IoT devices are being widely deployed. But the huge variance among them in the level of security and requirements for network resources makes it unfeasible to manage IoT networks using a common ...generic policy. One solution to this challenge is to define policies for classes of devices based on device type . In this paper, we present AuDI, a system for quickly and effectively identifying the type of a device in an IoT network by analyzing their network communications. AuDI models the periodic communication traffic of IoT devices using an unsupervised learning method to perform identification. In contrast to prior work, AuDI operates autonomously after initial setup, learning, without human intervention nor labeled data, to identify previously unseen device types. AuDI can identify the type of a device in any mode of operation or stage of lifecycle of the device. Via systematic experiments using 33 off-the-shelf IoT devices, we show that AuDI is effective (98.2% accuracy).
Industrial control systems (ICSs) are transitioning from legacy-electromechanical-based systems to modern information and communication technology (ICT)-based systems creating a close coupling ...between cyber and physical components. In this paper, we explore the ICS cybersecurity landscape including: 1) the key principles and unique aspects of ICS operation; 2) a brief history of cyberattacks on ICS; 3) an overview of ICS security assessment; 4) a survey of "uniquely-ICS" testbeds that capture the interactions between the various layers of an ICS; and 5) current trends in ICS attacks and defenses.
Today, embedded, mobile, and cyberphysical systems are ubiquitous and used in many applications, from industrial control systems, modern vehicles, to critical infrastructure. Current trends and ...initiatives, such as "Industrie 4.0" and Internet of Things (IoT), promise innovative business models and novel user experiences through strong connectivity and effective use of next generation of embedded devices. These systems generate, process, and exchange vast amounts of security-critical and privacy-sensitive data, which makes them attractive targets of attacks. Cyberattacks on IoT systems are very critical since they may cause physical damage and even threaten human lives. The complexity of these systems and the potential impact of cyberattacks bring upon new threats.
This paper gives an introduction to Industrial IoT systems, the related security and privacy challenges, and an outlook on possible solutions towards a holistic security framework for Industrial IoT systems.
Secure firmware update is an important stage in the Internet of Things (IoT) device life-cycle. Prior techniques, designed for other computational settings, are not readily suitable for IoT devices, ...since they do not consider idiosyncrasies of a realistic large-scale IoT deployment. This motivates our design of architecture for secure software update of realistic embedded devices ( ASSURED ), a secure and scalable update framework for IoT. ASSURED includes all stakeholders in a typical IoT update ecosystem, while providing end-to-end security between manufacturers and devices. To demonstrate its feasibility and practicality, ASSURED is instantiated and experimentally evaluated on two commodity hardware platforms. Results show that ASSURED is considerably faster than current update mechanisms in realistic settings.
IoT devices are increasingly deployed in daily life. Many of these devices are, however, vulnerable due to insecure design, implementation, and configuration. As a result, many networks already have ...vulnerable IoT devices that are easy to compromise. This has led to a new category of malware specifically targeting IoT devices. However, existing intrusion detection techniques are not effective in detecting compromised IoT devices given the massive scale of the problem in terms of the number of different types of devices and manufacturers involved. In this paper, we present DÏoT, an autonomous self-learning distributed system for detecting compromised IoT devices. DÏoT builds effectively on device-type-specific communication profiles without human intervention nor labeled data that are subsequently used to detect anomalous deviations in devices' communication behavior, potentially caused by malicious adversaries. DÏoT utilizes a federated learning approach for aggregating behavior profiles efficiently. To the best of our knowledge, it is the first system to employ a federated learning approach to anomaly-detection-based intrusion detection. Consequently, DÏoT can cope with emerging new and unknown attacks. We systematically and extensively evaluated more than 30 off-the-shelf IoT devices over a long term and show that DÏoT is highly effective (95.6% detection rate) and fast (257 ms) at detecting devices compromised by, for instance, the infamous Mirai malware. DÏoT reported no false alarms when evaluated in a real-world smart home deployment setting.
Code reuse attacks such as return-oriented programming (ROP) have become prevalent techniques to exploit memory corruption vulnerabilities in software programs. A variety of corresponding defenses ...has been proposed, of which some have already been successfully bypassed -- and the arms race continues. In this paper, we perform a systematic assessment of recently proposed CFI solutions and other defenses against code reuse attacks in the context of C++. We demonstrate that many of these defenses that do not consider object-oriented C++ semantics precisely can be generically bypassed in practice. Our novel attack technique, denoted as counterfeit object-oriented programming (COOP), induces malicious program behavior by only invoking chains of existing C++ virtual functions in a program through corresponding existing call sites. COOP is Turing complete in realistic attack scenarios and we show its viability by developing sophisticated, real-world exploits for Internet Explorer 10 on Windows and Fire fox 36 on Linux. Moreover, we show that even recently proposed defenses (CPS, T-VIP, vfGuard, and VTint) that specifically target C++ are vulnerable to COOP. We observe that constructing defenses resilient to COOP that do not require access to source code seems to be challenging. We believe that our investigation and results are helpful contributions to the design and implementation of future defenses against control flow hijacking attacks.
Remanence Decay Side-Channel: The PUF Case Zeitouni, Shaza; Oren, Yossef; Wachsmann, Christian ...
IEEE transactions on information forensics and security,
06/2016, Letnik:
11, Številka:
6
Journal Article
Recenzirano
We present a side-channel attack based on remanence decay in volatile memory and show how it can be exploited effectively to launch a noninvasive cloning attack against SRAM physically unclonable ...functions (PUFs) - an important class of PUFs typically proposed as lightweight security primitives, which use existing memory on the underlying device. We validate our approach using SRAM PUFs instantiated on two 65-nm CMOS devices. We discuss countermeasures against our attack and propose the constructive use of remanence decay to improve the cloning resistance of SRAM PUFs. Moreover, as a further contribution of independent interest, we show how to use our evaluation results to significantly improve the performance of the recently proposed TARDIS scheme, which is based on remanence decay in SRAM memory and used as a time-keeping mechanism for low-power clockless devices.
Automatic recognition of human faces is becoming increasingly popular in civilian and law enforcement applications that require reliable recognition of humans. However, the rapid improvement and ...widespread deployment of this technology raises strong concerns regarding the violation of individuals’ privacy. A typical application scenario for privacy-preserving face recognition concerns a client who privately searches for a specific face image in the face image database of a server.
In this paper we present a privacy-preserving face recognition scheme that substantially improves over previous work in terms of communication-and computation efficiency: the most recent proposal of Erkin et al. (PETS’09) requires \documentclass12pt{minimal}
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\begin{document}$\mathcal{O}(\log M)$\end{document} rounds and computationally expensive operations on homomorphically encrypted data to recognize a face in a database of M faces. Our improved scheme requires only \documentclass12pt{minimal}
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\begin{document}$\mathcal{O}(1)$\end{document} rounds and has a substantially smaller online communication complexity (by a factor of 15 for each database entry) and less computation complexity.
Our solution is based on known cryptographic building blocks combining homomorphic encryption with garbled circuits. Our implementation results show the practicality of our scheme also for large databases (e.g., for M = 1000 we need less than 13 seconds and less than 4 MByte online communication on two 2.4GHz PCs connected via Gigabit Ethernet).
The security of capacitive touchscreens is crucial since they have become the primary human-machine interface on smart devices. This paper presents Marionette , the first wired attack that creates ...ghost touches on capacitive touchscreens via charging cables and can manipulate the victim's devices with undesired consequences, e.g., establishing malicious Bluetooth connections. Our study provides a new threat vector against touchscreens that only requires connecting to a malicious charging port, which could be a public charging station, and is effective across various USB data blockers and power adapters. Despite the fact that smartphones employ abundant noise reduction and voltage management techniques, we manage to inject carefully crafted signals that can induce ghost touches within a chosen range. The underlying principle is to inject common-mode noises over the power line to avoid being effectively filtered yet affecting the touch measurement mechanism and synchronize the malicious noise with the screen measurement scanning cycles to place the ghost touches at target locations. We achieve three types of attacks, i.e., injection, alteration, and Denial-of-Service, and the evaluation of 12 commercial electronics, 6 power adapters, and 13 charging cables demonstrate the feasibility of Marionette .
The COVID-19 pandemic has caused many countries to deploy novel digital contact tracing (DCT) systems to boost the efficiency of manual tracing of infection chains. In this paper, we systematically ...analyze DCT solutions and categorize them based on their design approaches and architectures. We analyze them with regard to effectiveness, security, privacy and ethical aspects and compare prominent solutions based on these requirements. In particular, we discuss shortcomings of the Google and Apple Exposure Notification API (GAEN) that is currently widely adopted all over the world. We find that the security and privacy of GAEN has considerable deficiencies as it can be compromised by severe large-scale attacks. We also discuss other proposed approaches for contact tracing, including our proposal TraceCORONA , that are based on Diffie-Hellman (DH) key exchange and aim at tackling shortcomings of existing solutions. Our extensive analysis shows that TraceCORONA fulfills the above security requirements better than deployed state-of-the-art approaches. We have implemented TraceCORONA and its beta test version has been used by more than 2000 users without any major functional problems, 1 demonstrating that there are no technical reasons requiring to make compromises with regard to the requirements of DCT approaches.
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