automotive security DoS
216554877
A novel cyber security framework leveraging programmable capabilities in digital services
The introduction of new computing and networking paradigms, which leverage virtualization and service oriented architectures, has brought far more agility than ever in the creation and concatenation of digital services. Yet it raises new security and privacy concerns that cannot be properly tackled by existing tools and models. In this paper, we briefly review the main characteristics of emerging digital services, point out open cyber security challenges, and discuss the need to include cyber security programmable capabilities in every digital component. We also describe a novel framework for managing such functions and implement multiple security services for complex business chains.
ITASEC
Matteo Repetto Alessandro Carrega Armend Duzha
218549951
On the Performance of Detecting Injection of Fabricated Messages into the CAN Bus
There have been several public demonstrations of attacks on connected vehicles showing the ability of an attacker to take control of a targeted vehicle by injecting messages into their CAN bus. In this paper, using injected speed reading and RPM reading messages in in motion vehicle, we examine the ability of the Pearson correlation and the unsupervised learning methods k means clustering and HMM to differentiate 'no attack' and 'under attack' states of the given vehicle. We found that the Pearson correlation distinguishes the two states, the k means clustering method has an acceptable accuracy but high false positive rate and HMM detects attacks with acceptable detection rate but has a high false positive in detecting attacks from speed readings when there is no attack. The accuracy of these unsupervised learning methods are comparable to the ones of the supervised learning methods used by CAN bus IDS suppliers. In addition, the paper shows that studying CAN anomaly detection techniques using off vehicle test facilities may not properly evaluate the performance of the detection techniques. The results suggest using other features besides the data content of the CAN messages and integrate knowledge about how the ECU collaborate in building effective techniques for the detection of injection of fabricated message attacks.
Lotfi Ben Othmane Lalitha Dhulipala Nicholas J Multari Manimaran Govindarasu
214215373
Efecto de la suspension en la estabilidad al vuelco y direccionamiento de robots moviendose sobre discontinuidades de terreno
This article studies the effect produced by the suspension system in tip over stability and steerability of a Skid Steer mobile robot, when it faces different terrain discontinuities: descent (front and side) and ascent on steps, plus displacement over ditches. Specifically, the moment was studied when impact loads producted by the robot's movement on the irregularity of the terrain are generated. In each case, a correlational analysis was made about the effect in tip over stability and steerability (quantified with metrics based on the reaction forces of the wheels with the ground) by varying four parameters that define the suspension system: stiffness constant in the springs, damping constant in the dampers and the stiffness and damping constants in the wheels. Finally, it was estimated for each case, what magnitudes these parameters should acquire to ensure better stability and steerability of robot.
A Valero A Bohorquez
212671625
Dismantling DST80 based Immobiliser Systems
Car manufacturers deploy vehicle immobiliser systems in order to prevent car theft. However, in many cases the underlying cryptographic primitives used to authenticate a transponder are proprietary in nature and thus not open to public scrutiny. In this paper we publish the proprietary Texas Instruments DST80 cipher used in immobilisers of several manufacturers. Additionally, we expose serious flaws in immobiliser systems of major car manufacturers such as Toyota, Kia, Hyundai and Tesla. Specifically, by voltage glitching the firmware protection mechanisms of the microcontroller, we extracted the firmware from several immobiliser ECUs and reverse engineered the key diversification schemes employed within. We discovered that Kia and Hyundai immobiliser keys have only three bytes of entropy and that Toyota only relies on publicly readable information such as the transponder serial number and three constants to generate cryptographic keys. Furthermore, we present several practical attacks which can lead to recovering the full 80 bit cryptographic key in a matter of seconds or permanently disabling the transponder. Finally, even without key management or configuration issues, we demonstrate how an attacker can recover the cryptographic key using a profiled side channel attack. We target the key loading procedure and investigate the practical applicability in the context of portability. Our work once again highlights the issues automotive vendors face in implementing cryptography securely.
IACR Trans. Cryptogr. Hardw. Embed. Syst.
Lennert Wouters Jan Van den Herrewegen Flavio D Garcia David Oswald Benedikt Gierlichs Bart Preneel
211561060
Novel Deception Techniques for Malware Detection on Industrial Control Systems
To maintain the availability of industrial control systems (ICS) it is important to robustly detect malware infection that spreads within the ICS network. In ICS, a host often communicates with the determined hosts; for instance, a supervisory control host observes and controls the same devices routinely via the network. Therefore, a communication request to the unused internet protocol (IP) address space, i.e. darknet, in the ICS network is likely to be caused by malware in the compromised host in the network. That is, darknet monitoring may enable us to detect malware that tries to spread indiscriminately within the network. On the other hand, advanced malware, such as malware determining target hosts of infection with reference to host lists in the networks, infects the confined hosts in the networks, and consequently evades detection by security sensors or honeypots. In this paper, we propose novel deception techniques that lure such malware to our sensor, by embedding the sensor information continuously in the lists of hosts in the ICS networks. In addition, the feasibility of the proposed deception techniques is shown through our simplified implementation by using actual malware samples: WannaCry and Conficker.
IACR Cryptol. ePrint Arch.
Takanori Machida Dai Yamamoto Yuki Unno Hisashi Kojima
216230805
Trump's Foreign Policy and International Trade Law
Donald Trump has based his Foreign Policy in the area of international trade on two main objectives. The first one seeks to promote "fair trade" in order to bring down trade deficits, restore reciprocity and balance in the trade relations of the United States with its trading partners and defend American commercial interests against and/or beyond other countries interests. On the second place, Trump's Foreign Policy intends to stop the de location of productive activities from the United States and create new jobs to foster a strong and growing domestic economy. The concrete fulfilment of these objectives have shaken deeply the most central foundations of International Trade Law: a normative system build after the Second World War to give legal basis and regulate the economic relations between states in the new international liberal order. In the first place, Trump's Foreign Policy's neo protectionism represents a frontal attack on free trade, as a dominant paradigm of International Trade Law. In the second place, the avowed bilateralism of this Policy is the exact opposite of the multilateralism, promoted by the norms and institutions of International Trade Law. Both neo protectionism and bilateralism manifest a broader crisis of States' cooperation in the Post World War II international liberal order.
Virdzhiniya Petrova Georgieva
216111105
Evaluation of CAN Bus Security Challenges
The automobile industry no longer relies on pure mechanical systems; instead, it benefits from many smart features based on advanced embedded electronics. Although the rise in electronics and connectivity has improved comfort, functionality, and safe driving, it has also created new attack surfaces to penetrate the in vehicle communication network, which was initially designed as a close loop system. For such applications, the Controller Area Network (CAN) is the most widely used communication protocol, which still suffers from various security issues because of the lack of encryption and authentication. As a result, any malicious/hijacked node can cause catastrophic accidents and financial loss. This paper analyses the CAN bus comprehensively to provide an outlook on security concerns. It also presents the security vulnerabilities of the CAN and a state of the art attack surface with cases of implemented attack scenarios and goes through different solutions that assist in attack prevention, mainly based on an intrusion detection system (IDS)
Sensors
Mehmet Bozdal Mohammad Samie Sohaib Aslam Ian K Jennions
215733875
Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions
The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state of the art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.
Sensors
Martin W Hoffmann Stephan Wildermuth Ralf Gitzel Aydin Boyaci Jorg Gebhardt Holger Kaul Ido Amihai Bodo Forg Michael Suriyah Thomas Leibfried Volker Stich Jan Hicking Martin Bremer Lars Kaminski Daniel Beverungen Philipp zur Heiden Tanja Tornede
219106531
Five Maturity Levels of Managing AI: From Isolated Ignorance to Integrated Intelligence
To guide future discussions about managing artificial intelligence (AI) this article suggests an AI management framework with five maturity levels, which are comparable to the five levels of the autonomous driving framework from no automation to complete automation. If companies move beyond Isolated Ignorance (Level 0) they are characterized by an Initial Intent (Level 1) which typically evolves towards an Independent Initiative (Level 2) A more advanced management leads to Interactive Implementation (Level 3) and Interdependent Innovation (Level 4) On this basis, a close combination of AI and human knowledge enables a sustainable competitive advantage with Integrated Intelligence (Level 5) This framework draws on the intelligence based approach to company performance, and it provides the basis for an AI maturity assessment in organizations. It further helps to identify many firms' managerial challenges as well as major organizational limitations even in those firms that are often considered as AI leaders.
Ulrich Lichtenthaler
216156871
Threats and Alert Analytics in Autonomous Vehicles
Autonomous vehicles or self driving cars emerged with a promise to deliver a driving experience that is safe, secure, law abiding, alleviates traffic congestion and reduces traffic accidents. These self driving cars predominantly rely on wireless technology, vehicular ad hoc networks (VANETs) and Vehicle to Vehicle (V2V) networks, Road Side Units (RSUs) Millimeter Wave radars, light detection and ranging (LiDAR) sensors and cameras, etc. Since these vehicles are so dexterous and equipped with such advanced driver assistance technological features, their dexterity invites threats, vulnerabilities and hacking attacks. This paper aims to understand and study the technology behind these self driving cars and explore, identify and address popular threats, vulnerabilities and hacking attacks to which these cars are prone. This paper also establishes a relationship between these threats, trust and reliability. An analysis of the alert systems in self driving cars is also presented. keywords: Self driving cars, advanced driver assistance systems, trust, reliability, ethics, security, threats, vulnerabilities
CATA
Aakanksha Rastogi Kendall E Nygard