Biblio

Traditional encryption algorithms are not suitable for modern mass speech situations, while some low-dimensional chaotic encryption algorithms are simple and easy to implement, but their key space often small, leading to poor security, so there is still a lot of room for improvement. Aiming at these problems, this paper proposes a new type of four-dimensional chaotic system and applies it to speech encryption. Simulation results show that the encryption scheme in this paper has higher key space and security, which can achieve the speech encryption goal.

The readout of large pixellated detectors with good spectroscopic quality represents a challenge for both front-end and back-end electronics. The TRISTAN project for the search of the Sterile neutrino in the keV-scale, envisions the operation of 21 detection modules equipped with a monolithic array of 166 SDDs each, for β-decay spectroscopy in the KATRIN experiment's spectrometer. Since the trace of the sterile neutrino existence would manifest as a kink of \textbackslashtextless; 1ppm in the continuous spectrum, high accuracy in the acquisition is required. Within this framework, we present the design of a multichannel scalable analog processing and DAQ system named Kerberos, aimed to provide a simple and low-cost multichannel readout option in the early phase of the TRISTAN detector development. It is based on three 16-channel integrated programmable analog pulse processors (SFERA ASICs), high linearity ADCs, and an FPGA. The platform is able to acquire data from up to 48 pixels in parallel, providing also different readout and multiplexing strategies. The use of an analog ASIC-based solution instead of a Digital Pulse Processor, represents a viable and scalable processing solution at the price of slightly limited versatility and count rate.

The prevalence of social botnets has increased public distrust of social media networks. Current methods exist for detecting bot activity on Twitter, Reddit, Facebook, and other social media platforms. Most of these detection methods rely upon observing user behavior for a period of time. Unfortunately, the behavior observation period allows time for a botnet to successfully propagate one or many posts before removal. In this paper, we model the post propagation patterns of normal users and social botnets. We prove that a botnet may exploit deterministic propagation actions to elevate a post even with a small botnet population. We propose a probabilistic model which can limit the impact of social media botnets until they can be detected and removed. While our approach maintains expected results for non-coordinated activity, coordinated botnets will be detected before propagation with high probability.

The transition from high school to university is an exciting time for students including many new challenges. Particularly in the field of science, technology, engineering, and mathematics, the university dropout rate may reach up to 40%. The studies of physics rely on many abstract concepts and quantities that are not directly visible like energy or heat. We developed a mixed reality application for education, which augments the thermal conduction of metal by overlaying a representation of temperature as false-color visualization directly onto the object. This real-time augmentation avoids attention split and overcomes the perception gap by amplifying the human eye. Augmented and Virtual Reality environments allow students to perform experiments that were impossible to conduct for security or financial reasons. With the application, we try to foster a deeper understanding of the learning material and higher engagement during the studies.

Nowadays the massive amount of data is produced from different sources and lots of applications are processing these data to discover insights. Sometimes we may get unexpected results from these applications and it is not feasible to trace back to the data origin manually to find the source of errors. To avoid this problem, data must be accompanied by the context of how they are processed and analyzed. Especially, data-intensive applications like e-Science always require transparency and therefore, we need to understand how data has been processed and transformed. In this paper, we propose mathematical formulation and implementation of query inversion techniques to trace the provenance of data in a relational database management system (RDBMS). We build mathematical formulations of inverse queries for most of the relational algebra operations and show the formula for join operations in this paper. We, then, implement these formulas of inversion techniques and the experiment shows that our proposed inverse queries can successfully trace back to original data i.e. finding data provenance.

In this paper we discuss a simple and inexpensive method to introduce students to Newton's law of cooling using only their smartphones, according to the Bring-Your-Own-Device philosophy. A popular experiment in basic thermodynamics, both at a high-school and at University level, is the determination of the specific heat of solids and liquids using a water calorimeter, resourcing in many cases to a mercury thermometer. With our approach the analogical instrument is quickly turned into a digital device by analyzing the movement of the mercury with a video tracker. Thus, using very simple labware and the students' smartphones or tablets, it is possible to observe the decay behavior of the temperature of a liquid left to cool at room temperature. The dependence of the time constant with the mass and surface of the liquid can be easily probed, and the results of the different groups in the classroom can be brought together to observe the linear dependence1.

The chaotic system and cryptography have some common features. Due to the close relationship between chaotic system and cryptosystem, researchers try to combine the chaotic system with cryptosystem. In this study, security analysis of an encryption algorithm which aims to encrypt the data with ECG signals and chaotic functions was performed using the Logistic map in text encryption and Henon map in image encryption. In the proposed algorithm, text and image data can be encrypted at the same time. In addition, ECG signals are used to determine the initial conditions and control parameters of the chaotic functions used in the algorithm to personalize of the encryption algorithm. In this cryptanalysis study, the inadequacy of the mentioned process and the weaknesses of the proposed method have been determined. Encryption algorithm has not sufficient capacity to provide necessary security level of key space and secret key can be obtained with only one plaintext/ciphertext pair with chosen-plaintext attack.

We consider several challenging problems in complex networks (communication, control, social, economic, biological, hybrid) as problems in cooperative multi-agent systems. We describe a general model for cooperative multi-agent systems that involves several interacting dynamic multigraphs and identify three fundamental research challenges underlying these systems from a network science perspective. We show that the framework of constrained coalitional network games captures in a fundamental way the basic tradeoff of benefits vs. cost of collaboration, in multi-agent systems, and demonstrate that it can explain network formation and the emergence or not of collaboration. Multi-metric problems in such networks are analyzed via a novel multiple partially ordered semirings approach. We investigate the interrelationship between the collaboration and communication multigraphs in cooperative swarms and the role of the communication topology, among the collaborating agents, in improving the performance of distributed task execution. Expander graphs emerge as efficient communication topologies for collaborative control. We relate these models and approaches to statistical physics.

Physical attacks against cryptographic devices typically take advantage of information leakage (e.g., side-channels attacks) or erroneous computations (e.g., fault injection attacks). Preventing or detecting these attacks has become a challenging task in modern cryptographic research. In this context intrinsic physical properties of integrated circuits, such as Physical(ly) Unclonable Functions (PUFs), can be used to complement classical cryptographic constructions, and to enhance the security of cryptographic devices. PUFs have recently been proposed for various applications, including anti-counterfeiting schemes, key generation algorithms, and in the design of block ciphers. However, currently only rudimentary security models for PUFs exist, limiting the confidence in the security claims of PUF-based security primitives. A useful model should at the same time (i) define the security properties of PUFs abstractly and naturally, allowing to design and formally analyze PUF-based security solutions, and (ii) provide practical quantification tools allowing engineers to evaluate PUF instantiations. In this paper, we present a formal foundation for security primitives based on PUFs. Our approach requires as little as possible from the physics and focuses more on the main properties at the heart of most published works on PUFs: robustness (generation of stable answers), unclonability (not provided by algorithmic solutions), and unpredictability. We first formally define these properties and then show that they can be achieved by previously introduced PUF instantiations. We stress that such a consolidating work allows for a meaningful security analysis of security primitives taking advantage of physical properties, becoming increasingly important in the development of the next generation secure information systems.