ANÁLISE E APLICAÇÃO DE ESTRUTURAS DE SUFIXOS NA RESOLUÇÃO DO STRING MATCHING

String Matching é o problema que busca responder a seguinte pergunta: “É possível encontrar determinado padrão dentro de um texto?”. É um problema amplamente estudado na Ciência da Computação e também na Biologia Computacional, devido à existência de suas diferentes modificações em ferramentas de pesquisa e também no processamento de cadeias de DNA. Já existem algoritmos que alcançaram a solução ótima para responder a pergunta do problema, entretanto tais soluções não possuem a mesma eficiência nas extensões e variações do problema. Dessa forma, diversas pesquisas tem estudado estruturas de dados relativas aos sufixos do texto para alcançar soluções que sejam capazes de resolver variações complexas do string matching. O presente trabalho realiza um estudo e análise aprofundada sobre a eficiência de dessas estruturas: a árvore de sufixos e o autômato de sufixos. Algoritmos clássicos também são abordados e comparados às estruturas enquanto o trabalho é discorrido. As análises seguem critérios estatísticos, tempos de execução e complexidade de algoritmos para obter maior grau de confiança nos resultados

Parallelization of a software based intrusion detection system - Snort

Computer networks are already ubiquitous in people’s lives and work and network security is becoming a critical part. A simple firewall, which can only scan the bottom four OSI layers, cannot satisfy all security requirements. An intrusion detection system (IDS) with deep packet inspection, which can filter all seven OSI layers, is becoming necessary for more and more networks. However, the processing throughputs of the IDSs are far behind the current network speed. People have begun to improve the performance of the IDSs by implementing them on different hardware platforms, such as Field-Programmable Gate Array (FPGA) or some special network processors. Nevertheless, all of these options are either less flexible or more expensive to deploy. This research focuses on some possibilities of implementing a parallelized IDS on a general computer environment based on Snort, which is the most popular open-source IDS at the moment. In this thesis, some possible methods have been analyzed for the parallelization of the pattern-matching engine based on a multicore computer. However, owing to the small granularity of the network packets, the pattern-matching engine of Snort is unsuitable for parallelization. In addition, a pipelined structure of Snort has been implemented and analyzed. The universal packet capture API - LibPCAP has been modified for a new feature, which can capture a packet directly to an external buffer. Then, the performance of the pipelined Snort can have an improvement up to 60% on an Intel i7 multicore computer for jumbo frames. A primary limitation is on the memory bandwidth. With a higher bandwidth, the performance of the parallelization can be further improved

Identification of Small Endogenous Viral Elements within Host Genomes

A parallel string matching software architecture has been developed (incorporating several algorithms) to identify small genetic sequences in large genomes. Endogenous viral elements (EVEs) are sequences originating in the genomes of viruses that have become integrated into the chromosomes of sperm or egg cells of infected hosts, and passed to subsequent generations. EVEs have been identified in all seven classes of viruses and in the species of all kingdoms of life. Viruses from groups V and VI are considered in this thesis, including HIV and Ebola, within host genomes ranging from bacteria to humans. This database of small endogenous viral elements (SEVEs) contains homology between the viruses and every chromosome of the ten multicellular organisms in this study, including human, chimpanzee, gorilla, mouse, fruitbat, nematode, and thale cress

LIPIcs, Volume 244, ESA 2022, Complete Volume

LIPIcs, Volume 244, ESA 2022, Complete Volum

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here