• Title/Summary/Keyword: Bugging

Search Result 2, Processing Time 0.021 seconds

The danger and vulnerability of eavesdropping by using loud-speakers (스피커를 이용한 도청 위험에 대한 연구)

  • Lee, Seung Joon;Ha, Young Mok;Jo, Hyun Ju;Yoon, Ji Won
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.23 no.6
    • /
    • pp.1157-1167
    • /
    • 2013
  • The development of electronic devices has recently led to many problems such as personal information rape and leakage of business information. Conventional loud-speakers have been generally used to output devices. It can be, however, operated as a micro-phone which was abused as a means for eavesdropping since the speaker and microphone have basically the equivalent structure. Most importantly, the general peoples are not aware of the approaching danger about using speaker as microphone. And, traditional eavesdropping detection equipment does not check the attack. In this paper, we demonstrate that there is a serious danger and vulnerability in using loud-speakers since they can be used as eavesdropping devices.

Automatic Document Classification Using Multiple Classifier Systems (다중 분류기 시스템을 이용한 자동 문서 분류)

  • Kim, In-Cheol
    • The KIPS Transactions:PartB
    • /
    • v.11B no.5
    • /
    • pp.545-554
    • /
    • 2004
  • Combining multiple classifiers to obtain improved performance over the individual classifier has been a widely used technique. The task of constructing a multiple classifier system(MCS) contains two different Issues how to generate a diverse set of base-level classifiers and how to combine their predictions. In this paper, we review the characteristics of existing multiple classifier systems : Bagging, Boosting, and Slaking. For document classification, we propose new MCSs such as Stacked Bagging, Stacked Boosting, Bagged Stacking, Boosted Stacking. These MCSs are a sort of hybrid MCSs that combine advantages of existing MCSs such as Bugging, Boosting, and Stacking. We conducted some experiments of document classification to evaluate the performances of the proposed schemes on MEDLINE, Usenet news, and Web document collections. The result of experiments demonstrate the superiority of our hybrid MCSs over the existing ones.