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1. Performance Analysis of a Mission-Critical Portable LTE System in Targeted RF Interference

   Marojevic, Vuk ; Rao, Raghunandan ( September 2017 , IEEE Vehicular Technology Conference (VTC) Fall, 2017)

   Mission-critical wireless networks are being upgraded to 4G long-term evolution (LTE). As opposed to capacity, these networks require very high reliability and security as well as easy deployment and operation in the field. Wireless communication systems have been vulnerable to jamming, spoofing and other radio frequency attacks since the early days of analog systems. Although wireless systems have evolved, important security and reliability concerns still exist. This paper presents our methodology and results for testing 4G LTE operating in harsh signaling environments. We use software-defined radio technology and open-source software to develop a fully configurable protocol-aware interference waveform. We define several test cases that target the entire LTE signal or part of it to evaluate the performance of a mission-critical production LTE system. Our experimental results show that synchronization signal interference in LTE causes significant throughput degradation at low interference power. By dynamically evaluating the performance measurement counters, the k-nearest neighbor classification method can detect the specific RF signaling attack to aid in effective mitigation.
2. Security of GPS/INS Based On-road Location Tracking Systems

   https://doi.org/10.1109/SP.2019.00068  

   Narain, Sashank ; Ranganathan, Aanjhan ; Noubir, Guevara ( May 2019 , 2019 IEEE Symposium on Security and Privacy (SP))

   Location information is critical to a wide variety of navigation and tracking applications. GPS, today's de-facto outdoor localization system has been shown to be vulnerable to signal spoofing attacks. Inertial Navigation Systems (INS) are emerging as a popular complementary system, especially in road transportation systems as they enable improved navigation and tracking as well as offer resilience to wireless signals spoofing and jamming attacks. In this paper, we evaluate the security guarantees of INS-aided GPS tracking and navigation for road transportation systems. We consider an adversary required to travel from a source location to a destination and monitored by an INS-aided GPS system. The goal of the adversary is to travel to alternate locations without being detected. We develop and evaluate algorithms that achieve this goal, providing the adversary significant latitude. Our algorithms build a graph model for a given road network and enable us to derive potential destinations an attacker can reach without raising alarms even with the INS-aided GPS tracking and navigation system. The algorithms render the gyroscope and accelerometer sensors useless as they generate road trajectories indistinguishable from plausible paths (both in terms of turn angles and roads curvature). We also design, build and demonstrate that themore »magnetometer can be actively spoofed using a combination of carefully controlled coils. To experimentally demonstrate and evaluate the feasibility of the attack in real-world, we implement a first real-time integrated GPS/INS spoofer that accounts for traffic fluidity, congestion, lights, and dynamically generates corresponding spoofing signals. Furthermore, we evaluate our attack on ten different cities using driving traces and publicly available city plans. Our evaluations show that it is possible for an attacker to reach destinations that are as far as 30 km away from the actual destination without being detected. We also show that it is possible for the adversary to reach almost 60--80% of possible points within the target region in some cities. Such results are only a lower-bound, as an adversary can adjust our parameters to spend more resources (e.g., time) on the target source/destination than we did for our performance evaluations of thousands of paths. We propose countermeasures that limit an attacker's ability, without the need for any hardware modifications. Our system can be used as the foundation for countering such attacks, both detecting and recommending paths that are difficult to spoof.« less
3. Evaluating Resilience of Grid Load Predictions under Stealthy Adversarial Attacks

   https://doi.org/10.1109/RWS47064.2019.8971816  

   Zhou, Xingyu ; Li, Yi ; Barreto, Carlos A. ; Li, Jiani ; Volgyesi, Peter ; Neema, Himanshu ; Koutsoukos, Xenofon ( November 2019 , 2019 Resilience Week (RWS))

   Recent advances in machine learning enable wider applications of prediction models in cyber-physical systems. Smart grids are increasingly using distributed sensor settings for distributed sensor fusion and information processing. Load forecasting systems use these sensors to predict future loads to incorporate into dynamic pricing of power and grid maintenance. However, these inference predictors are highly complex and thus vulnerable to adversarial attacks. Moreover, the adversarial attacks are synthetic norm-bounded modifications to a limited number of sensors that can greatly affect the accuracy of the overall predictor. It can be much cheaper and effective to incorporate elements of security and resilience at the earliest stages of design. In this paper, we demonstrate how to analyze the security and resilience of learning-based prediction models in power distribution networks by utilizing a domain-specific deep-learning and testing framework. This framework is developed using DeepForge and enables rapid design and analysis of attack scenarios against distributed smart meters in a power distribution network. It runs the attack simulations in the cloud backend. In addition to the predictor model, we have integrated an anomaly detector to detect adversarial attacks targeting the predictor. We formulate the stealthy adversarial attacks as an optimization problem to maximize prediction lossmore »while minimizing the required perturbations. Under the worst-case setting, where the attacker has full knowledge of both the predictor and the detector, an iterative attack method has been developed to solve for the adversarial perturbation. We demonstrate the framework capabilities using a GridLAB-D based power distribution network model and show how stealthy adversarial attacks can affect smart grid prediction systems even with a partial control of network.« less
4. A Machine Learning Approach for Detecting and Classifying Jamming Attacks Against OFDM-based UAVs

   https://doi.org/10.1145/3468218.3469049  

   Pawlak, Jered ; Li, Yuchen ; Price, Joshua ; Wright, Matthew ; Al Shamaileh, Khair ; Niyaz, Quamar ; Devabhaktuni, Vijay ( June 2021 , Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning)

   In this paper, a machine learning (ML) approach is proposed to detect and classify jamming attacks on unmanned aerial vehicles (UAVs). Four attack types are implemented using software-defined radio (SDR); namely, barrage, single-tone, successive-pulse, and protocol-aware jamming. Each type is launched against a drone that uses orthogonal frequency division multiplexing (OFDM) communication to qualitatively analyze its impacts considering jamming range, complexity, and severity. Then, an SDR is utilized in proximity to the drone and in systematic testing scenarios to record the radiometric parameters before and after each attack is launched. Signal-to-noise ratio (SNR), energy threshold, and several OFDM parameters are exploited as features and fed to six ML algorithms to explore and enable autonomous jamming detection/classification. The algorithms are quantitatively evaluated with metrics including detection and false alarm rates to evaluate the received signals and facilitate efficient decision-making for improved reception integrity and reliability. The resulting ML approach detects and classifies jamming with an accuracy of 92.2% and a false-alarm rate of 1.35%.
5. Work in Progress: Interactive Introductory Online Modules on Wireless Communications and Radio-frequency Spectrum Sharing

   Dietrich, C. B. ; Polys, N. F. ; Reid, K. ; García Sheridan, J. A. ; Emenonye, D. ; Gomez, X. ; Tolley, J. ; Makin, C. ; Gaeddert, J. ( July 2021 , ASEE Annual Conference proceedings)

   1. Description of the objectives and motivation for the contribution to ECE education The demand for wireless data transmission capacity is increasing rapidly and this growth is expected to continue due to ongoing prevalence of cellular phones and new and emerging bandwidth-intensive applications that encompass high-definition video, unmanned aerial systems (UAS), intelligent transportation systems (ITS) including autonomous vehicles, and others. Meanwhile, vital military and public safety applications also depend on access to the radio frequency spectrum. To meet these demands, the US federal government is beginning to move from the proven but inefficient model of exclusive frequency assignments to a more-efficient, shared-spectrum approach in some bands of the radio frequency spectrum. A STEM workforce that understands the radio frequency spectrum and applications that use the spectrum is needed to further increase spectrum efficiency and cost-effectiveness of wireless systems over the next several decades to meet anticipated and unanticipated increases in wireless data capacity. 2. Relevant background including literature search examples if appropriate CISCO Systems’ annual survey indicates continued strong growth in demand for wireless data capacity. Meanwhile, undergraduate electrical and computer engineering courses in communication systems, electromagnetics, and networks tend to emphasize mathematical and theoretical fundamentals and higher-layer protocols, withmore »less focus on fundamental concepts that are more specific to radio frequency wireless systems, including the physical and media access control layers of wireless communication systems and networks. An efficient way is needed to introduce basic RF system and spectrum concepts to undergraduate engineering students in courses such as those mentioned above who are unable to, or had not planned to take a full course in radio frequency / microwave engineering or wireless systems and networks. We have developed a series of interactive online modules that introduce concepts fundamental to wireless communications, the radio frequency spectrum, and spectrum sharing, and seek to present these concepts in context. The modules include interactive, JavaScript-based simulation exercises intended to reinforce the concepts that are presented in the modules through narrated slide presentations, text, and external links. Additional modules in development will introduce advanced undergraduate and graduate students and STEM professionals to configuration and programming of adaptive frequency-agile radios and spectrum management systems that can operate efficiently in congested radio frequency environments. Simulation exercises developed for the advanced modules allow both manual and automatic control of simulated radio links in timed, game-like simulations, and some exercises will enable students to select from among multiple pre-coded controller strategies and optionally edit the code before running the timed simulation. Additionally, we have developed infrastructure for running remote laboratory experiments that can also be embedded within the online modules, including a web-based user interface, an experiment management framework, and software defined radio (SDR) application software that runs in a wireless testbed initially developed for research. Although these experiments rely on limited hardware resources and introduce additional logistical considerations, they provide additional realism that may further challenge and motivate students. 3. Description of any assessment methods used to evaluate the effectiveness of the contribution, Each set of modules is preceded and followed by a survey. Each individual module is preceded by a quiz and followed by another quiz, with pre- and post-quiz questions drawn from the same pool. The pre-surveys allow students to opt in or out of having their survey and quiz results used anonymously in research. 4. Statement of results. The initial modules have been and are being used by three groups of students: (1) students in an undergraduate Introduction to Communication Systems course; (2) an interdisciplinary group of engineering students, including computer science students, who are participating in related undergraduate research project; and (3) students in a graduate-level communications course that includes both electrical and computer engineers. Analysis of results from the first group of students showed statistically significant increases from pre-quiz to post-quiz for each of four modules on fundamental wireless communication concepts. Results for the other students have not yet been analyzed, but also appear to show substantial pre-quiz to post-quiz increases in mean scores.« less