CBSE APPROACH USING CLEAN ROOM SOFTWARE ENGINEERING FOR INTRUSION DETECTION SYSTEM

被引：0
|
作者：
Angurala, Mohit [1 ]
Sharma, Geetanjali [2 ]
机构：
[1] PTU, Golden Coll Engn & Technol, Gurdaspur, India
[2] PTU, Beant Coll Engn & Technol, Gurdaspur, India
来源：
PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT | 2016年
关键词：
Network Security; CBSE; Clean Room Software Engineering;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In today's era security in network is becoming weak due to increase in number of viruses and threats. These viruses and threats are becoming stronger and stronger due to automatic tools that are coming to the market. These tools without any knowledge of coding can create harmful viruses and threats which are really hard to control. Though we have latest tools to overcome against these threats but still we cannot think that we are safe completely. So, in this paper we have proposed our own Intrusion detection system with component based software Engineering approach along with the clean room software engineering approach in which we test our component at every stage of development of a component that is during its build so that we get minimum chances of bug in our Intrusion Detection System. We have proposed an algorithm for it and as well as we have implemented its design in UML language in software.
引用
收藏
页码：3279 / 3285
页数：7
相关论文
共 50 条
  • [1] An innovative approach to integrating research into education in Component-Based Software Engineering (CBSE)
    Pour, G
    6TH UICEE ANNUAL CONFERENCE ON ENINEERING EDUCATION, CONFERENCE PROCEEDINGS: EDUCATING FOR THE RIGHT ENVIRONMENT, 2003, : 105 - 108
  • [2] Security on software life cycle using intrusion detection system
    Myat Myat Min
    Khin Haymar Saw Hla
    APSITT 2005: 6th Asia-Pacific Symposium on Information and Telecommunication Technologies, Proceedings, 2005, : 360 - 363
  • [3] A software fault tree approach to requirements analysis of an intrusion detection system
    Helmer G.
    Wong J.
    Slagell M.
    Honavar V.
    Miller L.
    Lutz R.
    Requirements Engineering, 2002, 7 (4) : 207 - 220
  • [4] Intrusion Detection in Software Defined Network Using Deep Learning Approach
    Susilo, Bambang
    Sari, Riri Fitri
    2021 IEEE 11TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC), 2021, : 807 - 812
  • [5] Intrusion Detection Approach Using Connectionist Expert System
    马锐
    刘玉树
    杜彦辉
    Journal of Beijing Institute of Technology(English Edition), 2005, (04) : 467 - 470
  • [6] Intrusion Detection System (IDS): Anomaly Detection using Outlier Detection Approach
    Jabez, J.
    Muthukumar, B.
    INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION AND CONVERGENCE (ICCC 2015), 2015, 48 : 338 - 346
  • [7] An elastic intrusion detection system for software networks
    Martin Andreoni Lopez
    Diogo Menezes Ferrazani Mattos
    Otto Carlos M. B. Duarte
    Annals of Telecommunications, 2016, 71 : 595 - 605
  • [8] An elastic intrusion detection system for software networks
    Lopez, Martin Andreoni
    Ferrazani Mattos, Diogo Menezes
    Duarte, Otto Carlos M. B.
    ANNALS OF TELECOMMUNICATIONS, 2016, 71 (11-12) : 595 - 605
  • [9] Intrusion Detection System For Manets Using Deep Learning Approach
    Sbai, Oussama
    Elboukhari, Mohamed
    International Journal of Computer Science and Applications, 2021, 18 (01) : 85 - 101
  • [10] Intrusion Detection System Using Machine Learning Approach: A Review
    Sharma, Kapil
    Chawla, Meenu
    Tiwari, Namita
    INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATIONS, ICICC 2022, VOL 1, 2023, 473 : 727 - 734
12345