally initiating targeted or widespread BGP interception. In combination with server HTTP response manipulation, the algorithm attempts to reduce the candidate data set to eliminate client-side traffic that is most unlikely to be responsible for server-side connections of interest. Our test results show that MITM manipulated server responses lead to expected changes received by the Tor client. Using simulation data generated by shadow, we show that the detection scheme is effective with false positive rate of 0.001, while sensitivity detecting non-targets was 0.016+-0.127. Our algorithm could assist collaborating organisations willing to share their threat intelligence or cooperate during investigations.Comment: 26 page

Leveraging Conventional Internet Routing Protocol Behavior to Defeat DDoS and Adverse Networking Conditions

The Internet is a cornerstone of modern society. Yet increasingly devastating attacks against the Internet threaten to undermine the Internet\u27s success at connecting the unconnected. Of all the adversarial campaigns waged against the Internet and the organizations that rely on it, distributed denial of service, or DDoS, tops the list of the most volatile attacks. In recent years, DDoS attacks have been responsible for large swaths of the Internet blacking out, while other attacks have completely overwhelmed key Internet services and websites. Core to the Internet\u27s functionality is the way in which traffic on the Internet gets from one destination to another. The set of rules, or protocol, that defines the way traffic travels the Internet is known as the Border Gateway Protocol, or BGP, the de facto routing protocol on the Internet. Advanced adversaries often target the most used portions of the Internet by flooding the routes benign traffic takes with malicious traffic designed to cause widespread traffic loss to targeted end users and regions. This dissertation focuses on examining the following thesis statement. Rather than seek to redefine the way the Internet works to combat advanced DDoS attacks, we can leverage conventional Internet routing behavior to mitigate modern distributed denial of service attacks. The research in this work breaks down into a single arc with three independent, but connected thrusts, which demonstrate that the aforementioned thesis is possible, practical, and useful. The first thrust demonstrates that this thesis is possible by building and evaluating Nyx, a system that can protect Internet networks from DDoS using BGP, without an Internet redesign and without cooperation from other networks. This work reveals that Nyx is effective in simulation for protecting Internet networks and end users from the impact of devastating DDoS. The second thrust examines the real-world practicality of Nyx, as well as other systems which rely on real-world BGP behavior. Through a comprehensive set of real-world Internet routing experiments, this second thrust confirms that Nyx works effectively in practice beyond simulation as well as revealing novel insights about the effectiveness of other Internet security defensive and offensive systems. We then follow these experiments by re-evaluating Nyx under the real-world routing constraints we discovered. The third thrust explores the usefulness of Nyx for mitigating DDoS against a crucial industry sector, power generation, by exposing the latent vulnerability of the U.S. power grid to DDoS and how a system such as Nyx can protect electric power utilities. This final thrust finds that the current set of exposed U.S. power facilities are widely vulnerable to DDoS that could induce blackouts, and that Nyx can be leveraged to reduce the impact of these targeted DDoS attacks

On the Design of Clean-Slate Network Control and Management Plane

We provide a design of clean-slate control and management plane for data networks using the abstraction of 4D architecture, utilizing and extending 4D’s concept of a logically centralized Decision plane that is responsible for managing network-wide resources. In this paper, a scalable protocol and a dynamically adaptable algorithm for assigning Data plane devices to a physically distributed Decision plane are investigated, that enable a network to operate with minimal configuration and human intervention while providing optimal convergence and robustness against failures. Our work is especially relevant in the context of ISPs and large geographically dispersed enterprise networks. We also provide an extensive evaluation of our algorithm using real-world and artificially generated ISP topologies along with an experimental evaluation using ns-2 simulator

Analysis of Effects of BGP Black Hole Routing on a Network like the NIPRNET

The Department of Defense (DoD) relies heavily on the Non-secure Internet Protocol Router Network (NIPRNET) to exchange information freely between departments, services, bases, posts, and ships. The NIPRNET is vulnerable to various attacks, to include physical and cyber attacks. One of the most frequently used cyber attacks by criminally motivated hackers is a Distributed Denial of Service (DDoS) attack. DDoS attacks can be used to exhaust network bandwidth and router processing capabilities, and as a leveraging tool for extortion. Border Gateway Protocol (BGP) black hole routing is a responsive defensive network technique for mitigating DDoS attacks. BGP black hole routing directs traffic destined to an Internet address under attack to a null address, essentially stopping the DDoS attack by dropping all traffic to the targeted system. This research examines the ability of BGP black hole routing to effectively defend a network like the NIPRNET from a DDoS attack, as well as examining two different techniques for triggering BGP black hole routing during a DDoS attack. This thesis presents experiments with three different DDoS attack scenarios to determine the effectiveness of BGP black hole routing. Remote-triggered black hole routing is then compared against customer-triggered black hole routing to examine how well each technique reacts under a DDoS attack. The results from this study show BGP black hole routing to be highly successful. It also shows that remote-triggered black hole routing is much more effective than customer-triggered

On the Effectiveness of BGP Hijackers That Evade Public Route Collectors

Routing hijack attacks have plagued the Internet for decades. After many failed mitigation attempts, recent Internet-wide BGP monitoring infrastructures relying on distributed route collection systems, called route collectors, give us hope that future monitor systems can quickly detect and ultimately mitigate hijacks. In this paper, we investigate the effectiveness of public route collectors with respect to future attackers deliberately engineering longer hijacks to avoid being recorded by route collectors. Our extensive simulations (and attacks we device) show that monitor-based systems may be unable to observe many carefully crafted hijacks diverting traffic from thousands of ASes. Hijackers could predict whether their attacks would propagate to some BGP feeders (i.e., monitors) of public route collectors. Then, manipulate BGP route propagation so that the attack never reaches those monitors. This observation remains true when considering plausible future Internet topologies, with more IXP links and up to 4 times more monitors peering with route collectors. We then evaluate the feasibility of performing hijacks not observed by route collectors in the real-world. We experiment with two classifiers to predict the monitors that are dangerous to report the attack to route collectors, one based on monitor proximities (i.e., shortest path lengths) and another based on Gao-Rexford routing policies. We show that a proximity-based classifier could be sufficient for the hijacker to identify all dangerous monitors for hijacks announced to peer-to-peer neighbors. For hijacks announced to transit networks, a Gao-Rexford classifier reduces wrong inferences by $\ge 91\%$ without introducing new misclassifications for existing dangerous monitors