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In this paper, we investigate the security of SNOW-V, demonstrating two guess-and-determine (GnD) attacks against the full version with complexities 2384 and 2378, respectively, and one distinguishing attack against a reduced variant with complexity 2303 . Our GnD attacks use enumeration with recursion to explore valid guessing paths, and try to truncate as many invalid guessing paths as possible
Traditional network architecture design of Low Power Wide Area Networks (LPWAN) is incapable of dynamically scaling resources based on the served traffic and requires manual procedures for network capacity upgrades. Today's over-provisioning approach based on proprietary hardware (HW) would not be cost and energy efficient to cope with the ever-increasing scale of Internet of Things (IoT) devices
Cryptosystems based on the learning with errors (LWE) problem are assigned a security level that relates to the cost of generic algorithms for solving the LWE problem. This includes at least the so-called primal and dual lattice attacks. In this paper, we present an improvement of the dual lattice attack using an idea that can be traced back to work by Bleichenbacher. We present an improved distin
We report studies of charge-independent (CI) and charge-dependent (CD)two-particle differential number correlation functions, R2 (Δη,Δ℘), and transverse momentum correlation functions, P2 (Δη,Δ℘) of charged particles produced in Pb-Pb collisions at the LHC centre-of-mass energy √sNN= 2.76 TeV with the UrQMD, AMPT and EPOS models. Model predictions for R2 and P2 correlation functions are presented
Low-power wearable technologies offer a promising solution to pervasive epilepsy monitoring by removing the constraints concerning time and location, on one hand, and fulfilling long-term tracking, on the other hand. In the case of epileptic seizures, as the attacks infrequently occur, using an anomaly detection approach reduces the need to record long hours of data for each patient before detecti
Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automatic detection of epileptic seizures can substantially improve the patient's quality of life. To achieve a high-quality model, we have to collect d
A system we denote Seg2Pose is presented which converts pixel coordinate tracks, represented by instance segmentation masks across multiple video frames, into world coordinate pose tracks, for road users seen by static surveillance cameras. The road users are bound to a ground surface represented by a number of 3D points and does not necessarily have to be perfectly flat. The system works with one
Objective: To determine the burden of comorbidities in OA and their temporal relationships in the UK. Methods: The Clinical Practice Research Datalink (CPRD) GOLD was used to identify people with incident OA and age, gender and practice matched non-OA controls from UK primary care. Controls were assigned the same index date as matched cases (date of OA diagnosis). Associations between OA and 49 in
Industrial control systems (ICSs) are a significant part of industry and they play an important role in monitoring and controlling industrial processes. Traditionally, ICSs have been isolated from the Internet, and thereby secured from various Internet-based security threats. In recent years, since the cloud can provide huge advantages regarding storage and computing resources, industry has been m
In this paper we study structure from motion problems for 1D radial cameras. Under this model the projection of a 3D point is a line in the image plane going through the principal point, which makes the model invariant to radial distortion and changes in focal length. It can therefore effectively be applied to uncalibrated image collections without the need for explicit estimation of camera intrin
Low rank inducing penalties have been proven to successfully uncover fundamental structures considered in computer vision and machine learning; however, such methods generally lead to non-convex optimization problems. Since the resulting objective is non-convex one often resorts to using standard splitting schemes such as Alternating Direction Methods of Multipliers (ADMM), or other subgradient me
Software-Defined Networking (SDN) is a novel architectural model for cloud network infrastructure, improving resource utilization, scalability and administration. SDN deployments increasingly rely on virtual switches executing on commodity operating systems with large code bases, which are prime targets for adversaries attacking the network infrastructure. We describe and implement TruSDN, a frame
Multi-cell wireless systems usually encounter both intra-cell and inter-cell interference, which can be mitigated via coordinated multipoint (CoMP) transmission. Previous works on multi-cell analysis in the microwave band generally consider fully digital beamforming, requiring a complete radio-frequency chain behind each antenna. This is practically infeasible for millimeter-wave (mmWave) systems
This work demonstrates the sensitivity of lens antenna arrays operating at millimeter-wave (mmWave) frequencies. Considering a Rotman lens array in receive mode, our investigation focuses on its most imperative defect: aberration of electromagnetic (EM) energy. Aberration leads to spillover of electric fields to neighboring ports, reducing the lens' ability to focus the EM energy to a desired port
Lens–based massive multiple–input multiple–output (MIMO) systems have considerable potential to reduce signal processing cost at millimeter–wave frequencies. As a result, they are able to lower the effective channel dimension via beam selection, realized with a network of radio–frequency (RF) switches. However, lens arrays suffer from the inherent quantization of the beamspace, as well as errors d
In this paper, we take a fundamental look at the interference characteristics of a lens-based millimeter-wave (mmWave) multiuser multiple-input multiple-output system (MU-MIMO) system. We consider a hybrid architecture, implemented via a bank of radio-frequency (RF) switches which perform beam selection followed by low-complexity uplink maximum-ratio combining (MRC) at baseband. Considering a Rotm
We consider a massive multiple-input multiple- output system with minimum-mean-squared-error processing on the uplink. A novel analytical framework is proposed to approximate the instantaneous signal-to-interference-plus-noise- ratio (SINR) of an arbitrary user terminal, as well as, the system sum spectral efficiency. Unlike previous studies, our methodology considers spatially correlated Ricean f
Spatial correlation across an antenna array is known to be detrimental to the terminal signal-to- interference-plus-noise-ratio (SINR) and system spectral efficiency. For a downlink multiuser multiple-input multiple-output system (MU-MIMO), we show that the widely used, yet overly simplified, correlation models which generate fixed correlation patterns for all terminals tend to underestimate the s
