Biblio

There is a need for new tools and techniques to aid automotive engineers performing cybersecurity testing on connected car systems. This is in order to support the principle of secure-by-design. Our research has produced a method to construct useful automotive security tooling and tests. It has been used to implement Controller Area Network (CAN) fuzz testing (a dynamic security test) via a prototype CAN fuzzer. The black-box fuzz testing of a laboratory vehicle's display ECU demonstrates the value of a fuzzer in the automotive field, revealing bugs in the ECU software, and weaknesses in the vehicle's systems design.

Nowadays, the growing need to connect modern vehicles through computer networks leads to increased risks of cyberattacks. The internal network, which governs the several electronic components of a vehicle, is becoming increasingly overexposed to external attacks. The Controller Area Network (CAN) protocol, used to interconnect those devices is the key point of the internal network of modern vehicles. Therefore, securing such protocol is crucial to ensure a safe driving experience. However, the CAN is a standard that has undergone little changes since it was introduced in 1983. More precisely, in an attempt to reduce latency, the transfer of information remains unencrypted, which today represents a weak point in the protocol. Hence, the need to protect communications, without introducing low-level alterations, while preserving the performance characteristics of the protocol. In this work, we investigate the possibility of using symmetric encryption algorithms for securing messages exchanged by CAN protocol. In particular, we evaluate the using of lightweight ciphers to secure CAN-level communication. Such ciphers represent a reliable solution on hardware-constrained devices, such as microcontrollers.

The presence of security vulnerabilities in automotive networks has already been shown by various publications in recent years. Due to the specification of the Controller Area Network (CAN) as a broadcast medium without security mechanisms, attackers are able to read transmitted messages without being noticed and to inject malicious messages. In order to detect potential attackers within a network or software system as early as possible, Intrusion Detection Systems (IDSs) are prevalent. Many approaches for vehicles are based on techniques which are able to detect deviations from specified CAN network behaviour regarding protocol or payload properties. However, it is challenging to detect attackers who secretly connect to CAN networks and do not actively participate in bus traffic. In this paper, we present an approach that is capable of successfully detecting unknown CAN devices and determining the distance (cable length) between the attacker device and our sensing unit based on Time Domain Reflectometry (TDR) technique. We evaluated our approach on a real vehicle network.

Controller Area Network is the most widely adopted communication standard in automobiles. The CAN protocol is robust and is designed to minimize overhead. The light-weight nature of this protocol implies that it can't efficiently process secure communication. With the exponential increase in automobile communications, there is an urgent need for efficient and effective security countermeasures. We propose a support vector machine based intrusion detection system that is able to detect anomalous behavior with high accuracy. We outline a process for parameter selection and feature vector selection. We identify strengths and weaknesses of our system and propose to extend our work for time-series based data.

Security is a critical issue for new car generation targeting intelligent transportation systems (ITS), involving autonomous and connected vehicles. In this work we designed a low cost CAN probe and defined analysis tools in order to build attack scenarios. We reuse some threats identified by a previous work. Future researches will address new security protocols.

While deep learning has shown a great potential in various domains, the lack of transparency has limited its application in security or safety-critical areas. Existing research has attempted to develop explanation techniques to provide interpretable explanations for each classification decision. Unfortunately, current methods are optimized for non-security tasks ( e.g., image analysis). Their key assumptions are often violated in security applications, leading to a poor explanation fidelity. In this paper, we propose LEMNA, a high-fidelity explanation method dedicated for security applications. Given an input data sample, LEMNA generates a small set of interpretable features to explain how the input sample is classified. The core idea is to approximate a local area of the complex deep learning decision boundary using a simple interpretable model. The local interpretable model is specially designed to (1) handle feature dependency to better work with security applications ( e.g., binary code analysis); and (2) handle nonlinear local boundaries to boost explanation fidelity. We evaluate our system using two popular deep learning applications in security (a malware classifier, and a function start detector for binary reverse-engineering). Extensive evaluations show that LEMNA's explanation has a much higher fidelity level compared to existing methods. In addition, we demonstrate practical use cases of LEMNA to help machine learning developers to validate model behavior, troubleshoot classification errors, and automatically patch the errors of the target models.

The intrinsic use of SDN/NFV technologies in 5G infrastructures promise to enable the flexibility and programmability of networks to ensure lower cost of network and service provisioning and operation, however it brings new challenges and requirements due to new architectural changes. In terms of security, authentication and authorization functions need to evolve towards the new and emerging 5G virtualization platforms in order to meet the requirements of service providers and infrastructure operators. Over the years, a lot of authentication techniques have been used. Now, a wide range of options arise allowing to extend existing authentication and authorization mechanisms. This paper focuses on proposing and showcasing a 5G platform oriented solution among different approaches to integrate authentication and authorization functionalities, an adapted secure and stateless mechanism, providing identity and permissions management to handle not only users, but also system micro-services, in a network functions virtualization management and orchestration (NFV MANO) system, oriented to deploy virtualized services. The presented solution uses the NFV-based SONATA Service Platform which offers capabilities for a continuous integration and delivery DevOps methodology that allow high levels of programmability and flexibility to manage the entire life cycle of Virtual Network Functions, and enables the perfect scenario to showcase different approaches for authentication and authorization mechanisms for users and micro-services in a 5G platform.

Low-power wide area networks (LPWANs), such as LoRa, are fast emerging as the preferred networking technology for large-scale Internet of Things deployments (e.g., smart cities). Due to long communication range and ultra low power consumption, LPWAN-enabled sensors are today being deployed in a variety of application scenarios where sensitive information is wirelessly transmitted. In this work, we study the privacy guarantees of LPWANs, in particular LoRa. We show that, although the event-based duty cycling of radio communication, i.e., transmission of radio signals only when an event occurs, saves power, it inherently leaks information. This information leakage is independent of the implemented crypto primitives. We identify two types of information leakage and show that it is hard to completely prevent leakage without incurring significant additional communication and computation costs.

Security is a vital aspect of industrial control systems since they are used in critical infrastructures and manufacturing processes. As demonstrated by the increasing number of emerging exploits, securing such systems is still a challenge as the employed fieldbus technologies do not offer intrinsic support for basic security objectives. In this work we discuss some security aspects of DeviceNet, a communication protocol widely used for control applications especially in the North American industrial sector. Having the Controller Area Network (CAN) protocol at its base, DeviceNet inherits all the vulnerabilities that were already illustrated on CAN in-vehicle communication. We discuss how the lack of security in DeviceNet can be exploited and point on the fact that these vulnerabilities can be modelled by existing formal verification tools and countermeasures can be put in place.

Larger companies need more sites in the wide area network (WAN). However, internet service providers cannot obtain sufficient capacity to handle peak traffic, causing a terrible delay. The software-defined network (SDN) allows to own more programmability, adaptability, and application-aware, but scalability is a critical problem for merging both. This paper proposes a solution based on Protocol-Oblivious Forwarding (POF). It is a higher degree of decoupling control and data planes. The control plane uses fields unrelated to the protocol to unify packet match and route, and the data plane uses a set of general flow instructions in fast forwarding. As a result, we only save three flow tables on the forwarding paths so that each packet keeps a pipeline in the source route header to mark the next output ports. This solution can support a constant delay while the network expands.

With software defined networking and network function virtualization technologies, networks can be programmed to have customized processing and paths for different traffic at manageable costs and for massive numbers of applications. Now, picture a future Internet where each entity - a person, an organization, or an autonomous system - has the ability to choose how traffic in their respective network sessions is routed and processed between itself and its counterparts. The network is, essentially, liberated from today's homogeneous IP-based routing and limited connection options. To realize such a network paradigm, we propose a software defined exchange architecture that can provide the needed network programmability, session-level customization, and scale. We present a case study for traffic-analysis-resistant communication among individuals, campuses, or web services, where IP addresses no longer need to have a one-to-one correspondence with service providers.

Increased connectivity increases the attack vector. This also applies to connected vehicles in which vulnerabilities not only threaten digital values but also humans and the environment. Typically, attackers try to exploit the Controller Area Network (CAN) bus, which is the most widely used standard for internal vehicle communication. Once an Electronic Control Unit (ECU) connected to the CAN bus is compromised, attackers can manipulate messages at will. The missing sender authentication by design of the CAN bus enables adversarial access to vehicle functions with severe consequences. In order to address this problem, we propose Scission, an Intrusion Detection System (IDS) which uses fingerprints extracted from CAN frames, enabling the identification of sending ECUs. Scission utilizes physical characteristics from analog values of CAN frames to assess whether it was sent by the legitimate ECU. In addition, to detect comprised ECUs, the proposed system is able to recognize attacks from unmonitored and additional devices. We show that Scission is able to identify the sender with an average probability of 99.85%, during the evaluation on two series production cars and a prototype setup. Due to the robust design of the system, the evaluation shows that all false positives were prevented. Compared to previous approaches, we have significantly reduced hardware costs and increased identification rates, which enables a broad application of this technology.

While vehicle to everything (V2X) communication enables safety-critical automotive control systems to better support various connected services to improve safety and convenience of drivers, they also allow automotive attack surfaces to increase dynamically in modern vehicles. Many researchers as well as hackers have already demonstrated that they can take remote control of the targeted car by exploiting the vulnerabilities of in-vehicle networks such as Controller Area Networks (CANs). For assuring CAN security, we focus on how to authenticate electronic control units (ECUs) in real-time by addressing the security challenges of in-vehicle networks. In this paper, we propose a novel and lightweight authentication protocol with an attack-resilient tree algorithm, which is based on one-way hash chain. The protocol can be easily deployed in CAN by performing a firmware update of ECU. We have shown analytically that the protocol achieves a high level of security. In addition, the performance of the proposed protocol is validated on CANoe simulator for virtual ECUs and Freescale S12XF used in real vehicles. The results show that our protocol is more efficient than other authentication protocol in terms of authentication time, response time, and service delay.

Modern vehicles may contain a considerable number of ECUs (Electronic Control Units) which are connected through various means of communication, with the CAN (Controller Area Network) protocol being the most widely used. However, several vulnerabilities such as the lack of authentication and the lack of data encryption have been pointed out by several authors, which ultimately render vehicles unsafe to their users and surroundings. Moreover, the lack of security in modern automobiles has been studied and analyzed by other researchers as well as several reports about modern car hacking have (already) been published. The contribution of this work aimed to analyze and test the level of security and how resilient is the CAN protocol by taking a BMW E90 (3-series) instrument cluster as a sample for a proof of concept study. This investigation was carried out by building and developing a rogue device using cheap commercially available components while being connected to the same CAN-Bus as a man in the middle device in order to send spoofed messages to the instrument cluster.

The Controller Area Network (CAN) is a broadcast communications network invented by Robert Bosch GmbH in 1986. CAN is the standard communication network found in automobiles, industry equipment, and many space applications. To be used in these environments, CAN is designed for efficiency and reliability, rather than security. This research paper closely examines the security risks within the CAN protocol and proposes a feasible solution. In this research, we investigate the problems with implementing certain security features in the CAN protocol, such as message authentication and protections against replay and denial-of-service (DoS) attacks. We identify the restrictions of the CAN bus, and we demonstrate how our proposed implementation meets these restrictions. Many previously proposed solutions lack security, feasibility, and/or efficiency; however, a solution must not drastically hinder the real-time operation speed of the network. The solution proposed in this research is tested with a simulative CAN environment. This paper proposes an alteration to the standard CAN bus nodes and the CAN protocol to better protect automobiles and other CAN-related systems from attacks.

Traditional countermeasures to relay attacks are difficult to implement on mobile devices due to hardware limitations. Establishing proximity of a payment device and terminal is the central notion of most relay attack countermeasures, and mobile devices offer new and exciting possibilities in this area of research. One such possibility is the use of on-board sensors to measure ambient data at both the payment device and terminal, with a comparison made to ascertain whether the device and terminal are in close proximity. This project focuses on the iPhone, specifically the iPhone 6S, and the potential use of its sensors to both establish proximity to a payment terminal and protect Apple Pay against relay attacks. The iPhone contains 12 sensors in total, but constraints introduced by payment schemes mean only 5 were deemed suitable to be used for this study. A series of mock transactions and relay attack attempts are enacted using an iOS application written specifically for this study. Sensor data is recorded, and then analysed to ascertain its accuracy and suitability for both proximity detection and relay attack countermeasures.

Web servers use SSL/TLS to establish secure communication between clients and servers. The mechanism of SSL/TLS relies on a key pair to validate the server and to protect the confidentiality of the data. However, many websites are running on third-party servers or on cloud environments where website owners have no control over the physical servers or the software including the operating systems but still need to trust and store the private key on the servers. While it is common to store the encrypted key on the disk, the web server still need a decrypted key inside the memory during the operation. Thus, an adversary could obtain the private key residing on the web server's memory. In this paper, we propose a secure enclave for a web server running the high privilege code that handles the secret keys inside an encrypted memory area by utilizing Intel Software Guard Extension (SGX) whereas other components of the web server outside the trusted computing base are left intact. The experimental results show 19% to 38% implementation overhead depending on which cipher suite is used and how a session key is handled.

Today Machine to Machine (M2M) communications are very expanded in many application areas. M2M devices are likely to be small and able to operate for long periods and transmit data through wireless links, it is also defined as machine type communication (MTC) in Release 10 of the 3GPP "3rd Generation Partnership Project". Recently, most research has focused on congestion control, sensing information and control technologies and resource management, etc, but there are not many studies on the security aspects. Indeed, M2M communications and equipments may be exposed to different types of attacks (physical attacks on equipment and recovery of sensitive data, configurations attacks to compromise the software, attacks on the communications protocol, etc). In this article we introduce security into the M2M architecture and discuss the most important question of security, which is the group access authentication by modifying existing authentication protocols, such as group authentication and key agreement protocol used to resolve the group access authentication for M2M.

Graph modeling allows numerous security problems to be tackled in a general way, however, little work has been done to understand their ability to withstand adversarial attacks. We design and evaluate two novel graph attacks against a state-of-the-art network-level, graph-based detection system. Our work highlights areas in adversarial machine learning that have not yet been addressed, specifically: graph-based clustering techniques, and a global feature space where realistic attackers without perfect knowledge must be accounted for (by the defenders) in order to be practical. Even though less informed attackers can evade graph clustering with low cost, we show that some practical defenses are possible.

The Controller Area Network (CAN) is a widely used industry-standard intra-vehicle broadcast network that connects the Electronic Control Units (ECUs) which control most car systems. The CAN contains substantial vulnerabilities that can be exploited by attackers to gain control of the vehicle, due to its lack of security measures. To prevent an attacker from sending malicious messages through the CAN bus to take over a vehicle, we propose the addition of a secure hardware-based module, or Security ECU (SECU), onto the CAN bus. The SECU can perform key distribution and message verification, as well as corrupting malicious messages before they are fully received by an ECU. Only software modification is needed for existing ECUs, without changing the CAN protocol. This provides backward compatibility with existing CAN systems. Furthermore, we collect 6.673 million CAN bus messages from various cars, and find that the CAN messages collectively have low entropy, with an average of 11.915 bits. This finding motivates our proposal for CAN bus message compression, which allows us to significantly reduce message size to fit the message and its message authentication code (MAC) within one CAN frame, enabling fast authentication. Since ECUs only need to generate the MACs (and not verify them), the delay and computation overhead are also reduced compared to traditional authentication mechanisms. Our authentication mechanism is implemented on a realistic testbed using industry standard MCP2551 CAN transceivers and Raspberry Pi embedded systems. Experimental results demonstrate that our mechanism can achieve real-time message authentication on the CAN bus with minimal latency.

The Controller Area Network (CAN) is still the most widely employed bus in the automotive sector. Its lack of security mechanisms led to a high number of attacks and consequently several security countermeasures were proposed, i.e., authentication protocols or intrusion detection mechanisms. We discuss vulnerabilities of the CAN data link layer that can be triggered from the application level with the use of an off the shelf CAN transceiver. Namely, due to the wired-AND design of the CAN bus, dominant bits will always overwrite recessive ones, a functionality normally used to assure priority for frames with low value identifiers. We exploit this characteristic and show Denial of Service attacks both on senders and receivers based on bit injections by using bit banging to maliciously control the CAN transceiver. We demonstrate the effects and limitations of such attacks through experimental analysis and discuss possible countermeasures. In particular, these attacks may have high impact on centralized authentication mechanisms that were frequently proposed in the literature since these attacks can place monitoring nodes in a bus-off state for certain periods of time.

The high mobility of Army tactical networks, combined with their close proximity to hostile actors, elevates the risks associated with short-range network attacks. The connectivity model for such short range connections under active operations is extremely fluid, and highly dependent upon the physical space within which the element is operating, as well as the patterns of movement within that space. To handle these dependencies, we introduce the notion of "key cyber-physical terrain": locations within an area of operations that allow for effective control over the spread of proximity-dependent malware in a mobile tactical network, even as the elements of that network are in constant motion with an unpredictable pattern of node-to-node connectivity. We provide an analysis of movement models and approximation strategies for finding such critical nodes, and demonstrate via simulation that we can identify such key cyber-physical terrain quickly and effectively.

In IoT environments, the user may have many devices to connect each other and share the data. Also, the device will not have the powerful computation and storage ability. Many studies have focused on the lightweight authentication between the cloud server and the client in this environment. They can use the cloud server to help sensors or proxies to finish the authentication. But in the client side, how to create the group session key without the cloud capability is the most important issue in IoT environments. The most popular application network of IoT environments is the wireless body area network (WBAN). In WBAN, the proxy usually needs to control and monitor user's health data transmitted from the sensors. In this situation, the group authentication and group session key generation is needed. In this paper, in order to provide an efficient and robust group authentication and group session key generation in the client side of IoT environments, we propose a lightweight authentication scheme with dynamic group members in IoT environments. Our proposed scheme can satisfy the properties including the flexible generation of shared group keys, the dynamic participation, the active revocation, the low communication and computation cost, and no time synchronization problem. Also our scheme can achieve the security requirements including the mutual authentication, the group session key agreement, and prevent all various well-known attacks.

This study stems from the premise that we need to break away from the "reactive" cycle of developing defenses against new DDoS attacks (e.g., amplification) by proactively investigating the potential for new types of DDoS attacks. Our specific focus is on pulsating attacks, a particularly debilitating type that has been hypothesized in the literature. In a pulsating attack, bots coordinate to generate intermittent pulses at target links to significantly reduce the throughput of TCP connections traversing the target. With pulsating attacks, attackers can cause significantly greater damage to legitimate users than traditional link flooding attacks. To date, however, pulsating attacks have been either deemed ineffective or easily defendable for two reasons: (1) they require a central coordinator and can thus be tracked; and (2) they require tight synchronization of pulses, which is difficult even in normal non-congestion scenarios. This paper argues that, in fact, the perceived drawbacks of pulsating attacks are in fact not fundamental. We develop a practical pulsating attack called CICADAS using two key ideas: using both (1) congestion as an implicit signal for decentralized implementation, and (2) a Kalman-filter-based approach to achieve tight synchronization. We validate CICADAS using simulations and wide-area experiments. We also discuss possible countermeasures against this attack.

New viewpoints of covert channels are presented in this work. First, the origin of covert channels is traced back to acc ess control and a new class of covert channel, air-gap covert channels, is presented. Second, we study the design of covert channels and provide novel insights that differentiate the research area of undetectable communication from that of covert channels. Third, we argue that secure systems can be characterized as fixed-source systems or continuous-source systems, i.e., systems whose security is compromised if their design allows a covert channel to communicate a small, fixed amount of information or communicate information at a sufficiently high, continuous rate, respectively. Consequently, we challenge the traditional method for measuring covert channels, which is based on Shannon capacity, and propose that a new measure, steganographic capacity, be used to accurately assess the risk posed by covert channels, particularly those affecting fixed-source systems. Additionally, our comprehensive review of covert channels has led us to the conclusion that important properties of covert channels have not been captured in previous taxonomies. We, therefore, present novel extensions to existing taxonomies to more accurately characterize covert channels.