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Lambda-Reservoir Computing

UCLA researchers in the Department of Electrical and Computer Engineering have developed a Spectral Reservoir Computer that processes data using nonlinear optical interactions.

Techniques for Creation and Insertion of Test Points for Malicious Circuitry Detection

Researchers led by Dr. Potkonjak from the UCLA Department of Computer Science have developed a technique to detect hardware Trojans in integrated circuits.

System For Eliminating Clickbaiters On Visual-Centric Social Media

Researchers from the Department of Communication at UCLA have developed a system for identifying and eliminating clickbait from social media.

Privacy Preserving Stream Analytics

UCLA researchers in the Department of Computer Science have developed a new privacy preserving mechanism for stream analytics.

A New Signal Analysis Method For Angle Of Arrival Estimation, Tracking, Localization, And Head Counting With Rf Signals

A new framework that enables the estimation of the AoA of signal paths from signal sources (both active transmitters and passive objects), with only signal magnitude measurements.

DeepSign: Digital Rights Management in Deep Learning Models

As society becomes more and more complicated, we have also developed ways to analyze and solve some of these complexities via the convergence of the fields of artificial intelligence, cognitive science and neuroscience. What has emerged is the development of machine learning, which allows computers to improve automatically through experience. Thus, developers working on artificial intelligence (AI) systems have come forth to align AI with machine-learning algorithms to cover a wide variety of machine-learning problems. The most advanced of these are called supervised learning methods which form their predictions via learned mapping, which can include decision trees, logistic regression, support vector machines, neural networks and Bayesian classifiers. More recently, deep networks have emerged as multilayer networks involved in a number of applications, such as computer vision and speech recognition. A practical concern in the rush to adopt AI as a service is the capability to perform model protection: AI models are usually trained by allocating significant computational resources to process massive amounts of training data. The built models are therefore considered as the owner’s intellectual property (IP) and need to be protected to preserve the competitive advantage.

Librando: Transparent Code Randomization For Just-In-Time Compilers

Just-in-time compilation is a method of executing computer code which, while boasting superior execution times, is prone to security exploits. UCI researchers have developed librando, a software framework for increasing security for just-in-time compilers, ensuring that generated program code is not predictable to an attacker.

Value-Based Information Flow Tracking in Software Packages

A collaboration between UCLA and Rutgers have developed a novel information flow tracking technique to detect potential data leaks in mobile devices.

A Technique For Securing Key-Value Stores Against Malicious Servers

The advent of the Internet of Things (IoT) has drastically increased the potential scale and scope of destruction hackers can cause. Cloud servers now control and monitor devices such as cars, smart home controls, fitness trackers, medical monitoring systems. These cloud-based devices are at risk, however, in that if they become compromised, third parties could gain full control of all devices and stored information associated with that server. UCI researchers have developed the FIDELIUS system, a technique for secure communication and information storage.

Defending Side Channel Attack In Additive Layer Manufacturing Systems

Additive layer manufacturing systems, also known as 3D printers, are a powerful tool for manufacturers in both rapid prototyping stage and full-scale production. Sensitive intellectual property is carried in the electronic information of the design files utilized by 3D printers. However, the physical characteristics of the machine in operation, including power, temperature, sounds, and motion can also reveal sensitive information that could be used to reverse-engineer a product. The inventors at UCI have demonstrated the threat posed by such side-channel attacks, and have developed countermeasures that obscure information which would otherwise be exposed during printer operation.

Mechanical Process For Creating Particles Using Two Plates

UCLA researchers in the Department of Chemistry and Biochemistry & Physics and Astronomy have developed a novel method to lithograph two polished solid surfaces by using a simple mechanical alignment jig with piezoelectric control and a method of pressing them together and solidifying a material.

Synthesis Technique to Achieve High-Anisotropy FeNi

Researchers at the University of California, Davis have developed an innovative synthesis approach to achieve high anisotropy L1 FeNi by combining physical vapor deposition and a high speed rapid thermal annealing (RTA).

Detecting Malicious Http Users Using The Community Structure Property In Interaction Graph

Background: Wealth is being transferred into the hands of malicious cybercriminals with an estimated annual global cost of $445B from Intellectual Property (IP) theft. The security industry needs to rapidly progress to keep up with the ever more innovating cybercrimes. Due to the inadequacy of traditional security scanning software, we need a better method that is proficient in detecting perpetrators before they gain access to confidential information.  Brief Description: Malicious HTTP scanners scan for vulnerable websites with easy access into private information. UCR researchers created Scanner Hunter, a reconnaissance tool that will enable them to take preemptive measures before actual infiltration occurs. The tool has an innovative approach of filtering HTTP requests and tagging them as malignant or benign. Their dynamic methodology and algorithm successfully achieves its functions with 96.5% accuracy while virtually eliminating all false-positives.

Facial Recognition & Vehicle Logo Super-Resolution System

Background: The video surveillance market is projected to grow annually at 17% and reach $42B by 2020. Video surveillance is a popular tool to track and monitor movement of people and vehicles to provide protection and discover information for investigations. Current technologies are competent in capturing images but not with high definition. Therefore, a more advanced security system that is smarter and multidimensional is needed.  Brief Description: UCR Researchers have developed a novel method and system for unified face representation for individual recognition in surveillance videos along with vehicle recognition. They extracted facial images from a video, generated an emotion avatar image (EAI) and computed features using their innovative algorithms. Low-resolution vehicle images can also be enhanced by using their super-resolution algorithms to produce high-resolution images. Existing technologies can only take frontal images but this new technology can handle out-of-plane, rotated images.

Microfabrication of High Quality 3-D Structures Using Wafer-Level Glassblowing of Fused Quartz and Ultra Low Expansion Glasses

Micro-glassblowing MEMS fabrication process for low expansion and low loss materials

Referenceless Clock Recovery Circuit with Wide Frequency Acquisition Range

The technology is a circuit that recovers a full-rate clock signal from a random digital data signal. Properties include: achieves frequency and phase locking in a single loop and a wide acquisition range.

Cacophony: A Framework for Next Generation Software Sensors

The technology is a software architecture for providing robust predictions for software systems from cloud sourced data points. Properties include:the ability to “wrap” existing software sensors with additional services. The technology is used by executing software on a cloud based server and manipulating data points from user update systems, such as Waze, and provide predictive services around these data points.

Cost-Efficient Repair For Cloud Storage Systems Using Progressive Engagement

The technology is a coding process which facilitates efficient data failure recovery in cloud storage systems.It features greater flexibility in choosing subset of storage nodes for recovery and reduces amount of data that must be transferred upon recovery.

Sensor-Assisted Facial Authentication System For Smartphones

Researchers at the University of California, Davis have developed a method using standard mobile device sensors assisting with facial authentication to overcome the limitations faced by current methods.

Dynamic Proof of Retrievability from Cloud Storage

Data storage outsourcing has become one of the most popular applications of cloud computing, offering benefits such as economies of scale, flexible accessibility, efficiency, and allowing companies to focus on their primary business activities. Due to the increase in percentage of services conducted online and number of mobile internet connections, demand for data storage continues to grow. Customers in this industry are primarily concerned with authenticated storage and data retrievability. Although many efficient proof of retrievability technologies have been developed for static data, only two dynamic technologies exist. However, both are too expensive to implement in practice due to the fact that they require a high level of bandwidth. To address this problem, researchers have developed a dynamic proof of reliability scheme that requires 300 times less bandwidth than currently available technologies. This innovative technology makes dynamic proof retrievability of data practical and efficient, and thus attractive for the industry implementation. This technology gives clients of cloud storage providers assurance that their data has not been modified and that no data loss has occurred.

Multi-level Information Security in Information Flow Tracking

Information flow tracking (IFT) is a frequently used technique for enforcing IFC. IFT associates a label with data, and monitors the propagation of this label through the system to check if sensitive data leaks to an unclassified domain or if integrity-critical components are affected by untrusted data. With more functional units, such as security primitives, being built into hardware to meet performance and power constraints, it is required that embedded security be enforced from the underlying hardware up. In this process, hardware assisted IFT methods have been deployed to capture harmful flows of information including those through hardware specific timing channels. Implicit flows resulting from these timing channels have been shown to leak secret keys in stateful elements such as caches and branch predictors. In addition, such timing flows can cause violations in real-time constraints, hindering real-time operations of a system or even rendering the critical system useless. Further, these channels are so hard to detect that they are usually identified only after operational critical security policies have been violated.Critical embedded systems such as those found in the military, industrial infrastructures and medical devices all require strict guarantees on information flow security because of the extremely high cost of a failure. These systems require rigorous design and testing to ensure that untrusted information never affects trusted computation or that secret information never leaks to unclassified domains. The requirements, for both integrity and confidentiality, can be captured by the formal model of information flow security.

Eliminating Timing Information Flows in a Mix-trusted System-on-Chip

Modern computing systems continue to find themselves in control of applications which we rely on for our personal health and safety. These systems which require high-assurance have a very high cost of failure. In order to build such a system with complete security, it must be built with a secure computing foundation. Creating such a secure hardware foundation is non-trivial for a number of reasons. One of which is due to the use of third-party intellectual property cores to reduce both the cost and design time of modern system-on-chips (SOC). Ensuring the integrity of trusted cores in these systems becomes difficult since the behavior of the third party cores is undefined.

HCLR: A Hybrid Cross-Layer Routing Protocol For MANETs

Hybrid Routing protocol for more intelligent routing decisions on mobile ad-hoc networks (MANETs).It features leveragesdproactive and reactive routing schemes, a routing table generated globally using existing proactive routing protocol, and locally performed route optimization using on-demand reactive routing protocol.

Method for Malware Detection and Classification using Image Processing Techniques

A novel method for visualizing and classifying malware using image processing techniques, applicable to malware detection and anti-virus software.

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