The pharmacophore kernel for virtual screening with support vector machines

We introduce a family of positive definite kernels specifically optimized for the manipulation of 3D structures of molecules with kernel methods. The kernels are based on the comparison of the three-points pharmacophores present in the 3D structures of molecul es, a set of molecular features known to be particularly relevant for virtual screening applications. We present a computationally demanding exact implementation of these kernels, as well as fast approximations related to the classical fingerprint-based approa ches. Experimental results suggest that this new approach outperforms state-of-the-art algorithms based on the 2D structure of mol ecules for the detection of inhibitors of several drug targets

Development of a generic fingerprint authentication framework

Estágio realizado na ALERT Life Sciences Computing, S. ATese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

EFFICIENT HARDWARE PRIMITIVES FOR SECURING LIGHTWEIGHT SYSTEMS

In the era of IoT and ubiquitous computing, the collection and communication of sensitive data is increasingly being handled by lightweight Integrated Circuits. Efficient hardware implementations of crytographic primitives for resource constrained applications have become critical, especially block ciphers which perform fundamental operations such as encryption, decryption, and even hashing. We study the efficiency of block ciphers under different implementation styles. For low latency applications that use unrolled block cipher implementations, we design a glitch filter to reduce energy consumption. For lightweight applications, we design a novel architecture for the widely used AES cipher. The design eliminates inefficiencies in data movement and clock activity, thereby significantly improving energy efficiency over state-of-the-art architectures. Apart from efficiency, vulnerability to implementation attacks are a concern, which we mitigate by our randomization capable lightweight AES architecture. We fabricate our designs in a commercial 16nm FinFET technology and present measured testchip data on energy consumption and side channel resistance. Finally, we address the problem of supply chain security by using image processing techniques to extract fingerprints from surface texture of plastic IC packages for IC authentication and counterfeit prevention. Collectively these works present efficient and cost effective solutions to secure lightweight systems

Network Interface Design for Network-on-Chip

In the culture of globalized integrated circuit (IC, a.k.a chip) production, the use of Intellectual Property (IP) cores, computer aided design tools (CAD) and testing services from un-trusted vendors are prevalent to reduce the time to market. Unfortunately, the globalized business model potentially creates opportunities for hardware tampering and modification from adversary, and this tampering is known as hardware Trojan (HT). Network-on-chip (NoC) has emerged as an efficient on-chip communication infrastructure. In this work, the security aspects of NoC network interface (NI), one of the most critical components in NoC will be investigated and presented. Particularly, the NI design, hardware attack models and countermeasures for NI in a NoC system are explored. An OCP compatible NI is implemented in an IBM0.18ìm CMOS technology. The synthesis results are presented and compared with existing literature. Second, comprehensive hardware attack models targeted for NI are presented from system level to circuit level. The impact of hardware Trojans on NoC functionality and performance are evaluated. Finally, a countermeasure method is proposed to address the hardware attacks in NIs

Designer cell signal processing circuits for biotechnology

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field