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Exploiting Switching Noise for Stealthy Data Exfiltration from Desktop Computers

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Exploiting Switching Noise for Stealthy Data Exfiltration from Desktop Computers Your Noise, My Signal: Exploiting Switching Noise for Stealthy Data Exfiltration from Desktop Computers Zhihui Shao∗ Mohammad A. Islam∗† Shaolei Ren University of California, Riverside University of Texas at Arlington University of California, Riverside [email protected] [email protected] [email protected] ABSTRACT program’s usage pattern of CPU resources, if detected by another Attacks based on power analysis have been long existing and stud- program, can be modulated for information transfer between the ied, with some recent works focused on data exfiltration from victim two [50, 57]. Consequently, to mitigate data theft risks, enterprise systems without using conventional communications (e.g., WiFi). users commonly have restricted access to outside networks — all Nonetheless, prior works typically rely on intrusive direct power data transfer from and to the outside is tightly scrutinized. measurement, either by implanting meters in the power outlet or Nevertheless, such systems may still suffer from data exfiltration tapping into the power cable, thus jeopardizing the stealthiness of at- attacks that bypass the conventional communications protocols tacks. In this paper, we propose NoDE (Noise for Data Exfiltration), (e.g., WiFi) by transforming the affected computer into a transmitter a new system for stealthy data exfiltration from enterprise desk- and establishing a covert channel. For example, the transmitting top computers. Specifically, NoDE achieves data exfiltration over computer can modulate the intensity of the generated acoustic a building’s power network by exploiting high-frequency voltage noise by varying its cooling fan or hard disk spinning speed to ripples (i.e., switching noises) generated by power factor correction carry 1/0 bit information (e.g., a high fan noise represents “1” and circuits built into today’s computers. Located at a distance and even “0” otherwise), while a nearby receiver with a microphone can hear from a different room, the receiver can non-intrusively measure the noise and decode the carried bits [8, 32, 34, 38]. Likewise, the the voltage of a power outlet to capture the high-frequency switch- power consumption [35, 73], the amount of generated heat [31], the ing noises for online information decoding without supervised electromagnetic interference (EMI) [29, 30], the system status LEDs training/learning. To evaluate NoDE, we run experiments on seven [37, 55], and magnetic signal (to escape a Faraday cage) [36, 58] can different computers from top vendors and using top-brand power all be modulated in a similar manner for data exfiltration. supply units. Our results show that for a single transmitter, NoDE Our contribution. We contribute to the existing body of re- achieves a rate of up to 28.48 bits/second with a distance of 90 feet search by designing a new data exfiltration system, called NoDE (27.4 meters) without the line of sight, demonstrating a practically (Noise for Data Exfiltration), where a malware modulates the vic- stealthy threat. Based on the orthogonality of switching noise fre- tim computer’s power consumption to send data over a building’s quencies of different computers, we also demonstrate simultaneous power network to the attacker’s receiver. The key novelty is that data exfiltration from four computers using only one receiver. Fi- NoDE uniquely exploits high-frequency voltage ripples (i.e., elec- nally, we present a few possible defenses, such as installing noise tronic switching noises) generated by power factor correction (PFC) filters, and discuss their limitations. circuits built into today’s power supply units for power-consuming devices like computers. Like the existing data exfiltration attacks KEYWORDS (Table 3), NoDE exhibits several desirable properties: a reasonable achievable bit rate (28.48 bits/s), good effective distance (27.4 me- Covert channel, data exfiltration, power analysis, switching noise ters), and no line-of-sight requirement. Additionally, based on an in-depth investigation of how PFC-induced switching noises relate 1 INTRODUCTION to a computer’s power consumption, NoDE adds the following two The total number of registered malware samples has grown by 36% distinguishing features to the literature. in the past year and reached an all-time high of 690 million, let • arXiv:2001.06729v2 [cs.CR] 27 Jan 2020 Indirect power measurement. NoDE uses indirect power mea- alone the huge number of undiscovered malware [59]. Importantly, surement that does not require any tampering of the building’s more than 70% of the malware threats are in the form of phishing, power network and hence is more stealthy. Here, being indirect spywares, and Trojans that aim at stealing sensitive information, means that the target computer’s current does not directly flow especially from end users in companies, universities, among others through the attacker’s sensing device at the receiver; instead, the (which we collectively refer to as enterprise) [70]. receiver only measures voltage signals containing PFC-induced In the wake of growing risks of data theft, a proactive defense switching noises which we find are correlated with the target com- is to keep sensitive data within an enterprise network at all times. puter’s power/current. Nonetheless, the existing power-based data Nonetheless, this approach is vulnerable to various types of covert exfiltration attacks rely on direct power measurement and hence channel attacks, through which sensitive data is stealthily trans- are less stealthy [23, 35, 73]: a power meter is directly connected to ferred to a program that can access external networks and eventu- the outlet or a sensing apparatus is placed along the cable directly ally send information to the outside [11, 50, 69]. For example, one powering the target device. • Simultaneous data exfiltration. We identify the (approximate) ∗Both authors contribute equally to this work. orthogonality nature of PFC-induced switching noises in practice, †This work was partially done while M. A. Islam was at UC Riverside. ACM SIGMETRICS, June 08–12, 2020, Boston, MA Zhihui Shao, Mohammad A. Islam, and Shaolei Ren thus allowing simultaneous data exfiltration from multiple comput- 2 FEATURES OF NODE AND PRELIMINARIES ers to a single receiver without much interference. Thus, if multiple In this section, we first discuss NoDE’s distinguishing features computers within the same power network are infected, only a and advantages under its own subclass of power analysis-based single receiver is needed to exfiltrate data from these computers in side/covert channel attacks. Then, we provide a note on the current parallel. This results in a higher overall exfiltration rate due to the PFC design in power electronics. multiple parallel data streams. More concretely, we focus on an enterprise environment, with the goal of stealthy data exfiltration from a desktop computer. Note 2.1 Power Analysis-based Attacks that, we do not target military-grade systems that have sophis- NoDE falls under the power analysis-based attacks, and we identify ticated and expensive defense against information leakages (e.g., the key differences of NoDE from the existing works. With power TEMPEST [26]). We first observe that the amplitude information of usage information of the victim, prior studies have achieved se- a computer’s electric current, and hence the power consumption, cret key extraction from smart cards and mobile devices [6, 23, 56], is contained in the voltage at any other power outlet connected to anomaly detection in embedded systems [14, 54, 66], tracking web- the same building’s power network. sites [13, 79], among others. Besides the orthogonal context and In practice, however, it is very challenging to directly extract the objective, our work stands apart from the prior studies in the fol- current amplitude of the target computer from the voltage measure- lowing key aspects. ment, which consists of a blend of current amplitude information Power measurement. A prominent assumption made by many of all the devices within the same power network (Section 4.1). existing attacks is that the target system’s power consumption (or This is further compounded by the power grid’s random voltage current) can be directly measured [13, 79]. Nonetheless, this can fluctuations which can be several order-of-magnitude larger than only be accomplished if the sensing apparatus is placed directly the voltage variation caused by current amplitude variations. inside the target system or at the nearest power outlet (indicated by We find that all desktop computers today are mandated tohave Fig. 1(a) and ○A in Fig. 1(b)). Moreover, the way that the transmitter’s built-in power PFC circuits in their power supply units to reduce current is measured (e.g., measuring current at ○B in Fig. 1(b)) [35] harmonics [18, 43, 64]. Importantly, these PFC circuits result in results in a very low bit rate because of strong interference from prominent high-frequency current ripples between 40kHz and other computers and/or devices. 150kHz [64], whose amplitude changes with the computer’s power By sharp contrast, NoDE can collect voltage signals from any consumption — the higher power consumption, the taller ripples, outlet within the same power network as the transmitter, and iden- and vice-versa. These high-frequency current ripples also produce tifies and focuses on a unique frequency band for each transmitter, high-frequency voltage ripples at other power outlets, which are re- thus achieving stealthy data exfiltration (even simultaneously from ferred to switching noises. Thus, by properly filtering the received multiple transmitters). voltage signals at a power outlet, switching noises can be retained Offline training. The studies on side channel attacks using and the receiver is able to successfully extract information about power analysis are prolific, e.g., recognizing TV content out of volt- the transmitter’s modulated current amplitude. Further, the switch- age signal measurement from a nearby outlet [19] and identifying ing noise frequencies are typically different for different computers human gestures using body-induced electric signals [15].
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