1,750 research outputs found
Towards secure message systems
Message systems, which transfer information from sender to recipient via communication networks, are indispensable to our modern society. The enormous user base of message systems and their critical role in information delivery make it the top priority to secure message systems. This dissertation focuses on securing the two most representative and dominant messages systems---e-mail and instant messaging (IM)---from two complementary aspects: defending against unwanted messages and ensuring reliable delivery of wanted messages.;To curtail unwanted messages and protect e-mail and instant messaging users, this dissertation proposes two mechanisms DBSpam and HoneyIM, which can effectively thwart e-mail spam laundering and foil malicious instant message spreading, respectively. DBSpam exploits the distinct characteristics of connection correlation and packet symmetry embedded in the behavior of spam laundering and utilizes a simple statistical method, Sequential Probability Ratio Test, to detect and break spam laundering activities inside a customer network in a timely manner. The experimental results demonstrate that DBSpam is effective in quickly and accurately capturing and suppressing e-mail spam laundering activities and is capable of coping with high speed network traffic. HoneyIM leverages the inherent characteristic of spreading of IM malware and applies the honey-pot technology to the detection of malicious instant messages. More specifically, HoneyIM uses decoy accounts in normal users\u27 contact lists as honey-pots to capture malicious messages sent by IM malware and suppresses the spread of malicious instant messages by performing network-wide blocking. The efficacy of HoneyIM has been validated through both simulations and real experiments.;To improve e-mail reliability, that is, prevent losses of wanted e-mail, this dissertation proposes a collaboration-based autonomous e-mail reputation system called CARE. CARE introduces inter-domain collaboration without central authority or third party and enables each e-mail service provider to independently build its reputation database, including frequently contacted and unacquainted sending domains, based on the local e-mail history and the information exchanged with other collaborating domains. The effectiveness of CARE on improving e-mail reliability has been validated through a number of experiments, including a comparison of two large e-mail log traces from two universities, a real experiment of DNS snooping on more than 36,000 domains, and extensive simulation experiments in a large-scale environment
The effects of security protocols on cybercrime at Ahmadu Bello University, Zaria, Nigeria.
Masters Degree. University of KwaZulu-Natal, Durban.The use of Information Communication Technology (ICT) within the educational
sector is increasing rapidly. University systems are becoming increasingly
dependent on computerized information systems (CIS) in order to carry out their
daily routine. Moreover, CIS no longer process staff records and financial data
only, as they once did. Nowadays, universities use CIS to assist in automating
the overall system. This automation includes the use of multiple databases, data
detail periodicity (i.e. gender, race/ethnicity, enrollment, degrees granted, and
program major), record identification (e.g. social security number ‘SSN’), linking
to other databases (i.e. linking unit record data with external databases such as
university and employment data).
The increasing demand and exposure to Internet resources and infrastructure by
individuals and universities have made IT infrastructure easy targets for
cybercriminals who employ sophisticated attacks such as Advanced Persistent
Threats, Distributed Denial of Service attacks and Botnets in order to steal
confidential data, identities of individuals and money. Hence, in order to stay in
business, universities realise that it is imperative to secure vital Information
Systems from easily being exploited by emerging and existing forms of
cybercrimes. This study was conducted to determine and evaluate the various
forms of cybercrimes and their consequences on the university network at
Ahmadu Bello University, Zaria. The study was also aimed at proposing means
of mitigating cybercrimes and their effects on the university network. Hence, an
exploratory research design supported by qualitative research approach was
used in this study. Staff of the Institute of Computing, Information and
Communication technology (ICICT) were interviewed. The findings of the study
present different security measures, and security tools that can be used to
effectively mitigate cybercrimes. It was found that social engineering, denial of
service attacks, website defacement were among the types of cybercrimes
occurring on the university network. It is therefore recommended that behavioural
approach in a form of motivation of staff behaviour, salary increases, and cash
incentive to reduce cybercrime perpetrated by these staff
How to accelerate your internet : a practical guide to bandwidth management and optimisation using open source software
xiii, 298 p. : ill. ; 24 cm.Libro ElectrónicoAccess to sufficient Internet bandwidth enables worldwide electronic collaboration, access to informational resources, rapid and effective communication, and grants membership to a global community. Therefore, bandwidth is probably the single most critical resource at the disposal of a modern organisation.
The goal of this book is to provide practical information on how to gain the largest possible benefit from your connection to the Internet. By applying the monitoring and optimisation techniques discussed here, the effectiveness of your network can be significantly improved
Prometheus: a generic e-commerce crawler for the study of business markets and other e-commerce problems
Dissertação de mestrado em Computer ScienceThe continuous social and economic development has led over time to an increase in consumption,
as well as greater demand from the consumer for better and cheaper products.
Hence, the selling price of a product assumes a fundamental role in the purchase decision
by the consumer. In this context, online stores must carefully analyse and define the best
price for each product, based on several factors such as production/acquisition cost, positioning
of the product (e.g. anchor product) and the competition companies strategy. The
work done by market analysts changed drastically over the last years.
As the number of Web sites increases exponentially, the number of E-commerce web
sites also prosperous. Web page classification becomes more important in fields like Web
mining and information retrieval. The traditional classifiers are usually hand-crafted and
non-adaptive, that makes them inappropriate to use in a broader context. We introduce an
ensemble of methods and the posterior study of its results to create a more generic and
modular crawler and scraper for detection and information extraction on E-commerce web
pages. The collected information may then be processed and used in the pricing decision.
This framework goes by the name Prometheus and has the goal of extracting knowledge
from E-commerce Web sites.
The process requires crawling an online store and gathering product pages. This implies
that given a web page the framework must be able to determine if it is a product page.
In order to achieve this we classify the pages in three categories: catalogue, product and
”spam”. The page classification stage was addressed based on the html text as well as on
the visual layout, featuring both traditional methods and Deep Learning approaches.
Once a set of product pages has been identified we proceed to the extraction of the pricing
information. This is not a trivial task due to the disparity of approaches to create a web
page. Furthermore, most product pages are dynamic in the sense that they are truly a page
for a family of related products. For instance, when visiting a shoe store, for a particular
model there are probably a number of sizes and colours available. Such a model may be
displayed in a single dynamic web page making it necessary for our framework to explore
all the relevant combinations. This process is called scraping and is the last stage of the
Prometheus framework.O contínuo desenvolvimento social e económico tem conduzido ao longo do tempo a um
aumento do consumo, assim como a uma maior exigência do consumidor por produtos
melhores e mais baratos. Naturalmente, o preço de venda de um produto assume um papel
fundamental na decisão de compra por parte de um consumidor. Nesse sentido, as lojas
online precisam de analisar e definir qual o melhor preço para cada produto, tendo como
base diversos fatores, tais como o custo de produção/venda, posicionamento do produto
(e.g. produto âncora) e as próprias estratégias das empresas concorrentes. O trabalho dos
analistas de mercado mudou drasticamente nos últimos anos.
O crescimento de sites na Web tem sido exponencial, o número de sites E-commerce
também tem prosperado. A classificação de páginas da Web torna-se cada vez mais importante,
especialmente em campos como mineração de dados na Web e coleta/extração
de informações. Os classificadores tradicionais são geralmente feitos manualmente e não
adaptativos, o que os torna inadequados num contexto mais amplo. Nós introduzimos
um conjunto de métodos e o estudo posterior dos seus resultados para criar um crawler
e scraper mais genéricos e modulares para extração de conhecimento em páginas de Ecommerce.
A informação recolhida pode então ser processada e utilizada na tomada de
decisão sobre o preço de venda. Esta Framework chama-se Prometheus e tem como intuito
extrair conhecimento de Web sites de E-commerce.
Este processo necessita realizar a navegação sobre lojas online e armazenar páginas de
produto. Isto implica que dado uma página web a framework seja capaz de determinar
se é uma página de produto. Para atingir este objetivo nós classificamos as páginas em
três categorias: catálogo, produto e spam. A classificação das páginas foi realizada tendo
em conta o html e o aspeto visual das páginas, utilizando tanto métodos tradicionais como
Deep Learning.
Depois de identificar um conjunto de páginas de produto procedemos à extração de
informação sobre o preço. Este processo não é trivial devido à quantidade de abordagens
possíveis para criar uma página web. A maioria dos produtos são dinâmicos no sentido
em que um produto é na realidade uma família de produtos relacionados. Por exemplo,
quando visitamos uma loja online de sapatos, para um modelo em especifico existe
a provavelmente um conjunto de tamanhos e cores disponíveis. Esse modelo pode ser
apresentado numa única página dinâmica fazendo com que seja necessário para a nossa
Framework explorar estas combinações relevantes. Este processo é chamado de scraping e
é o último passo da Framework Prometheus
The Future of the Internet III
Presents survey results on technology experts' predictions on the Internet's social, political, and economic impact as of 2020, including its effects on integrity and tolerance, intellectual property law, and the division between personal and work lives
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