17,094 research outputs found

    Privacy Violation and Detection Using Pattern Mining Techniques

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    Privacy, its violations and techniques to bypass privacy violation have grabbed the centre-stage of both academia and industry in recent months. Corporations worldwide have become conscious of the implications of privacy violation and its impact on them and to other stakeholders. Moreover, nations across the world are coming out with privacy protecting legislations to prevent data privacy violations. Such legislations however expose organizations to the issues of intentional or unintentional violation of privacy data. A violation by either malicious external hackers or by internal employees can expose the organizations to costly litigations. In this paper, we propose PRIVDAM; a data mining based intelligent architecture of a Privacy Violation Detection and Monitoring system whose purpose is to detect possible privacy violations and to prevent them in the future. Experimental evaluations show that our approach is scalable and robust and that it can detect privacy violations or chances of violations quite accurately. Please contact the author for full text at [email protected]

    Estimating the costs of crime in New Zealand in 2003/04

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    We estimate that the total costs of crime in New Zealand in 2003/04 amounted to 9.1billion.Ofthis,theprivatesectorincurred9.1 billion. Of this, the private sector incurred 7 billion in costs and the public sector $2.1 billion. Offences against private property are the most common crimes but offences against the person are the most costly, accounting for 45% of the total estimated costs of crime. Empirically-based measures like those presented here – the total and average costs of crime by category – are a useful aid to policy analysis around criminal justice operations and settings. However, care needs to be taken when interpreting these results because they rely considerably on assumptions, including the assumed volume of actual crime, and the costs that crime imposes on victims. This difficulty in constructing robust estimates also implies that care should be taken not to draw conclusions about whether the Government should be putting more or less resources into any specific categories of crime, based on their relative costs alone.crime; justice; costs; New Zealand

    Analysis of DoS Attacks at MAC Layer in Mobile Adhoc Networks

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    —Wireless network security has received tremendous attention due to the vulnerabilities exposed in the open communication medium. The most common wireless Medium Access Control (MAC) protocol is IEEE 802.11, which assumes all the nodes in the network are cooperative. However, nodes may purposefully misbehave in order to disrupt network performance, obtain extra bandwidth and conserve resources. These MAC layer misbehaviours can lead to Denial of Service (DoS) attacks which can disrupt the network operation. There is a lack of comprehensive analysis of MAC layer misbehaviour driven DoS attacks for the IEEE 802.11 protocol. This research studied possible MAC layer DoS attack strategies that are driven by the MAC layer malicious/selfish nodes and investigates the performance of the IEEE 802.11 protocol. Such DoS attacks caused by malicious and selfish nodes violating backoff timers associated with the protocol. The experimental and analytical approach evaluates several practical MAC layer backoff value manipulation and the impact of such attacks on the network performance and stability in MANETs. The simulation results show that introducing DoS attacks at MAC layer could significantly affect the network throughput and data packet collision rate. This paper concludes that DoS attacks with selfish/malicious intend can obtain a larger throughput by denying well-behaved nodes to obtain deserved throughput, also DoS attacks with the intend of complete destruction of the network can succee

    Diagnose network failures via data-plane analysis

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    Diagnosing problems in networks is a time-consuming and error-prone process. Previous tools to assist operators primarily focus on analyzing control plane configuration. Configuration analysis is limited in that it cannot find bugs in router software, and is harder to generalize across protocols since it must model complex configuration languages and dynamic protocol behavior. This paper studies an alternate approach: diagnosing problems through static analysis of the data plane. This approach can catch bugs that are invisible at the level of configuration files, and simplifies unified analysis of a network across many protocols and implementations. We present Anteater, a tool for checking invariants in the data plane. Anteater translates high-level network invariants into boolean satisfiability problems, checks them against network state using a SAT solver, and reports counterexamples if violations have been found. Applied to a large campus network, Anteater revealed 23 bugs, including forwarding loops and stale ACL rules, with only five false positives. Nine of these faults are being fixed by campus network operators

    Traffic Justice: Achieving Effective and Equitable Traffic Enforcement in the Age of Vision Zero

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    An Implementation of Intrusion Detection System Using Genetic Algorithm

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    Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. So Intrusion Detection Systems have become a needful component in terms of computer and network security. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. So, the quest of betterment continues. In this progression, here we present an Intrusion Detection System (IDS), by applying genetic algorithm (GA) to efficiently detect various types of network intrusions. Parameters and evolution processes for GA are discussed in details and implemented. This approach uses evolution theory to information evolution in order to filter the traffic data and thus reduce the complexity. To implement and measure the performance of our system we used the KDD99 benchmark dataset and obtained reasonable detection rate

    Cost-effectiveness of traffic enforcement: case study from Uganda

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    BACKGROUND: In October 2004, the Ugandan Police department deployed enhanced traffic safety patrols on the four major roads to the capital Kampala. OBJECTIVE: To assess the costs and potential effectiveness of increasing traffic enforcement in Uganda. METHODS: Record review and key informant interviews were conducted at 10 police stations along the highways that were patrolled. Monthly data on traffic citations and casualties were reviewed for January 2001 to December 2005; time series (ARIMA) regression was used to assess for a statistically significant change in traffic deaths. Costs were computed from the perspective of the police department in US2005.Costoffsetsfromsavingstothehealthsectorwerenotincluded.RESULTS:Theannualcostofdeployingthefoursquadsoftrafficpatrols(20officers,fourvehicles,equipment,administration)isestimatedatUS 2005. Cost offsets from savings to the health sector were not included. RESULTS: The annual cost of deploying the four squads of traffic patrols (20 officers, four vehicles, equipment, administration) is estimated at 72,000. Since deployment, the number of citations has increased substantially with a value of 327311annually.Monthlycrashdatapreandpostinterventionshowastatisticallysignificant17327 311 annually. Monthly crash data pre- and post-intervention show a statistically significant 17% drop in road deaths after the intervention. The average cost-effectiveness of better road safety enforcement in Uganda is 603 per death averted or 27perlifeyearsaveddiscountedat327 per life year saved discounted at 3% (equivalent to 9% of Uganda's 300 GDP per capita). CONCLUSION: The costs of traffic safety enforcement are low in comparison to the potential number of lives saved and revenue generated. Increasing enforcement of existing traffic safety norms can prove to be an extremely cost-effective public health intervention in low-income countries, even from a government perspective
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