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Ditemukan 9 dokumen yang sesuai dengan query
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New York: Addison-Wesley , 1990
005.8 COM
Buku Teks SO  Universitas Indonesia Library
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Hruska, Jan, 1957-
New York: Ellis Horwood, 1993
005.8 HRU c
Buku Teks SO  Universitas Indonesia Library
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Kane, Pamela
Jakarta: Dinastindo , 1995
005.8 KAN p
Buku Teks SO  Universitas Indonesia Library
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Rijanto Tosin
Jakarta: Dinastindo, 1991
005.8 RIJ d
Buku Teks SO  Universitas Indonesia Library
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Levin, Richard B.
Berkeley: Osborne McGraw-Hill, 1990
R 005.8 LEV c
Buku Referensi  Universitas Indonesia Library
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Hartojo Salim
Yogyakarta: Andi, 1993
005.8 HAR v
Buku Teks SO  Universitas Indonesia Library
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Revient Noor Ode
"Traffic is a major problem in large cities which requires wireless infrastructure that controls traffic density. Vehiculer Ad-hoc Network (VANET) which becomes communication among vehicles can solve the main problem of traffic congestion. VANET requires dynamic routing protocols such as AODV routing protocol and its extensions such as AODV-UU. Manhattan map is used in this simulation because it represents the condition of a big city. VANET network simulation with AODV routing protocol uses network simulator 2 (NS2) with the scenario of traffic density addition. We simulate routing protocol is AODV, AODV-UU, and AODV with malicious node attacks on Manhattan mobility model.
The simulation results show that VANET is more effective and efficient using AODV-UU than other routing protocol, because AODV-UU routing protocol has fast computation in transferring data. The results of VANET simulation experiments with AODV-UU routing protocol generated average delay of 16.56 ms, average packetloss of 0.228%, and average throughput of 159.64 ms. In the VANET network simulation using AODV routing protocol with malicious nodes attack mode, packetloss values generated in very large values from 30% to 50%. This results shows that a malicious hacker attacks on VANET network using AODV routing protocol will decrease the Quality of Service (QoS) performance."
Depok: Fakultas Teknik Universitas Indonesia, 2015
T44309
UI - Tesis Membership  Universitas Indonesia Library
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Aldi Burhanhamali
"ABSTRAK
Internet dan komunikasi antar jaringan yang saat ini telah menjadi kebutuhan bagi banyak orang. Salah satu bentuk serangan keamanan komputer adalah malware. Malware (Malicious Software), merupakan perangkat lunak yang dibuat untuk atau dengan maksud dan tujuan merugikan orang lain. Malware Analysis Metode Dinamis merupakan analisis yang dilakukan terhadap malware untuk mengetahui maksud dari fungsionalitas dari suatu malware, mengetahui jenis malware, mengetahui bagaimana malware dapat tersebar, apa saja yang dapat diinfeksi oleh malware dengan mempersiapkan lingkungan khusus untuk eksekusi. Berdasarkan Threat Severity Assesstment oleh Symantec Parameter menentukan tingkat ancaman adalah sejauh mana malware berada di dunia (in-the-wild), kerusakan yang malware sebabkan jika ditemukan, dan bagaimana malware bisa menyebar di sistem. Sampel malware yang dieksekusi di dalam sistem sebanyak 17 sampel secara bergantian. Dua lingkungan virtual dibuat untuk membandingkan proses injeksinya pada sistem dengan koneksi internet dan tanpa internet. Perangkat lunak yang digunakan untuk memonitor malware adalah Regshot, Process Monitor, Autoruns, Process Explorer, TCPView, Capture BAT, Wireshark dan FakeDNS. Windows 10 mampu mengenali seluruh sampel sebagai program berbahaya. Namun hanya enam (35%) sampel yang saat berjalan mampu dihentikan Windows Defender. Lima (29%) sampel membutuhkan koneksi internet agar fungsi malware berjalan sesuai dengan jenisnya. Dari 17 sampel yang dieksekusi hanya menghasilkan 3 tingkat kategori ancaman. Enam (35%) sampel berada pada tingkat ancaman Menengah. Tiga (12%) sampel diidentifikasi sebagai kategori ancaman Rendah dan 53% lainnya dikategorikan sebagai Sangat Rendah.

ABSTRACT
Internet and communication between networks today, has become a necessity for many people and can also threaten other people's personal or company data at the same time. Malware Malicious Software is a software created with the purpose and intent of harming others. Dynamic Malware Analysis Method is an analysis of the malware determine the intent of the functionality of the malware, knowing the type of malware, how malware spreads, anything that can be infected, by preparing special environment for execution. Based on Threat Severity Assessment by Symantec, the parameter that determines the threat level is the wild which measures to the extent in which virus is already spreading among computers, the damage which measures the amount of damage that a given infection could inflict and the distribution which measures how quickly a program spreads itself. Samples of malware that was executed are 17 samples. Two virtualization was created to compare the process on the system with an internet and without an internet. The monitoring software is Regshot, Process Monitor, Autoruns, Process Explorer, TCPView, Capture BAT, Wireshark and fakeDNS. Windows 10 recognized all samples as malware. However, six (35%) samples were terminated by Windows Defender after malware execution. Five (29%) samples require an internet in order to perform the function as the malware type. From all samples that were executed, the result has three levels of The Threat level categories. Six (35%) samples are at Moderate Level. Three (12%) samples as Low Threat and another 53% are categorized as Very Low;;"
2016
S65663
UI - Skripsi Membership  Universitas Indonesia Library
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