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Semi-supervised learning (SSL) algorithms have had great success in recent years in limited labeled data regimes. However, the current state-of-the-art SSL algorithms are computationally expensive and entail significant compute time and…
Virtual network services that span multiple data centers are important to support emerging data-intensive applications in fields such as bioinformatics and retail analytics. Successful virtual network service composition and maintenance…
Over the last years, security kernels have played a promising role in reshaping the landscape of platform security on today's ubiquitous embedded devices. Security kernels, such as separation kernels, enable constructing high-assurance…
Traditionally, Volt/VAR optimization (VVO) is performed in distribution networks through legacy devices such as on-load tap changers (OLTCs), voltage regulators (VRs), and capacitor banks. With the amendment in IEEE 1547 standard,…
Vehicular Ad hoc Networks (VANETs) are becoming a reality where secure communication is a prerequisite. Public key infrastructure (PKI) can be used to secure VANETs where an onboard tamper proof device (TPD) stores a number of encryption…
Embedded Network Stacks (ENS) enable low-resource devices to communicate with the outside world, facilitating the development of the Internet of Things and Cyber-Physical Systems. Some defects in ENS are thus high-severity cybersecurity…
Efficient embedding virtual clusters in physical network is a challenging problem. In this paper we consider a scenario where physical network has a structure of a balanced tree. This assumption is justified by many real- world…
Modern cloud computing platforms based on virtual machine monitors carry a variety of complex business that present many network security vulnerabilities. At present, the traditional architecture employs a number of security devices at…
Emerging ultra-low-power tiny scale computing devices in Cyber-Physical Systems %and Internet of Things (IoT) run on harvested energy, are intermittently powered, have limited computational capability, and perform sensing and actuation…
We study efficient algorithms for Sparse PCA in standard statistical models (spiked covariance in its Wishart form). Our goal is to achieve optimal recovery guarantees while being resilient to small perturbations. Despite a long history of…
Hardware accelerator for convolution neural network (CNNs) enables real time applications of artificial intelligence technology. However, most of the accelerators only support dense CNN computations or suffers complex control to support…
IoT devices particularly microcontrollers are challenged by their inherent limitations in processing capabilities, memory capacity, and energy conservation. Securing communication within IoT networks is further complicated by the…
As the number of Common Vulnerabilities and Exposures (CVE) continues to grow exponentially, security teams face increasingly difficult decisions about prioritization. Current approaches using Common Vulnerability Scoring System (CVSS)…
Vector Perturbation Precoding (VPP) can speed up downlink data transmissions in Large and Massive Multi-User MIMO systems but is known to be NP-hard. While there are several algorithms in the literature for VPP under total power constraint,…
The reliable deployment of neural networks in control systems requires rigorous robustness guarantees. In this paper, we obtain tight robustness certificates over convex attack sets for min-max representations of ReLU neural networks by…
We propose the first fast and certifiable algorithm for the registration of two sets of 3D points in the presence of large amounts of outlier correspondences. We first reformulate the registration problem using a Truncated Least Squares…
There has recently been a flood of interest in potential new applications of blockchains, as well as proposals for more generic designs called public ledgers. Most of the novel proposals have been in the financial sector. However, the…
A new era in wireless sensor network technology has been ushered in through the introduction of multimedia sensor networks, which has a major bottleneck in the form of network congestion. Congestion occurs when resources are in high demand…
The main issue related to Software-Defined Network emulators is how to replicate real behavior in experiments. Mininet and others SDN emulators have an architecture that limits both the scope of experiments and the fidelity of networking…
While neural networks have achieved high performance in different learning tasks, their accuracy drops significantly in the presence of small adversarial perturbations to inputs. Defenses based on regularization and adversarial training are…