Information and communications security: 20th International Conference, ICICS 2018, Lille, France, October 29-31, 2018, Proceedings

International audienceThis book constitutes the refereed proceedings of the 20th International Conference on Information and Communications Security, ICICS 2018, held in Lille, France, in October 2018. The 39 revised full papers and 11 short papers presented were carefully selected from 202 submissions. The papers are organized in topics on blockchain technology, malware, botnet and network security, real-world cryptography, encrypted computing, privacy protection, signature schemes, attack analysis and detection, searchable encryption and identity-based cryptography, verifiable storage and computing, applied cryptography, supporting techniques, formal analysis and cryptanalysis, attack detection, and security managemen

Hardware Implementations of NIST Lightweight Cryptographic Candidates: A First Look

Achieving security in the Internet of Things (IoT) is challenging. The need for lightweight yet robust cryptographic solutions suitable for the IoT calls for improved design and implementation of constructs such as authenticated encryption with associated data (AEAD) which can ensure confidentiality, integrity, and authenticity of data in one algorithm. The U.S. National Institute of Standards and Technology (NIST) has embarked on a multi-year effort called the lightweight cryptography (LWC) standardization process to evaluate lightweight AEAD and optional hash algorithms for inclusion in U.S. federal standards. As candidates are evaluated for many characteristics including hardware resources and performance, obtaining results of hardware implementations as early as possible is preferable. In this work, we implement six NIST LWC Round 2 candidate ciphers, SpoC, GIFT-COFB, COMET-AES, COMET-CHAM, Ascon, and Schwaemm and Esch, in the Artix-7, Spartan-6, and Cyclone-V FPGAs. Implementations are compliant with the newly-released hardware (HW) applications programming interface (API) for lightweight cryptography and are tested in actual hardware. We also provide the average power and energy per bit of our implementations at 40 MHz. Results indicate that SpoC has the smallest area and power, while Ascon has the highest throughput-to-area (TPA) ratio

Security of Ubiquitous Computing Systems

The chapters in this open access book arise out of the EU Cost Action project Cryptacus, the objective of which was to improve and adapt existent cryptanalysis methodologies and tools to the ubiquitous computing framework. The cryptanalysis implemented lies along four axes: cryptographic models, cryptanalysis of building blocks, hardware and software security engineering, and security assessment of real-world systems. The authors are top-class researchers in security and cryptography, and the contributions are of value to researchers and practitioners in these domains. This book is open access under a CC BY license

Efficient Linkable Ring Signatures: New Framework and Post-Quantum Instantiations

In this paper, we introduce a new framework for constructing linkable ring signatures (LRS). Our framework is based purely on signatures of knowledge (SoK) which allows one to issue signatures on behalf of any NP-statement using the corresponding witness. Our framework enjoys the following advantages: (1) the security of the resulting LRS depends only on the security of the underlying SoK; (2) the resulting LRS naturally supports online/offline signing (resp. verification), where the output of the offline signing (resp. verification) can be re-used across signatures of the same ring. For a ring size $n$, our framework requires an SoK of the NP statement with size $\log n$. To instantiate our framework, we adapt the well-known post-quantum secure non-interactive argument of knowledge (NIAoK), ethSTARK, into an SoK. This SoK is inherently post-quantum secure and has a signature size poly-logarithmic in the size of the NP statement. Thus, our resulting LRS has a signature size of $O(\text{polylog}(\log n))$. By comparison, existing post-quantum ring signatures, regardless of linkability considerations, have signature sizes of $O(\log n)$ at best. Furthermore, leveraging online/offline verification, part of the verification of signatures on the same ring can be shared, resulting in a state-of-the-art amortized verification cost of $O(\text{polylog}(\log n))$. Our LRS also performs favourably against existing schemes in practical scenarios. Concretely, our scheme has the smallest signature size among all post-quantum linkable ring signatures with non-slanderability for ring size larger than $32$. In our experiment, at $128$-bit security and ring size of $1024$, our LRS has a size of $29$KB, and an amortized verification cost of $0.3$ ms, surpassing the state-of-the-art by a significant margin. Even without considering amortization, the verification time for a single signature is $128$ ms, comparable to those featuring linear signature size. A similar performance advantage can also be seen at signing. Furthermore, our LRS has extremely short public keys ($32$ bytes), while public keys of existing constructions are in the order of kilobytes

Security of Ubiquitous Computing Systems

The chapters in this open access book arise out of the EU Cost Action project Cryptacus, the objective of which was to improve and adapt existent cryptanalysis methodologies and tools to the ubiquitous computing framework. The cryptanalysis implemented lies along four axes: cryptographic models, cryptanalysis of building blocks, hardware and software security engineering, and security assessment of real-world systems. The authors are top-class researchers in security and cryptography, and the contributions are of value to researchers and practitioners in these domains. This book is open access under a CC BY license

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Multimodal sentiment analysis in real-life videos

This thesis extends the emerging field of multimodal sentiment analysis of real-life videos, taking two components into consideration: the emotion and the emotion's target. The emotion component of media is traditionally represented as a segment-based intensity model of emotion classes. This representation is replaced here by a value- and time-continuous view. Adjacent research fields, such as affective computing, have largely neglected the linguistic information available from automatic transcripts of audio-video material. As is demonstrated here, this text modality is well-suited for time- and value-continuous prediction. Moreover, source-specific problems, such as trustworthiness, have been largely unexplored so far. This work examines perceived trustworthiness of the source, and its quantification, in user-generated video data and presents a possible modelling path. Furthermore, the transfer between the continuous and discrete emotion representations is explored in order to summarise the emotional context at a segment level. The other component deals with the target of the emotion, for example, the topic the speaker is addressing. Emotion targets in a video dataset can, as is shown here, be coherently extracted based on automatic transcripts without limiting a priori parameters, such as the expected number of targets. Furthermore, alternatives to purely linguistic investigation in predicting targets, such as knowledge-bases and multimodal systems, are investigated. A new dataset is designed for this investigation, and, in conjunction with proposed novel deep neural networks, extensive experiments are conducted to explore the components described above. The developed systems show robust prediction results and demonstrate strengths of the respective modalities, feature sets, and modelling techniques. Finally, foundations are laid for cross-modal information prediction systems with applications to the correction of corrupted in-the-wild signals from real-life videos

Intelligent Agents for Active Malware Analysis

The main contribution of this thesis is to give a novel perspective on Active Malware Analysis modeled as a decision making process between intelligent agents. We propose solutions aimed at extracting the behaviors of malware agents with advanced Artificial Intelligence techniques. In particular, we devise novel action selection strategies for the analyzer agents that allow to analyze malware by selecting sequences of triggering actions aimed at maximizing the information acquired. The goal is to create informative models representing the behaviors of the malware agents observed while interacting with them during the analysis process. Such models can then be used to effectively compare a malware against others and to correctly identify the malware famil