| 000 | 02376ntm a2200277 a 4500 | ||
|---|---|---|---|
| 001 | vtls000099242 | ||
| 003 | KUKTEM | ||
| 005 | 20251117113326.0 | ||
| 008 | 170420t2016 my a f am 000 0 eng d | ||
| 020 | _aTHE0001289(Local) | ||
| 039 | 9 |
_a201905271616 _batie _y201704201117 _zsaini |
|
| 040 | _aUMP | ||
| 090 | _aFSKKP .Y44 2016 r Bc. | ||
| 100 | 1 | _aYee, Wai Kit | |
| 245 | 1 | 0 |
_aRaspberry PI-based investigation model for identifying and collecting intrusion evidences / _cYee Wai Kit |
| 260 |
_aKuantan, Pahang : _bUMP, _c2016 |
||
| 300 |
_axv, 65 p. : _bill. (some col.) ; _c30 cm. + _e1 CD-ROM |
||
| 500 | _aFaculty of Computer Systems and Software Engineering | ||
| 502 | _aProject paper (Bachelor of Computer Science (Computer Systems & Networking) With Honours) -- Universiti Malaysia Pahang – 2016 | ||
| 504 | _aBibliography : p. 64-65 | ||
| 520 | 3 | _aNowadays it is very important to maintain an intermediary level of security to ensure safe and trusted communication of information for daily usage. However, a secured data communication over internet and any other network is hard to achieve due to the threat of intrusions and misuses. None of the existing systems proved to be flawless, though various approaches being utilised for thwarting network intrusion activities, such as Denial of Service (DoS) attack, Man-in-the Middle attack and also IP address spoofing. This research proposed a system for Identifying and Collecting Intrusion Evidences (MICIE) in order to study about intrusion behaviour based on collected evidences. In particular, the proposed system MICIE comprises three main features, SNORT as IDS, MySQL as database and BASE for result viewing. These features were installed on Raspberry Pi, which was used to aid the data collection process. For the course of this research, Modified Waterfall Model is used for keeping track of the progress and to ensure that the task delegation can be fulfilled before meeting deadlines. The results demonstrated that the proposed system is promising for identifying and collecting evidence of network intrusions in real time. | |
| 610 | 2 | 0 |
_aFaculty of Computer Systems and Software Engineering _xDissertations |
| 650 | 0 |
_aUniversities and Colleges _xDissertations |
|
| 650 | 0 | _aTheses | |
| 999 |
_aVIRTUA40 _c6772 _d6778 |
||
| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5000*5020*5040*5200*6100*6500*6501*9992 | ||