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[Keyword] false positive(7hit)

1-7hit
  • Node Density Loss Resilient Report Generation Method for the Statistical Filtering Based Sensor Networks

    Jin Myoung KIM  Hae Young LEE  

     
    LETTER-Information Network

      Pubricized:
    2020/05/29
      Vol:
    E103-D No:9
      Page(s):
    2007-2010

    In the statistic en-route filtering, each report generation node must collect a certain number of endorsements from its neighboring nodes. However, at some point, a node may fail to collect an insufficient number of endorsements since some of its neighboring nodes may have dead batteries. This letter presents a report generation method that can enhance the generation process of sensing reports under such a situation. Simulation results show the effectiveness of the proposed method.

  • Multi-Dimensional Bloom Filter: Design and Evaluation

    Fei XU  Pinxin LIU  Jing XU  Jianfeng YANG  S.M. YIU  

     
    PAPER-Privacy, anonymity, and fundamental theory

      Pubricized:
    2017/07/21
      Vol:
    E100-D No:10
      Page(s):
    2368-2372

    Bloom Filter is a bit array (a one-dimensional storage structure) that provides a compact representation for a set of data, which can be used to answer the membership query in an efficient manner with a small number of false positives. It has a lot of applications in many areas. In this paper, we extend the design of Bloom Filter by using a multi-dimensional matrix to replace the one-dimensional structure with three different implementations, namely OFFF, WOFF, FFF. We refer the extended Bloom Filter as Feng Filter. We show the false positive rates of our method. We compare the false positive rate of OFFF with that of the traditional one-dimensional Bloom Filter and show that under certain condition, OFFF has a lower false positive rate. Traditional Bloom Filter can be regarded as a special case of our Feng Filter.

  • Improvement of Detection Performance in DWT-Based Image Watermarking under Specified False Positive Probability

    Masayoshi NAKAMOTO  Kohei SAYAMA  Mitsuji MUNEYASU  Tomotaka HARANO  Shuichi OHNO  

     
    PAPER-Digital Signal Processing

      Vol:
    E94-A No:2
      Page(s):
    661-670

    For copyright protection, a watermark signal is embedded in host images with a secret key, and a correlation is applied to judge the presence of watermark signal in the watermark detection. This paper treats a discrete wavelet transform (DWT)-based image watermarking method under specified false positive probability. We propose a new watermarking method to improve the detection performance by using not only positive correlation but also negative correlation. Also we present a statistical analysis for the detection performance with taking into account the false positive probability and prove the effectiveness of the proposed method. By using some experimental results, we verify the statistical analysis and show this method serves to improve the robustness against some attacks.

  • Identifying IP Blocks with Spamming Bots by Spatial Distribution

    Sangki YUN  Byungseung KIM  Saewoong BAHK  Hyogon KIM  

     
    LETTER-Internet

      Vol:
    E93-B No:8
      Page(s):
    2188-2190

    In this letter, we develop a behavioral metric with which spamming botnets can be quickly identified with respect to their residing IP blocks. Our method aims at line-speed operation without deep inspection, so only TCP/IP header fields of the passing packets are examined. However, the proposed metric yields a high-quality receiver operating characteristics (ROC), with high detection rates and low false positive rates.

  • A Clustering Method for Improving Performance of Anomaly-Based Intrusion Detection System

    Jungsuk SONG  Kenji OHIRA  Hiroki TAKAKURA  Yasuo OKABE  Yongjin KWON  

     
    PAPER-Network Security

      Vol:
    E91-D No:5
      Page(s):
    1282-1291

    Intrusion detection system (IDS) has played a central role as an appliance to effectively defend our crucial computer systems or networks against attackers on the Internet. The most widely deployed and commercially available methods for intrusion detection employ signature-based detection. However, they cannot detect unknown intrusions intrinsically which are not matched to the signatures, and their methods consume huge amounts of cost and time to acquire the signatures. In order to cope with the problems, many researchers have proposed various kinds of methods that are based on unsupervised learning techniques. Although they enable one to construct intrusion detection model with low cost and effort, and have capability to detect unforeseen attacks, they still have mainly two problems in intrusion detection: a low detection rate and a high false positive rate. In this paper, we present a new clustering method to improve the detection rate while maintaining a low false positive rate. We evaluated our method using KDD Cup 1999 data set. Evaluation results show that superiority of our approach to other existing algorithms reported in the literature.

  • Filtering False Positives Based on Server-Side Behaviors

    Makoto SHIMAMURA  Miyuki HANAOKA  Kenji KONO  

     
    PAPER-Application Information Security

      Vol:
    E91-D No:2
      Page(s):
    264-276

    Reducing the rate of false positives is of vital importance in enhancing the usefulness of signature-based network intrusion detection systems (NIDSs). To reduce the number of false positives, a network administrator must thoroughly investigate a lengthy list of signatures and carefully disable the ones that detect attacks that are not harmful to the administrator's environment. This is a daunting task; if some signatures are disabled by mistake, the NIDS fails to detect critical remote attacks. We designed a NIDS, TrueAlarm, to reduce the rate of false positives. Conventional NIDSs alert administrators that a malicious message has been detected, regardless of whether the message actually attempts to compromise the protected server. In contrast, TrueAlarm delays the alert until it has confirmed that an attempt has been made. The TrueAlarm NIDS cooperates with a server-side monitor that observes the protected server's behavior. TrueAlarm only alerts administrators when a server-side monitor has detected deviant server behavior that must have been caused by a message detected by a NIDS. Our experimental results revealed that TrueAlarm reduces the rate of false positives. Using actual network traffic collected over 14 days, TrueAlarm produced 46 false positives, while Snort, a conventional NIDS, produced 818.

  • An RTSD System against Various Attacks for Low False Positive Rate Based on Patterns of Attacker's Behaviors

    Joong-seok SONG  Yong-jin KWON  

     
    PAPER-Application Information Security

      Vol:
    E89-D No:10
      Page(s):
    2637-2643

    There is a certain level of requirements for system performance that intrusion detection systems on the Internet need. One of them is to lower the rate of "False Positive" and "False Negative." Another one is to have a convenient user interface so that users can manage system security easily with the detection systems. However, scan detection systems on public domain show a high rate of false detection and have difficulty in detecting various scanning techniques. In addition, since current scan detection systems are based on the command interface, the systems have been poor at user interface and therefore it is difficult to apply them to system security management. Hence, we first propose a set of new filter rules, which detect various scan attacks based on port scanning techniques. Secondly, a set of ABP-Rules derived from attacker's behavioral patterns is proposed in order to minimize the False Positive rate. With these methods, we implement a new real-time scan detection system, overcoming the limitations of current real-time scan detection systems. Also the implemented system contains a GUI interface for user's convenience of managing the network security, which was developed with Tcl/Tk.