Searched for: subject%3A%22countermeasure%22
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Aljuffri, A.A.M. (author)
The security of electronic devices holds the greatest importance in the modern digital era, with one of the emerging challenges being the widespread occurrence of hardware attacks. The aforementioned attacks present a substantial risk to hardware devices, and it is of utmost importance to comprehend the potential detrimental effects they may...
doctoral thesis 2024
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Muntenaar, Laura (author)
Demand for smart, Internet-connected devices and other electronics has increased dramatically in recent years. This increase in demand for technological devices, driven by advancements in Artificial Intelligence (AI), the Internet of Things (IoT), and autonomous systems, has exposed the digital system to potential security threats. As more...
master thesis 2023
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Köylü, T.C. (author)
Machine learning has gained a lot of recognition recently and is now being used in many important applications. However, this recognition was limited in the hardware security area. Especially, very few approaches depend on this powerful tool to detect attacks during operation. This thesis reduces this gap in the field of fault injection attack...
doctoral thesis 2023
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Wu, L. (author)
For almost three decades, side-channel analysis has represented a realistic and severe threat to embedded devices' security. As a well-known and influential class of implementation attacks, side-channel analysis has been applied against cryptographic implementations, processors, communication systems, and, more recently, machine learning models....
doctoral thesis 2023
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Köylü, T.C. (author), Reinbrecht, Cezar (author), Brandalero, Marcelo (author), Hamdioui, S. (author), Taouil, M. (author)
Fault injection attacks are a threat to all digital systems, especially to the ones conducting security sensitive operations. Recently, the strategy of observing the instruction flow to detect attacks has gained popularity. In this paper, we provide a comparative study between three hardware-based techniques (i.e., recurrent neural network (RNN)...
journal article 2022
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Köylü, T.C. (author), Hamdioui, S. (author), Taouil, M. (author)
Artificial neural networks (ANNs) are used to accomplish a variety of tasks, including safety critical ones. Hence, it is important to protect them against faults that can influence decisions during operation. In this paper, we propose smart and low-cost redundancy schemes that protect the most vulnerable ANN parts against fault attacks....
conference paper 2022
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Aljuffri, A.A.M. (author), Reinbrecht, Cezar (author), Hamdioui, S. (author), Taouil, M. (author), Sepulveda, Johanna (author)
Currently NIST is working towards the standardization of lightweight cryptography (LWC). Although the cryptanalytic strength of LWC is currently under deep scrutiny, the LWC implementation security has not been yet widely explored. GIFT block cipher is the main building block of many of the LWC NIST candidates and therefore has the potential to...
conference paper 2022
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Rijsdijk, Jorai (author), Wu, L. (author), Perin, G. (author)
Deep learning-based side-channel attacks are capable of breaking targets protected with countermeasures. The constant progress in the last few years makes the attacks more powerful, requiring fewer traces to break a target. Unfortunately, to protect against such attacks, we still rely solely on methods developed to protect against generic...
conference paper 2022
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Verrer, Daan (author)
Modern implementations of encryption algorithms on CPU’s that use frequent memory lookups of precomputed functions, are vulnerable to Cache based Side­Channel Attacks. The ρ­-VEX processor, a runtime reconfigurable VLIW processor developed at the Computer and Quantum Engineering department at the TU Delft was identified to possibly allow for...
master thesis 2021
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Korpas Kamarianos, Alexandros (author)
Over the last decades, side-channel attacks (SCAs) have been proven as a substantial weakness of cryptographic devices, while the recent growth of deep learning (DL) dramatically improved the performance of SCA. More and more researches present ways to build lightweight deep neural network (DNN) models that can retrieve the secret encryption key...
master thesis 2021
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Köylü, T.C. (author), Reinbrecht, Cezar (author), Hamdioui, S. (author), Taouil, M. (author)
Artificial neural networks are currently used for many tasks, including safety critical ones such as automated driving. Hence, it is very important to protect them against faults and fault attacks. In this work, we propose two fault injection attack detection mechanisms: one based on using output labels for a reference input, and the other on...
conference paper 2021
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Noroozian, A. (author), Turcios Rodriguez, E.R. (author), Lastdrager, Elmer (author), Kasama, Takahiro (author), van Eeten, M.J.G. (author), Hernandez Ganan, C. (author)
For the mitigation of compromised Internet of Things (IoT) devices we rely on Internet Service Providers (ISPs) and their users. Given that devices are in the hands of their subscribers, what can ISPs realistically do? This study examines the effects of ISP countermeasures on infections caused by variants of the notorious Mirai family of IoT...
conference paper 2021
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Rijsdijk, Jorai (author)
Side-channel attacks (SCA), which use unintended leakage to retrieve a secret cryptographic key, have become more sophisticated over time. With the recent successes of machine learning (ML) and especially deep learning (DL) techniques against cryptographic implementations even in the presence of dedicated countermeasures, various methods have...
master thesis 2020
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Talluri, Pavan (author)
The adoption of Microprocessors is increasingly diversifying to several embedded and mo- bile devices. Growingly they can also be found in Smart Cards, RFID tags, SIM cards, Pay TVs, identity cards and passports. These devices store, processes and transact sensitive information like social security numbers and credit card numbers. Ensuring...
master thesis 2020
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Reinbrecht, Cezar (author), Aljuffri, A.A.M. (author), Hamdioui, S. (author), Taouil, M. (author), Forlin, Bruno E. (author), Sepulveda, Johanna (author)
Multi-Processor System-on-Chips (MPSoCs) are popular computational platforms for a wide variety of applications due to their energy efficiency and flexibility. Like many other platforms they are vulnerable to Side Channel Attacks (SCAs). In particular, Logical SCAs (LSCAs) are very powerful as sensitive information can be retrieved by simply...
conference paper 2020
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Wu, L. (author), Picek, S. (author)
In the profiled side-channel analysis, deep learning-based techniques proved to be very successful even when attacking targets protected with countermeasures. Still, there is no guarantee that deep learning attacks will always succeed. Various countermeasures make attacks significantly more complex, and such countermeasures can be further...
journal article 2020
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Wang, Haoyu (author)
Transition zones in railway tracks are locations with considerable changes in the vertical stiffness of the track support, which can be found near bridges, culverts and tunnels. In such locations, the stiffness variation and the differential settlement of tracks (uneven settlement of the track on the embankment and of the engineering structure)...
doctoral thesis 2019
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Krishnan, S. (author), Lin, Jiabiao (author), Simanjuntak, Johannes (author), Hooimeijer, F.L. (author), Bricker, J.D. (author), Daniël, Maäyan (author), Yoshida, Y. (author)
Engineering for flood resilience of dense coastal regions often neglects the resultant impact on urban design quality. Vital subsurface infrastructure such as hydraulic systems, water networks, civil construction, transport, energy supply and soil systems are especially important in shaping the urban environment and integrating resilience....
journal article 2019
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Picek, S. (author), Heuser, Annelie (author), Jovic, Alan (author), Batina, Lejla (author)
Profiled side-channel attacks consist of several steps one needs to take. An important, but sometimes ignored, step is a selection of the points of interest (features) within side-channel measurement traces. A large majority of the related works start the analyses with an assumption that the features are preselected. Contrary to this...
journal article 2019
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Baron-Hyppolite, C.G. (author), Lashley, Christopher H. (author), Garzon, Juan (author), Miesse, Tyler (author), Bricker, J.D. (author)
Assessing the accuracy of nearshore numerical models—such as SWAN—is important to ensure their effectiveness in representing physical processes and predicting flood hazards. In particular, for application to coastal wetlands, it is important that the model accurately represents wave attenuation by vegetation. In SWAN, vegetation might be...
journal article 2018
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