Biblio

We show that elliptic-curve cryptography implementations on mobile devices are vulnerable to electromagnetic and power side-channel attacks. We demonstrate full extraction of ECDSA secret signing keys from OpenSSL and CoreBitcoin running on iOS devices, and partial key leakage from OpenSSL running on Android and from iOS's CommonCrypto. These non-intrusive attacks use a simple magnetic probe placed in proximity to the device, or a power probe on the phone's USB cable. They use a bandwidth of merely a few hundred kHz, and can be performed cheaply using an audio card and an improvised magnetic probe.

As cyber-physical systems (CPS) become prevalent in everyday life, it is critical to understand the factors that may impact the security of such systems. In this paper, we present insights from an initial study of historical security incidents to analyse such factors for a particular class of CPS: industrial control systems (ICS). Our study challenges the usual tendency to blame human fallibility or resort to simple explanations for what are often complex issues that lead to a security incident. We highlight that (i) perception errors are key in such incidents (ii) latent design conditions – e.g., improper specifications of a system's borders and capabilities – play a fundamental role in shaping perceptions, leading to security issues. Such design-time considerations are particularly critical for ICS, the life-cycle of which is usually measured in decades. Based on this analysis, we discuss how key characteristics of future smart CPS in such industrial settings can pose further challenges with regards to tackling latent design flaws.

With cyber-physical systems opening to the outside world, security can no longer be considered a secondary issue. One of the key aspects in security of cyber-phyiscal systems is to deal with intrusions. In this paper, we highlight the several unique properties of control applications in cyber-physical systems. Using these unique properties, we propose a systematic intrusion-damage assessment and mitigation mechanism for the class of observable and controllable attacks. On the one hand, in cyber-physical systems, the plants follow certain laws of physics and this can be utilized to address the intrusion-damage assessment problem. That is, the states of the controlled plant should follow those expected according to the physics of the system and any major discrepancy is potentially an indication of intrusion. Here, we use a machine learning algorithm to capture the normal behavior of the system according to its dynamics. On the other hand, the control performance strongly depends on the amount of allocated resources and this can be used to address the intrusion-damage mitigation problem. That is, the intrusion-damage mitigation is based on the idea of allocating more resources to the control application under attack. This is done using a feedback-based approach including a convex optimization.

Embedded Systems (ES) are an integral part of Cyber-Physical Systems (CPS), the Internet of Things (IoT), and consumer devices like smartphones. ES often have limited resources, and - if used in CPS and IoT - have to satisfy real time requirements. Therefore, ES rarely employ the security measures established for computer systems and networks. Due to the growth of both CPS and IoT it is important to identify ongoing attacks on ES without interfering with realtime constraints. Furthermore, security solutions that can be retrofit to legacy systems are desirable, especially when ES are used in Industrial Control Systems (ICS) that often maintain the same hardware for decades. To tackle this problem, several researchers have proposed using side-channels (i.e., physical emanations accompanying cyber processes) to detect such attacks. While prior work focuses on the anomaly detection approach, this might not always be sufficient, especially in complex ES whose behavior depends on the input data. In this paper, we determine whether one of the most common attacks - a buffer overflow attack - generates distinct side-channel signatures if executed on a vulnerable ES. We only consider the power consumption side-channel. We collect and analyze power traces from normal program operation and four cases of buffer overflow attack categories: (i) crash program execution, (ii) injection of executable code, (iii) return to existing function, and (iv) Return Oriented Programming (ROP) with gadgets. Our analysis shows that for some of these cases a power signature-based detection of a buffer overflow attack is possible.

Additive Manufacturing (AM) uses Cyber-Physical Systems (CPS) (e.g., 3D Printers) that are vulnerable to kinetic cyber-attacks. Kinetic cyber-attacks cause physical damage to the system from the cyber domain. In AM, kinetic cyber-attacks are realized by introducing flaws in the design of the 3D objects. These flaws may eventually compromise the structural integrity of the printed objects. In CPS, researchers have designed various attack detection method to detect the attacks on the integrity of the system. However, in AM, attack detection method is in its infancy. Moreover, analog emissions (such as acoustics, electromagnetic emissions, etc.) from the side-channels of AM have not been fully considered as a parameter for attack detection. To aid the security research in AM, this paper presents a novel attack detection method that is able to detect zero-day kinetic cyber-attacks on AM by identifying anomalous analog emissions which arise as an outcome of the attack. This is achieved by statistically estimating functions that map the relation between the analog emissions and the corresponding cyber domain data (such as G-code) to model the behavior of the system. Our method has been tested to detect potential zero-day kinetic cyber-attacks in fused deposition modeling based AM. These attacks can physically manifest to change various parameters of the 3D object, such as speed, dimension, and movement axis. Accuracy, defined as the capability of our method to detect the range of variations introduced to these parameters as a result of kinetic cyber-attacks, is 77.45%.

The security of critical infrastructures such as oil and gas cyber-physical systems is a significant concern in today's world where malicious activities are frequent like never before. On one side we have cyber criminals who compromise cyber infrastructure to control physical processes; we also have physical criminals who attack the physical infrastructure motivated to destroy the target or to steal oil from pipelines. Unfortunately, due to limited resources and physical dispersion, it is impossible for the system administrator to protect each target all the time. In this research paper, we tackle the problem of cyber and physical attacks on oil pipeline infrastructure by proposing a Stackelberg Security Game of three players: system administrator as a leader, cyber and physical attackers as followers. The novelty of this paper is that we have formulated a real world problem of oil stealing using a game theoretic approach. The game has two different types of targets attacked by two distinct types of adversaries with different motives and who can coordinate to maximize their rewards. The solution to this game assists the system administrator of the oil pipeline cyber-physical system to allocate the cyber security controls for the cyber targets and to assign patrol teams to the pipeline regions efficiently. This paper provides a theoretical framework for formulating and solving the above problem.

Multilateration techniques have been proposed to verify the integrity of unprotected location claims in wireless localization systems. A common assumption is that the adversary is equipped with only a single device from which it transmits location spoofing signals. In this paper, we consider a more advanced model where the attacker is equipped with multiple devices and performs a geographically distributed coordinated attack on the multilateration system. The feasibility of a distributed multi-device attack is demonstrated experimentally with a self-developed attack implementation based on multiple COTS software-defined radio (SDR) devices. We launch an attack against the OpenSky Network, an air traffic surveillance system that implements a time-difference-of-arrival (TDoA) multi-lateration method for aircraft localization based on ADS-B signals. Our experiments show that the timing errors for distributed spoofed signals are indistinguishable from the multilateration errors of legitimate aircraft signals, indicating that the threat of multi-device spoofing attacks is real in this and other similar systems. In the second part of this work, we investigate physical-layer features that could be used to detect multi-device attacks. We show that the frequency offset and transient phase noise of the attacker's radio devices can be exploited to discriminate between a received signal that has been transmitted by a single (legitimate) transponder or by multiple (malicious) spoofing sources. Based on that, we devise a multi-device spoofing detection system that achieves zero false positives and a false negative rate below 1%.

Securing visible light communication (VLC) systems on the physical layer promises to prevent against a variety of attacks. Recent work shows that the adaption of existing legacy radio wave physical layer security (PLS) mechanisms is possible with minor changes. Yet, many adaptations open new vulnerabilities due to distinct propagation characteristics of visible light. A common understanding of threats arising from various attacker capabilities is missing. We specify a new attacker model for visible light physical layer attacks and evaluate the applicability of existing PLS approaches. Our results show that many attacks are not considered in current solutions.

In this work, we constructively combine adaptive wormholes with channel-reciprocity based key establishment (CRKE), which has been proposed as a lightweight security solution for IoT devices and might be even more important for the 5G Tactile Internet and its embedded low-end devices. We present a new secret key generation protocol where two parties compute shared cryptographic keys under narrow-band multi-path fading models over a delayed digital channel. The proposed approach furthermore enables distance-bounding the key establishment process via the coherence time dependencies of the wireless channel. Our scheme is thoroughly evaluated both theoretically and practically. For the latter, we used a testbed based on the IEEE 802.15.4 standard and performed extensive experiments in a real-world manufacturing environment. Additionally, we demonstrate adaptive wormhole attacks (AWOAs) and their consequences on several physical-layer security schemes. Furthermore, we proposed a countermeasure that minimizes the risk of AWOAs.

Physical layer security for wireless communication is broadly considered as a promising approach to protect data confidentiality against eavesdroppers. However, despite its ample theoretical foundation, the transition to practical implementations of physical-layer security still lacks success. A close inspection of proven vulnerable physical-layer security designs reveals that the flaws are usually overlooked when the scheme is only evaluated against an inferior, single-antenna eavesdropper. Meanwhile, the attacks exposing vulnerabilities often lack theoretical justification. To reduce the gap between theory and practice, we posit that a physical-layer security scheme must be studied under multiple adversarial models to fully grasp its security strength. In this regard, we evaluate a specific physical-layer security scheme, i.e. orthogonal blinding, under multiple eavesdropper settings. We further propose a practical "ciphertext-only attack" that allows eavesdroppers to recover the original message by exploiting the low entropy fields in wireless packets. By means of simulation, we are able to reduce the symbol error rate at an eavesdropper below 1% using only the eavesdropper's receiving data and a general knowledge about the format of the wireless packets.

Recently, there has been great interest in the physical layer security technique which exploits the artificial noise (AN) to enlarge the channel condition between the legitimate receiver and the eavesdropper. However, in certain communication scenery, this strategy may suffer from some attacks in the signal processing perspective. In this paper, we consider speech signals and the scenario in which the eavesdropper has the similar channel performance compared to the legitimate receiver. We design the optimal artificial noise (AN) to resist the attack of the eavesdropper who uses the blind source separation (BSS) technology to reconstruct the secret information. The Optimal AN is obtained by making a tradeoff between results of direct eavesdropping and reconstruction. The simulation results show that the AN we proposed has better performance than that of the white Gaussian AN to resist the BSS attacks effectively.
 

Discrete fractional Fourier transform (DFRFT) is a generalization of discrete Fourier transform. There are a number of DFRFT proposals, which are useful for various signal processing applications. This paper investigates practical solutions toward the construction of unconditionally secure communication systems based on DFRFT via cross-layer approach. By introducing a distort signal parameter, the sender randomly flip-flops between the distort signal parameter and the general signal parameter to confuse the attacker. The advantages of the legitimate partners are guaranteed. We extend the advantages between legitimate partners via developing novel security codes on top of the proposed cross-layer DFRFT security communication model, aiming to achieve an error-free legitimate channel while preventing the eavesdropper from any useful information. Thus, a cross-layer strong mobile communication secure model is built.
 

Security is a major challenge preventing wide deployment of the smart grid technology. Typically, the classical power grid is protected with a set of isolated security tools applied to individual grid components and layers ignoring their cross-layer interaction. Such an approach does not address the smart grid security requirements because usually intricate attacks are cross-layer exploiting multiple vulnerabilities at various grid layers and domains. We advance a conceptual layering model of the smart grid and a high-level overview of a security framework, termed CyNetPhy, towards enabling cross-layer security of the smart grid. CyNetPhy tightly integrates and coordinates between three interrelated, and highly cooperative real-time security systems crossing section various layers of the grid cyber and physical domains to simultaneously address the grid's operational and security requirements. In this article, we present in detail the physical security layer (PSL) in CyNetPhy. We describe an attack scenario raising the emerging hardware Trojan threat in process control systems (PCSes) and its novel PSL resolution leveraging the model predictive control principles. Initial simulation results illustrate the feasibility and effectiveness of the PSL.
 

It is widely accepted that wireless channels decorrelate fast over space, and half a wavelength is the key distance metric used in link signature (LS) for security assurance. However, we believe that this channel correlation model is questionable, and will lead to false sense of security. In this project, we focus on establishing correct modeling of channel correlation so as to facilitate proper guard zone designs for LS security in various wireless environments of interest.