433 resultados para Internet Security

em Queensland University of Technology - ePrints Archive


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A browser is a convenient way to access resources located remotely on computer networks. Security in browsers has become a crucial issue for users who use them for sensitive applications without knowledge ofthe hazards. This research utilises a structure approach to analyse and propose enhancements to browser security. Standard evaluation for computer products is important as it helps users to ensure that the product they use is appropriate for their needs. Security in browsers, therefore, has been evaluated using the Common Criteria. The outcome of this was a security requirements profile which attempts to formalise the security needs of browsers. The information collected during the research was used to produce a prototype model for a secure browser program. Modifications to the Lynx browser were made to demonstrate the proposed enhancements.

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For any discipline to be regarded as a professional undertaking by which its members may be treated as true “professionals” in a specific area, practitioners must clearly understand that discipline’s history as well as the place and significance of that history in current practice as well as its relevance to available technologies and artefacts at the time. This is common for many professional disciplines such as medicine, pharmacy, engineering, law and so on but not yet, this paper submits, in information technology. Based on twenty five elapsed years of experience in developing and delivering Cybersecurity courses at undergraduate and postgraduate levels, this paper proposes a rationale and set of differing perspectives for the planning and development of curricula relevant to the delivery of appropriate courses in the history of cybersecurity or information assurance to information and communications technology (ICT) students and thus to potential information technology professionals.

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Nth-Dimensional Truncated Polynomial Ring (NTRU) is a lattice-based public-key cryptosystem that offers encryption and digital signature solutions. It was designed by Silverman, Hoffstein and Pipher. The NTRU cryptosystem was patented by NTRU Cryptosystems Inc. (which was later acquired by Security Innovations) and available as IEEE 1363.1 and X9.98 standards. NTRU is resistant to attacks based on Quantum computing, to which the standard RSA and ECC public-key cryptosystems are vulnerable to. In addition, NTRU has higher performance advantages over these cryptosystems. Considering this importance of NTRU, it is highly recommended to adopt NTRU as part of a cipher suite along with widely used cryptosystems for internet security protocols and applications. In this paper, we present our analytical study on the implementation of NTRU encryption scheme which serves as a guideline for security practitioners who are novice to lattice-based cryptography or even cryptography. In particular, we show some non-trivial issues that should be considered towards a secure and efficient NTRU implementation.

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We propose two public-key schemes to achieve “deniable authentication” for the Internet Key Exchange (IKE). Our protocols can be implemented using different concrete mechanisms and we discuss different options; in particular we suggest solutions based on elliptic curve pairings. The protocol designs use the modular construction method of Canetti and Krawczyk which provides the basis for a proof of security. Our schemes can, in some situations, be more efficient than existing IKE protocols as well as having stronger deniability properties.

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There is value of using brands to build relationships with customers and improve brand performance on the web. Products and services are easily replicated; therefore to simplify the buyer decision making process, brands have become important. Building strong brands is important as they can create contrasts between other brands, connections to consumers, and relevance through building customer relationships. Branding in an online environment is important for three reasons: security, recognition and associated costs.

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Monitoring Internet traffic is critical in order to acquire a good understanding of threats to computer and network security and in designing efficient computer security systems. Researchers and network administrators have applied several approaches to monitoring traffic for malicious content. These techniques include monitoring network components, aggregating IDS alerts, and monitoring unused IP address spaces. Another method for monitoring and analyzing malicious traffic, which has been widely tried and accepted, is the use of honeypots. Honeypots are very valuable security resources for gathering artefacts associated with a variety of Internet attack activities. As honeypots run no production services, any contact with them is considered potentially malicious or suspicious by definition. This unique characteristic of the honeypot reduces the amount of collected traffic and makes it a more valuable source of information than other existing techniques. Currently, there is insufficient research in the honeypot data analysis field. To date, most of the work on honeypots has been devoted to the design of new honeypots or optimizing the current ones. Approaches for analyzing data collected from honeypots, especially low-interaction honeypots, are presently immature, while analysis techniques are manual and focus mainly on identifying existing attacks. This research addresses the need for developing more advanced techniques for analyzing Internet traffic data collected from low-interaction honeypots. We believe that characterizing honeypot traffic will improve the security of networks and, if the honeypot data is handled in time, give early signs of new vulnerabilities or breakouts of new automated malicious codes, such as worms. The outcomes of this research include: • Identification of repeated use of attack tools and attack processes through grouping activities that exhibit similar packet inter-arrival time distributions using the cliquing algorithm; • Application of principal component analysis to detect the structure of attackers’ activities present in low-interaction honeypots and to visualize attackers’ behaviors; • Detection of new attacks in low-interaction honeypot traffic through the use of the principal component’s residual space and the square prediction error statistic; • Real-time detection of new attacks using recursive principal component analysis; • A proof of concept implementation for honeypot traffic analysis and real time monitoring.

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The technological environment in which contemporary small and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides for the SME a complex and challenging operational context. The primary aim of this research was to concentrate on those SMEs that had already adopted technology in order to identify their needs for the new mobile data technologies (MDT), the mobile Internet. The research design utilised a mixed approach whereby both qualitative and quantitative data was collected to address the question. Overall, the needs of these SMEs for MDT can be conceptualised into three areas where the technology will assist business practices; communication, eCommerce and security.

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Today’s evolving networks are experiencing a large number of different attacks ranging from system break-ins, infection from automatic attack tools such as worms, viruses, trojan horses and denial of service (DoS). One important aspect of such attacks is that they are often indiscriminate and target Internet addresses without regard to whether they are bona fide allocated or not. Due to the absence of any advertised host services the traffic observed on unused IP addresses is by definition unsolicited and likely to be either opportunistic or malicious. The analysis of large repositories of such traffic can be used to extract useful information about both ongoing and new attack patterns and unearth unusual attack behaviors. However, such an analysis is difficult due to the size and nature of the collected traffic on unused address spaces. In this dissertation, we present a network traffic analysis technique which uses traffic collected from unused address spaces and relies on the statistical properties of the collected traffic, in order to accurately and quickly detect new and ongoing network anomalies. Detection of network anomalies is based on the concept that an anomalous activity usually transforms the network parameters in such a way that their statistical properties no longer remain constant, resulting in abrupt changes. In this dissertation, we use sequential analysis techniques to identify changes in the behavior of network traffic targeting unused address spaces to unveil both ongoing and new attack patterns. Specifically, we have developed a dynamic sliding window based non-parametric cumulative sum change detection techniques for identification of changes in network traffic. Furthermore we have introduced dynamic thresholds to detect changes in network traffic behavior and also detect when a particular change has ended. Experimental results are presented that demonstrate the operational effectiveness and efficiency of the proposed approach, using both synthetically generated datasets and real network traces collected from a dedicated block of unused IP addresses.

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Before making a security or privacy decision, Internet users should evaluate several security indicators in their browser, such as the use of HTTPS (indicated via the lock icon), the domain name of the site, and information from extended validation certificates. However, studies have shown that human subjects infrequently employ these indicators, relying on other indicators that can be spoofed and convey no cryptographic assurances. We identify four simple security indicators that accurately represent security properties of the connection and then examine 125 popular websites to determine if the sites' designs result in correctly displayed security indicators during login. In the vast majority of cases, at least some security indicators are absent or suboptimal. This suggests users are becoming habituated to ignoring recommended security indicators.

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The following report considers a number of key challenges the Australian Federal Government faces in designing the regulatory framework and the reach of its planned mandatory internet filter. Previous reports on the mandatory filtering scheme have concentrated on the filtering technologies, their efficacy, their cost and their likely impact on the broadband environment. This report focuses on the scope and the nature of content that is likely to be caught by the proposed filter and on identifying associated public policy implications.

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Many commentators have treated the internet as a site of democratic freedom and as a new kind of public sphere. While there are good reasons for optimism, like any social space digital space also has its dark side. Citizens and governments alike have expressed anxiety about cybercrime and cyber-security. In August 2011, the Australian government introduced legislation to give effect to Australia becoming a signatory to the European Convention on Cybercrime (2001). At the time of writing, that legislation is still before the Parliament. In this article, attention is given to how the legal and policy-making process enabling Australia to be compliant with the European Convention on Cybercrime came about. Among the motivations that informed both the development of the Convention in Europe and then the Australian exercise of legislating for compliance with it was a range of legitimate concerns about the impact that cybercrime can have on individuals and communities. This article makes the case that equal attention also needs to be given to ensuring that legislators and policy makers differentiate between legitimate security imperatives and any over-reach evident in the implementation of this legislation that affects rule of law principles, our capacity to engage in democratic practices, and our civic and human rights.

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Internet chatrooms are common means of interaction and communications, and they carry valuable information about formal or ad-hoc formation of groups with diverse objectives. This work presents a fully automated surveillance system for data collection and analysis in Internet chatrooms. The system has two components: First, it has an eavesdropping tool which collects statistics on individual (chatter) and chatroom behavior. This data can be used to profile a chatroom and its chatters. Second, it has a computational discovery algorithm based on Singular Value Decomposition (SVD) to locate hidden communities and communication patterns within a chatroom. The eavesdropping tool is used for fine tuning the SVD-based discovery algorithm which can be deployed in real-time and requires no semantic information processing. The evaluation of the system on real data shows that (i) statistical properties of different chatrooms vary significantly, thus profiling is possible, (ii) SVD-based algorithm has up to 70-80% accuracy to discover groups of chatters.