A Secure Civil GNSS for Today
Many civil GNSS applications need secure, assured information for asset tracking, fleet management and the like. But there is also a growing demand for geosecurity location-based services such as hardware configuration and management, virtual site licenses, digital rights management and geofencing. Unfortunately, GNSS is vulnerable to malicious intrusion and spoofing. How can users be sure the information they receive is authentic? This article introduces a new method that uses hidden attributes fundamental to the GPS satellite broadcast — and cross-compared between two receivers — to authenticate signals and the location solutions they generate.
Brad Parkinson, first director of the GPS Joint Program Office, once remarked that the NAVSTAR Global Positioning System represents, next to the Internet, perhaps the most successful civilian adoption of military-developed, dual-use technology.
Today, hundreds of millions of people worldwide rely on satellite navigation to deliver accurate position and time information to a host of critical services, including everything from guiding aircraft at night and during inclement weather to synchronization of cellular communication networks. Other applications range from helping emergency dispatchers direct rescue personnel to giving route instructions to touring motorists.
As these and other GNSS-enabled applications become increasingly woven into the fabric of our global 21st-century economic and social infrastructure, the consequences of breach-of-service become greater as well. In this context, service breach encompasses not only system outages (e.g., constellation failures, inadvertent or deliberate interference, and so forth) but also failures of trust in the basic integrity of the position and time broadcast.
Moreover, experience with the Internet shows that as a resource becomes more valuable to our civil infrastructure, criminal or malicious agents will seek to discover and exploit weaknesses in order to disrupt legitimate users or to perpetrate fraud.
Navigation system security is ever more important for two reasons. The first reason is to ensure that the position, navigation, and time (PNT) information upon which we increasingly rely are indeed trustworthy. The second is that secure PNT can serve as a building block for protection of critical data and assets in the global fight against information technology attack. We refer to these features as “security for navigation” and “security from navigation.”
Ideally, security would be a built-in feature of civilian GNSS. Unfortunately, as with the Internet, this was not an initial design consideration for civil use of GPS. The European Galileo system, which will employ such features possibly as a fee-based service, still is a number of years from operational capability.
Recently, proposals have been made to incorporate security and authentication signatures directly into the civil GPS signal. However, GPS probably will not incorporate these features, due both to institutional priorities and to long procurement and deployment cycles.
Thus, the GNSS community must work within the existing system to develop civilian navigation security features. In this article, we will present a new technique that can provide such capabilities today for civilian GNSS.
The GNSS Security Threat
Due to the low received power of GNSS signals, the most common attack currently contemplated is denial-of-service by jamming or intentional interference. Of greater concern in the future will be spoofing, where a signal is transmitted so that a GNSS receiver computes an incorrect position. Spoofing represents a more pernicious attack than denial-of-service, because it attempts to misrepresent the user’s true location while at the same time avoiding detection of the attack itself.
Concerns about GNSS authenticity are particularly relevant today. For example, several over-the-air spoofing incidents already have been reported. A number of such incidents are mentioned in the article by B. Forssell cited in the Additional Resources section.
Additionally, a U.S. research team has developed and described a portable GPS civilian spoofer capable of several different attack mechanisms (See the article by T. Humphreys et alia in Additional Resources.). This “cookbook on GPS spoofing” expands the attacker threat space to include not only sophisticated foreign powers but also rogue organizations and even moderately skilled domestic groups or individuals.
These developments not only demonstrate intent but also illustrate the ever-increasing attack sophistication. Hacking the satellite-to-receiver signal interface opens GNSS to the same types of attacks that daily plague personal computers, corporate mainframe systems, and the Internet.
An additional attack vector occurs when a supplicant party submits its position to a permission-granting agent. Without an authentication token generated as part of the position computation process, no mechanism exists whereby a party can assure that a position assertion is bone fide.
Consequently, the navigation security threat space raises these dual concerns for a user: (1) when processing signals that I receive myself, how do I ensure their authenticity? and (2) when receiving an assertion from another party about the signals that they receive, how do I ensure the validity of their assertion?
Current methods of protecting GPS users against system faults or intentional attacks rely on cross-checks against metrics either internal or external to the GNSS subsystem, or on tests of predictable characteristics of the navigation signal. Of course, as the robustness of the defensive countermeasures increases, system complexity and cost go up as well — which can be a barrier in applications where the GNSS hardware bill-of-materials is expected to remain below $1!
And not all countermeasures are secure against every possible attack. For example, even sophisticated direction-of-arrival anti-spoofing methods described in the literature — for example, the article by P. Y. Montgomery et alia in Additional Resources — do not protect the integrity of location assertions made by one party to another.
With these concerns in mind, we have developed and tested a signal authentication technology that relies not on the predictable characteristics of the GPS signal, but rather makes use of hidden attributes that are fundamental to the satellite broadcast and that can be cross-compared between receivers to ensure the validity of the signals that are received and the location solutions that those signals generate.
Anti-Spoofing for Civil GNSS
These signals produce asymmetry, meaning that the service provider has the encryption or generation mechanism while an attacker does not. Consequently, an attacker will not be able to generate the authentic encrypted signal for use in a spoofing broadcast or injection attack. Of course, civil users do not have access to the P(Y), M-code, or PRS, and even authorized military GPS users require Selective Availability/anti-spoofing module (SAASM) hardware, which is both expensive and access-restricted.
Our research has created a method to provide the anti-spoofing benefits of secret codes, without needing access to the codes themselves. This capability is achieved by joint processing of the signal received at one location with a nearly synchronous signal received at a remote (preferably trusted) station; the theory of this joint processing is described in the next section.
A central tenet of this method is that the better the secret codes are protected by the corresponding operating authority, such as the U.S. Department of Defense (for the P(Y) and M-code) or the Galileo operating agency (for the PRS), the better the security of this authentication system. (Security can be expressed in terms of an equivalent cryptographic strength, the brute-force attack time, and so forth.)
The following section and the remainder of the article will use the GPS L1/P(Y) code as the secret code being operated upon. While L1/P(Y) is used as an illustrative example, the technique can be applied to other navigation and communication signals as well.
Processing of Secret Signals for Authentication – Theory
The L1 frequency carries both C/A-code and P(Y)-code signals, transmitted in phase quadrature. Hence, on L1 a GPS receiver has available to it a signal sL1(t) that is composed of the received RF energy si(t) from each of N satellites in the visible constellation, plus thermal noise η(t):
Note that the received signals are well below the thermal noise floor and only detectable after correlation processing with a receiver-generated replica or observation via high-gain steerable antennas.
We now focus on the data and code components of the L1 signal from a specific satellite i while dropping the L1 subscript; at receiver #1 this signal is s1i(t):
Here, subscripts C and P denote C/A-code and P(Y)-code respectively, A and B are scaling parameters for the received signal power, D is the navigation data bit sequence (possibly different for C/A and P(Y)), xC and xP are the C/A-code and P(Y)-code sequences, τC and τP are the phases of the respective generating functions, fD is the satellite-to-receiver Doppler frequency (it may also include a frequency offset between the satellite oscillator and that of the receiver), and θ is the phase of the received RF carrier with respect to the local reference oscillator.
The receiver performs a series of functions on the received signal in space: amplification, mixing and frequency down-conversion, low-pass filtering, and Doppler frequency and carrier-phase estimation to yield a baseband signal suitable for processing, as follows:
Here, the superscript i has been dropped for clarity and the superscript caret ‘^’ indicates estimation. Processing for C/A-code detection and tracking involves multiplication by a replica C/A-code sequence xC(t - τ^C,1). Since xC is orthogonal to xP (meaning their cross-correlation product is nearly zero for all τC and τP), accumulation (noise-averaging) for an integration interval TC yields in-phase and quadrature terms:
Signal tracking seeks to maximize SI and to minimize SQ by driving to zero the differences between the received and estimated values of code-phase, Doppler frequency, and carrier-phase. Figure 1 shows this process for code-phase alignment. A receiver with access to the encrypted P(Y)-code sequence can process that signal component in an analogous manner. (In addition, some codeless and semi-codeless techniques exploit the fact that identical P(Y)-code sequences are broadcast on the L1 and L2 frequencies.)
The foregoing procedure is common, with small variations, to almost all commercial GNSS receivers. The innovation we are introducing is the joint processing of signals received at two separate locations to access the secret code sequence for authentication. This authentication process recognizes and exploits the fact that the P(Y)-code sequence received at a location #1, xP(t – τP,1), is identical to the sequence received at a location #2, xP(t + Δt – τP,2), except for the differential satellite-to-receiver signal travel time Δt.
At this point, accumulation of the product of the Eq. (4) quadrature signals from two receivers (and remembering that xC is orthogonal to xP, and that with Doppler frequency and carrier-phase alignment the ‘sin’ terms go to zero and the ‘cos’ terms go to one) yields:
Observation of a correlation peak, as shown in Figure 2, indicates the presence of component sP(Y)(t) in both receiver #1 and receiver #2 signals, and is accomplished by sliding the correlation window until Δt = τP,2 – τP,1. A peak in the function SQ,1:2 establishes signal authenticity (with the trivial caveat that receiver #1 and receiver #2 not be within reception range of the same signal-spoofing attacker).
The value of Δt accounts both for receiver clock offset and for different satellite-to-receiver signal travel times. Consequently, if Δt should be measured on several satellites, then the presence of the correlation peaks serves not only to confirm the authenticity of each receiver’s signal observation but also to locate receiver #1 with respect to receiver #2 in a manner analogous to GPS carrier-phase differential positioning.
The strength of the correlation peak depends on many factors such as correlation time duration and the signal-to-noise ratio (SNR) of the measurements. For example, the correlation results will be more evident if the reference station uses a high-gain dish or steered-beam array antenna rather than an omnidirectional patch antenna.
The difference between this joint processing method and having the actual P(Y)-code sequence (which is like having a noiseless measurement) is shown in Equation 6, assuming noise power is σ2/2, the receiver #1 signal has amplitude B1, and the receiver #2 “reference signal” has amplitude B2 = αB1 (with the same noise); N represents the averaging time. Note that as the gain of the reference station antenna increases, the ratio approaches 1 as expected.
An Authentication Architecture
A system implementing one possible variant of this authentication architecture is illustrated in Figure 3. In this example, the reference station continuously collects and stores GPS raw data (or it could do so on a published schedule); these archived data are used in the authentication joint processing operation. The steps required for joint processing can be described as follows:
1. Record GPS raw data at location #1 (i.e., the user device) and location #2 (i.e., the reference station).
For each satellite of interest in a data set pair (user device and reference station):
3. Perform Doppler frequency wipe-off.
The first two steps relate to signal collection and distribution. Note that the signal bandwidth must be sufficient to recover energy from the embedded secret code; for the P(Y)-code, a bandwidth of at least 10-20 megahertz is desirable. Signal processing occurs in the last three steps.
The simplest method of estimating Doppler frequency and carrier-phase, of course, is to acquire and track the C/A-code; this operation is simple for the reference station to perform but could be prohibitive at the user device (due to processor complexity or battery life concerns, for example). If the data snapshot is not sufficiently long for tracking, then a Doppler frequency estimate can come either from signal acquisition or from the satellite ephemeris.
Signal Authentication with Live Satellite Broadcasts
Raw RF data were collected at each site with an RF signal analyzer in a 20 megahertz band about the GPS L1 center frequency using a hemispherical patch antenna (both sites) and a 1.8-meter high-gain steerable dish antenna (Palo Alto only). The dish antenna provides approximately 25 decibels of gain over that of a standard patch. Coarse time synchronization was achieved through cellular communication links, which yielded ~0.25 seconds of timing error.
In analyzing the results of this test, we first sought to validate the basic signal-authentication concept. The correlation between measurements taken with the patch antennas at the two locations was examined. Figure 4 shows the in-phase (C/A-code) and quadrature (P(Y)-code) correlation with a 100-millisecond observation window, two-bit I/Q data samples, and precise Doppler frequency and carrier-phase alignment (from signal tracking with a GPS software receiver). The repeating peaks in the C/A-code receiver-to-receiver correlation output are an artifact of the one-millisecond C/A-code repeat interval, modulated by the 50-hertz navigation data message.
Another important goal of our analysis seeks to minimize the required memory size of the data snapshot stored at one receiver. This is important in memory- or bandwidth-constrained authentication applications such as integrated circuits, smart cards, or near-real-time challenge-response scenarios.
Using the 1.8-meter high-gain steerable dish antenna for one receiver (i.e., the reference station), one-bit I/Q samples at the other receiver (i.e., the user device), and a one-millisecond correlation window allows recovery of a prominent correlation peak with no more than 4,800 bits of data, as shown in Figure 5. Reducing the signal bandwidth to a 15-megahertz sampling frequency could push the data storage requirements below 3,000 bits.
Requirements & Benefits
A reference station network (and the associated authentication servers) is needed to provide the authentication function. We should note that the required number of reference stations is quite modest, because a single reference station can serve a sizable area. For example, the continental U.S. could be covered by two or three such stations with significant redundancy, as the reference station network requirement simply is to observe every satellite that may be seen by any user in the service coverage area. (Peer-to-peer authentication is a slight modification of the above-described architecture and does away with the reference station network entirely.)
The most basic user device, essentially a data capture engine, can make do with less functionality than a typical GNSS receiver, because the entire authentication processing typically is done remotely. Stripping away correlation, tracking, and navigation units leaves only a wide-band front-end, simple analog-to-digital converter (1-1½ bit), storage, and input/output subsystems. Furthermore, remote processing drastically reduces power consumption, which still can be a major concern for GNSS receiver integrators.
Real-time or near real-time receivers also require a secure communications link. With the proliferation of data communication technologies such as Wi-Fi, Wi-Max, and numerous high-speed cellular communication standards, this requirement is not a major constraint in most of the developed world. Additionally, the hardware needed for these links increasingly is being integrated with GPS in mobile telephony.
In contrast, some applications may find a real-time communications link unnecessary. For example, a receiver designed for route auditing or cargo transit assurance needs only to store GPS snapshots in tamperproof memory, with verification done at intermediate or final destination.
With these required elements, the authentication architecture essentially transfers the security, and possibly the navigation, functionality from the user device to the trusted authentication processor. This reduces costs by moving the main security vulnerability from the distributed users to a few hardened locations.
The sites containing the authentication processor and the GNSS reception equipment can be hardened with features such as physical security barriers, high-gain directional antennas, or steered-beam antenna arrays. The benefit to this centralization is that high-cost security features only are needed in a few locations, with the resulting cost amortized across many users.
The end result is an architecture that can support many PNT security applications at very reasonable cost. These include not only current high-value applications such as asset tracking and fleet management, but also emerging geo-security location-based services such as hardware configuration and management, virtual site licenses, digital rights management and manners policies, and geo-fencing. Moreover, new applications can be supported, such as the following example of secure location signatures for integrated circuit (IC) assurance.
Location Security for IC Assurance
Secure GNSS offers a novel and cost-effective solution to address integrated circuit and supply chain assurance by implanting one or more unique time- and location-based signatures within the IC at the times of fabrication, board level manufacturing, and system assembly. Figure 6 shows one means of using GNSS authentication signatures for IC verification as part of a multi-factor integrated suite of defensive technologies.
However, the IC logic and silicon gate-count devoted to the assurance functionality are severely constrained, as resources allocated to security or validation circuits directly compete with the primary processing features of the die. For example, the on-die and at-speed IP of DAFCA’s reconfigurable security product suite have been optimized to minimize the footprint in the final silicon device.
For this reason, it is likely that GNSS location and time signatures, and the logic resources required to securely store them in memory, comprise an IC assurance technology that may be most suited to high-value mission-critical devices such as systems on chip (SoCs), central processing units (CPUs), integrated memory controllers, specialized digital signal processors (DSPs), and other system or I/O control chips.
We estimate that the storage requirements of a 400-kByte GNSS signature, along with the associated encryption and tamperproofing circuits, and using existing die-to-system communication channels, becomes feasible for devices containing approximately one million transistors.
Of course, one benefit of combining the circuit validation and IC manufacturing assurance capabilities at the same phase of the design cycle is architectural simplification of shared communication across standardized test access ports. In this way, a system integrator (for example) could validate the functional integrity, manufacturing provenance, and transport chain-of-custody through a common test interface.
Figure 7 illustrates an example process wherein the GNSS security protocol provides an attack-resistant verification of the manufacturing and transport stages within the IC supply chain by requiring that each successive step be dependent on successful authentication during the previous step.
The scheme in Figure 7 can further be extended into a feature activation scheme that integrates the location and time signatures with hardware-based activation logic and software verification. With the addition of tamper-resistant hardware and software, along with hardware countermeasures, a robust security system can be created that extends from logic design and device fabrication, through the supply channel, and into system deployment.
In this article, we have described a signal-authentication system architecture for single-frequency civil-use GNSS devices that delivers a verifiable position report or confirms a position assertion by a remote agent. We have validated this authentication architecture through live signal tests with hardware in the loop, and have described the implementation of GNSS security signatures for integrated circuit and supply chain assurance.
As the satellite navigation attack threat space and sophistication continue to grow, this and other defensive technologies will become increasingly important to the high-integrity application of GNSS, as illustrated in Figure 8. With this effort, we will realize security for GNSS and security from GNSS.
Disclosure: The first three authors are members of the Stanford University GPS Laboratory and have formed the start-up company Zanio to pursue development of GNSS security and authentication technology.
ManufacturersStanford University and Colorado researchers use an 89600 vector signal analyzer (VSA) from Agilent Technologies, Santa Clara California, USA, to collect signals received either from high-gain steerable dish or hemispherical-gain patch antennas. The 1.8-meter dish is part of the Stanford GNSS Monitor Station; the patch antennas are NovAtel GPS Pinwheel Model 702 from NovAtel, Inc., Calgary Alberta, Canada. The software GNSS receiver and the specialized signal authentication codebase are implemented in MATLAB from the MathWorks, Inc., Natick Massachusetts, USA.
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