A Challenge Obfuscating Interface for Arbiter PUF Variants against Machine Learning Attacks

Physical unclonable functions are promising candidates as security primitives for resource-constrained IoT devices . Arbiter PUFs (APUFs) are a group of delay-based PUFs which are highly lightweight in resource requirements but suffer from high susceptibility to machine learning attacks . The challenge input interface incurs low resource overhead and improves PUFs’ resistance against machine-learning attacks .…

DIALED Data Integrity Attestation for Low end Embedded Devices

The central challenge is how to securelydetect software exploits with minimal overhead . DIALED works in tandem with a companion CFA scheme to detect all (currently known) types of runtime software exploits at low-cost . Such attacks exploit softwarevulnerabilities to corrupt intermediate computation results stored in datamemory, changing neither the program code nor its control flow .…

An Offline Delegatable Cryptocurrency System

Offline delegation offers an efficient way to exchange coins . However, in such an approach, the coins thathave been delegated confront the risk of being spent twice . In DelegaCoin, an owner can delegate his coinsthrough offline-transactions without interacting with the blockchain network .…

CNN vs ELM for Image Based Malware Classification

Research in the field of malware classification often relies on machinelearning models that are trained on high-level features, such as opcodes,function calls, and control flow graphs . Extracting such features is costly, since disassembly or code execution is generally required .…

RDMA is Turing complete we just did not know it yet

Remote Direct Memory Access(RDMA) NICs (RNICs) are one such device, allowing applications to offloadremote memory accesses . RDMA still requires CPU intervention for complex offloads, beyond simple remote memory access . RedN can outperform one and two-sided RDMA implementations by up to 3x and 7.8x for key-value get operations and .performance…

A Multi Tenant Framework for Cloud Container Services

Virtual-Cluster is a new multi-tenant framework that extends Kubernetes . VirtualCluster provides both control plane and data plane isolations while sharing the underlying compute resources among tenants . The new framework preserves API compatibility by avoiding modifying the KuberNETes core components .…

SCHeMa Scheduling Scientific Containers on a Cluster of Heterogeneous Machines

SCHeMa is an open-source platform that facilitates the execution and reproducibility of computational analysis on heterogeneous clusters . It uses containerization, experiment packaging, workflow management, and machine learning technologies . SCMa is the latest open source platform to combine these technologies with machine learning and containerization to facilitate the work of scientists in this direction .…

Ontology Based Recommendation of Editorial Products

Smart Book Recommender (SBR) was developed by The Open University in collaboration with Springer Nature . It supports their Computer Science editorial team in selecting products to market at specific venues . SBR recommends books, journals, and conference proceedings relevant to a conference by taking advantage of a semantically enhanced representation of about 27K editorial products .…

Single Sample Prophet Inequalities Revisited

The study of the prophet inequality problem in the limited information regimewas initiated by Azar et al. [SODA’14] in the pursuit of prior-independentposted-price mechanisms . As they show, $O(1)$-competitive policies areachievable using only a single sample from the distribution of each agent .…

On the Uniform Distribution of Regular Expressions

In this paper we study a set of expressions that avoid a givenabsorbing pattern . It is shown that, although this set is significantly smallerthan the standard one, the asymptotic average estimates for the size of the . automaton for these expressions does not differ from the standardcase .…

Failure Tolerant Contract Based Design of an Automated Valet Parking System using a Directive Response Architecture

The architecture is demonstrated on amodular automated valet parking (AVP) system . The contracts for the different components in the AVP system are explicitly defined, implemented, and validated against a Python implementation . This paper aims to extend the contract-based design approach using a directive-response architecture to reactivity to failure scenarios .…

Deep Implicit Moving Least Squares Functions for 3D Reconstruction

Point set is a flexible and lightweight representation widely used for 3D deep learning . However, their discrete nature prevents them from representing continuous and fine geometry, posing a major issue for learning-based shapegeneration . In this work, we turn discrete point sets into smooth surfaces by introducing the well-known implicit moving least-squares (IMLS) surfaceformulation, which naturally defines locally implicit functions on point sets .…

Towards Efficient Auctions in an Auto bidding World

Auto-bidding has become one of the main options for bidding in online advertisements . Advertisers only need to specify high-level objectives and leave the task of bidding to auto-bidders . In this paper, we propose a family of auctions with boosts to improve welfare in auto-bid environments with both return on ad spend constraints and budget constraints .…

A relaxed inertial forward backward forward algorithm for Stochastic Generalized Nash equilibrium seeking

In this paper we propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation andinertial effects . Our work is inspired by recent deterministic operatorsplitting methods, designed for solving structured monotone inclusion problems . The algorithm is derived from a forward-backward-forward scheme for solvingstructured monotones problems featuring a Lipschitz continuous andmonotone game operator .…

Online Market Equilibrium with Application to Fair Division

We focus on the case of online Fishermarkets: individuals have linear, additive utility and items drawn from adistribution arrive one at a time in an online setting . We show that our dynamics can also be used as an online item-allocation rule such that the time-averagedallocations and utilities converge to those of a corresponding static Fishermarket .…

How to Motivate and Engage Generation Clash of Clans at Work Emergent Properties of Business Gamification Elements in the Digital Economy

Average employee spends eleven cumulative years of their life at work . Less than one third of the workforce are actually engaged in their duties throughout their career . Using behavioural concepts derived from video games, and applying game designelements in business systems to motivate employees in the digital economy, is aconcept which has come to be recognised as Business Gamification .…

Hierarchical Hyperedge Embedding based Representation Learning for Group Recommendation

In this work, we study group recommendation in a particular scenario, namelyOccasional Group Recommendation (OGR) Most existing works have addressed OGR by aggregating group members’ personal preferences to learn the grouprepresentation . We propose to leverage the user-user interactions to alleviatethe sparsity issue of user-item interactions, and design a GNN-basedrepresentation learning network to enhance the learning of individuals’preferences from their friends’ preferences .…

Web Mining for Estimating Regulatory Blockchain Readiness

The regulatory framework of cryptocurrencies (and, in general, blockchaintokens) is of paramount importance . This framework drives nearly all key decisions in the respective business areas . In this work, a computational model is proposed for quantitatively estimating the regulatory stance of countries with respect to cryptocurrencies .…

Quantized Corrupted Sensing with Random Dithering

Corrupted sensing concerns the problem of recovering a high-dimensionalstructured signal from a collection of measurements that are contaminated by structured corruption and unstructured noise . In practical applications of digital signalprocessing, the quantization process is inevitable, which often leads tonon-linear measurements .…

A Message Passing based Adaptive PDA Algorithm for Robust Radio based Localization and Tracking

We present a message passing algorithm for localization and tracking inmultipath-prone environments . The proposed adaptive probabilistic data association algorithminfers the position of a mobile agent using multiple anchors . The algorithm adapts in an online manner to both, the time-varyingsignal-to-noise-ratio and line-of-sight (LOS) existence probability of eachanchor .…

Energy Efficient Resource Allocation in Massive MIMO NOMA Networks with Wireless Power Transfer A Distributed ADMM Approach

In multicell massive multiple-input multiple- input multiple-output (MIMO) non-orthogonalmultiple access (NOMA) networks, base stations (BSs) with multiple antennas deliver their radio frequency energy in the downlink, and Internet-of-Things(IoT) devices use their harvested energy to support uplink data transmission . To maximize theEE of the network, we propose a novel joint power, time, antenna selection, andsubcarrier resource allocation scheme .…

Homomorphic encoders of profinite abelian groups

In this paper we investigate the structure of order controllable subgroups . We say that asubgroup $G_i :i\in\N\}$ is a family of finite Abelian groups . If $G$ is an ordercontrollable, shift invariant, group code over an abelian group $H$ then $G#possesses a canonical generator set .…

Analysis of QoS in Heterogeneous Networks with Clustered Deployment and Caching Aware Capacity Allocation

In cellular networks, the densification of connected devices and basestations engender the ever-growing traffic intensity . We propose the allocation ofdownlink data transmission capacity according to the cases of requestedcontents which are either cached or non-cached in nearby nodes . The throughput and delay of the allocationsystem are derived based on the approximated sojourn time of the DiscriminatoryProcessor Sharing (DPS) queue .…