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Iot-Botnet Detection and Isolation by Access Routers 2018 9th International Conference on the Network of the Future (NOF) IoT-Botnet Detection and Isolation by Access Routers Christian Dietz∗y, Raphael Labaca Castro∗, Jessica Steinbergery, Cezary Wilczak∗, Marcel Antzek∗, Anna Sperottoy and Aiko Prasy ∗ Research Institute CODE yDesign and Analysis of Communication Systems Bundeswehr University Munich University of Twente Neubiberg, Germany Enschede, The Netherlands Email:fChristian.Dietz, Raphael.Labaca, Email:fC.Dietz, J.Steinberger, Cezary.Wilczak, [email protected] A.Sperotto, [email protected] Abstract—In recent years, emerging technologies such as the The main attack techniques used by IoT botnets exploit Internet of Things gain increasing interest in various commu- security vulnerabilities and make use of sophisticated, complex nities. However, the majority of IoT devices have little or no and multi-vector large-scale cyber attacks based on flooding protection at software and infrastructure levels and thus are also opening up new vulnerabilities that might be misused by and Water Torture techniques whereas traditional Botnets cybercriminals to perform large-scale cyber attacks by means make use of Reflection and Amplification. In particular, the IoT of IoT botnets. These kind of attacks lead to infrastructure botnet Mirai used 10 predefined attack vectors [7] including and service outages and cause enormous financial loss, image generic routing encapsulation (GRE) flood, TCP STOMP and and reputation damage. One approach to proactively block DNS Water Torture technique and mainly performed volumet- the spreading of such IoT botnets is to automatically scan for vulnerable IoT devices and isolate them from the Internet ric, application-layer, and TCP state-exhaustion attacks [6]. before they are compromised and also become part of the IoT botnet. The goal of this paper is to present an IoT botnet Given the quantity of IoT devices, the sophisticated complex detection and isolation approach at the level of access routers attack vectors and the trend of reached attack intensities, DDoS that makes IoT devices more attack resilient. We show that our attacks of IoT botnets could lead to enormous financial loss, IoT botnet detection and isolation approach helps to prevent the compromise of IoT devices without the need to have in-depth image and reputation damage [8]. One approach to proactively technical administration knowledge, and hence make it viable block the spreading of such botnets is to automatically scan for customers and end users. for vulnerable IoT devices and isolate them from the Internet before they are compromised and also become part of the IoT I. INTRODUCTION botnet to perform malicious actions. In recent years, the world and our daily life became increasingly connected [1]. These interconnections built a To overcome critical security issues in IoT devices and network of billions of connected general-purpose devices such make them more attack resilient, we propose an IoT botnet as smartphones, PCs, wearable tech or everyday household detection and isolation approach. Thus this research focuses objects that are referred to as the Internet of Things (IoT). to answer the following three research questions: i) How and The amount of IoT devices is still increasing and thus Gart- where can vulnerable IoT devices be protected against IoT ner. Inc [1] forecasts an amount of 20:4 billion IoT devices in botnet infections, in particular Mirai? ii) How can detection use worldwide by 2020. and isolation approaches adapt to new derivatives of the Mirai Despite the steady year-over-year growth in the amount of family? iii) How can current barriers (such as costs, techni- IoT devices, the security of these has been criticized over the cal knowledge, hidden install routines of available detection past few years [2], [3] as they have little or no protection at solution) be eliminated? software and infrastructure levels [4]. The lack of protection of IoT devices along with poor Therefore the main contributions of this paper are: i) we security update management result in serious security flaws provide a structured and detailed literature research resulting that gain increasing interest and are abused by cybercrimi- in an overview of existing automated scanning and isolations nals. In 2016, they compromised approximately 600 000 IoT solutions in the context of IoT botnets. ii) we provide an open- devices to set up an IoT botnet [5] and launch a large scale source and resource efficient detection and isolation approach cyber attack, namely a Distributed Denial of Service (DDoS), at the level of access routers to detect and mitigate the effects with a traffic peak of 1:1 Tbps [6]. This DDoS attack led to of large-scale DDoS attacks launched by IoT botnets. iii.) we infrastructure and service outages affecting companies such provided a reference implementation of our solution that is as AirBnB, Amazon, GitHub, PayPal, Netflix, Spotify and extensible for other IoT botnets and portable to other router Twitter [5], [6]. platforms. 978-1-5386-8503-7/18/$31.00 ©2018 IEEE 88 2018 9th International Conference on the Network of the Future (NOF) Phase: Scan & Detection powerful enough to perform Denials-of-Services while lacking maintenance from security perspective, which allows criminals to leverage powerful attacks by combining a large number of Connection Code and Obtainment of device compromised devices. One example of such an IoT botnet Scan open Access to the command of to C&C to ports IoT device administrator download injection privileges harmful script is Mirai. However since the source code has been leaked on Phase: Isolation the Internet many variants evolved including Satori, Okiru, Persirai, Masuta and Puremasuta [14]. In general botnets have a similar behavior regardless of Attacker Spread and The script Execution of controls the attack other deletes itself the malicious their variant or the malware family they belong to. More botnet from a vulnerable and runs script C&C centre devices in-memory specifically, IoT and regular botnets share similar botnet life cycles when compromising new devices. Fig. 1. Life cycle of an IoT botnet partially based on [9] In this paper, we refer to a bot as a compromised device remotely controlled by an attacker or botmaster. The life cycle of a typical IoT botnet is visualized in II. TERMINOLOGY Figure 1 and can be generally summarized into the following 7 In this section, we introduce the terms used throughout the stages: i) Scan the (inter)network for open ports on connected paper and thus support better understanding of our work. First, devices. ii) Brute-force the discovered ports to gain access we define SmartHome and IoT. Next, we generally describe the to victims. iii) Kill potential competitors on the infected term botnet and provide a main introduction of a general botnet hosts. iv) Create a command and control (C&C) channel with life cycle. Furthermore, we clarify the specific characteristics the botmaster. v) Execute and sometimes delete malicious of IoT botnets. script (runs in memory). vi) Spread through the network by searching for new instances. vii) Launch attacks or perform A. IoT and SmartHome other malicious actions. The term IoT refers to an application domain that integrates This life cycle was observed in Mirai [15] and in some of different technological and social fields [10]. According to its variants like Satori or Persirai [13]. Although the general IETF [11], ”The Internet of Things is the network of physical operation remains the same, some steps might differ such as objects or ”things” embedded with electronics, software, sen- the initial compromise. For example, instead of scanning the sors, and connectivity to enable objects to exchange data with network for open ports on devices, Satori attempts [16] to the manufacturer, operator and/or other connected devices.” connect on ports 37 215 and 52 869 using an exploit while We adhere to the definition of IoT presented in [11]. Within Persirai exploits [13] a reported zero-day vulnerability that this general definition of IoT devices SmartHomes represent provides access directly to the password data. Nevertheless, an application domain described as follows: ”SmartHomes once the IoT-devices are infected, all of them can be used are homes equipped with technology that provides the oc- to execute large-scale DDoS attacks (e.g., attack against the cupants with comprehensive information about the state of French cloud service provider OVH where peaks of 1.1 Tbps their home and allows them to control all connected devices, were registered using a Mirai botnet [6]). including remotely” [12]. Examples of such smart devices are cameras, TVs or fridges. Furthermore, ENISA [12] describes C. Detection and Defense SmartHome as ”a point of intense contact between networked Throughout this paper the term detection refers to identi- information technology and physical space. This will create fying vulnerabilities of connected IoT devices (e.g. open port new yet unknown threat and vulnerability models that are and default credentials) that can be used to compromise a the result of bringing together both the virtual and physical specific IoT device. We refer to detection as a proactively context”. We also adhere to the definition of SmartHome performed detection, which is done without triggering events presented in [12]. or user interaction and targets the first stage of the botnet life- cylce (see Figure 1). We consider defense as reactive, as it B. Botnet vs IoT Botnet is triggered by the detection output. Further defense refers to Botnets are networks of devices which have been infected the automated creation of firewall rules that isolate vulnerable with malware allowing a malicious actor to remotely control IoT devices from the Internet and thus prevent the device from them. Although botnets are not new, IoT botnets disrupted becoming part of a botnet. the way some attacks are performed over the last few years. That is because unlike regular botnets the goal of the mali- III.
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