I Kadek Dendy Senapartha
Universitas Kristen Duta Wacana

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ANALISIS KEAMANAN JARINGAN UNIVERSITAS KRISTEN DUTA WACANA DENGAN SERANGAN SSL/TLS Nathanael Dharmawan; Gani Indriyanta; I Kadek Dendy Senapartha
Jurnal Terapan Teknologi Informasi Vol 6 No 2 (2022): Jurnal Terapan Teknologi Informasi
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21460/jutei.2022.62.214

Abstract

The security of data communication over the network has become an obligation that needs to be considered in a technology ecosystem. Data security has various layers, one layer that needs to be protected is the presentation layer where SSL/TLS is located. If at this layer there are vulnerabilities where sensitive data such as cookies, usernames, and passwords are present, then data leakage will have a major impact on all stakeholders in the technology sector using SSL/TLS technology. In order to research and improve data security in Duta Wacana Christian University (DWCU) campus network, the researchers conducted SSL/TLS vulnerability testing on the  SSAT and E-Class websites using the SSL Test from Qualys and a script from testssl.sh, the author also conducted Checking Mixed Content with GeekFlare and checking HSTS Preload using the HSTS Preload website provided by Google. Researchers also conducted SSL Strip penetration tests at 12 points of the DWCU building and also in Lab D. Based on the results of the study, there were several results found. The results on the SSL Test using Qualys found that the SSAT and E-Class websites already use HTTP Strict Transport Security (HSTS) rules with Max-Age 31536000 (1 year) but HSTS Preload has not been implemented, Mixed Content testing with GeekFlare shows that all transactions on SSAT and E-Class already uses HTTPS paths, then in tests using the testssl.sh script there are vulnerabilities that are read, and SSL Strip attacks are possible in Duta Wacana Christian University network under several conditions.
Fake Face Detection System Using MobileNets Architecture Gabriel Indra Widi Tamtama; I Kadek Dendy Senapartha
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 2 (2023): July 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i2.43762

Abstract

Sistem pengenalan wajah merupakan salah satu metode dalam teknik biometric yang menggunakan wajah untuk proses identifikasi atau verifikasi seseorang. Teknologi ini tidak memerlukan kontak fisik seperti verifikasi sidik jari dan diklaim lebih aman karena wajah setiap orang memiliki karakter yang berbeda-beda. Terdapat dua fase utama dalam sistem biometrik wajah, yaitu deteksi wajah palsu Presentation Attack (PA) detektor dan pengenalan wajah (face recognition). Penelitian ini melakukan eksperimen dengan tujuan membangun sebuah model pembelajaran mesin (machine learning) berbasis mobile untuk melakukan deteksi wajah palsu ataupun memverifikasi keaslian wajah dengan menggunakan arsitektur Mobilenets. Verifikasi keaslian wajah diperlukan untuk meningkatkan sistem pengenalan wajah sehingga bisa membedakan wajah palsu dengan asli. Wajah palsu bisa dihadirkan dengan menunjukkan rekaman video atau gambar wajah seseorang sehingga bisa memanipulasi sistem. Dengan adanya metode verifikasi wajah asli, maka keamanan sistem bisa ditingkatkan dan meminimalisir penyalahgunaan. Kami menggunakan tiga jenis dataset publik, yaitu Replay-Mobile, Record-MPAD, dan LLC-FSAD untuk bahan training terhadap model anti-spoof yang dibangun. Model anti-spoof wajah dibangun dengan menggunakan arsitektur MobilenetV2 dengan menambahkan 3 layer neural network yang digunakan sebagai layer klasifikasi. Kemudian pengujian secara terkontrol dilakukan dengan menggunakan program komputer menghasilkan nilai HTER 0.17. Sedangkan hasil pengujian secara tidak terkontrol menggunakan aplikasi prototipe Android menghasilkan nilai HTER sebesar 0.21. Hasil pengujian ini menghasilkan selisih nilai HTER sebesar 0.04 yang mengindikasikan bahwa model anti-spoof wajah akan memiliki performa yang cenderung menurun bila digunakan secara real. The facial recognition system is a method in biometric techniques that use faces to identify or verify a person. This technology does not require physical contact such as fingerprint verification and is claimed to be safer because everyone's face has a different character. There are two main phases in the facial biometric system, namely fake face detection (Presentation Attack (PA) detector) and facial recognition. This study conducted experiments with the aim of building a mobile-based machine learning model to detect fake faces or verify facial authenticity using the MobileNets architecture. Verification of facial authenticity is needed to improve the facial recognition system so that it can distinguish fake faces from real ones. Fake faces can be presented by showing video recordings or pictures of someone's face so they can manipulate the system. The real-face verification method can improve system security and minimize misuse. We use three types of public datasets, namely Replay-Mobile, Record-MPAD, and LLC-FSAD for training materials for the built anti-spoof model. The facial anti-spoof model is built using the MobilenetV2 architecture by adding 3 neural network layers which are used as classification layers. Then controlled testing was carried out using a computer program to produce an HTER value of 0.17. While the results of uncontrolled testing using the Android prototype application produce an HTER value of 0.21. The results of this test produce a difference in the HTER value of 0.04, indicating that the facial anti-spoof model will have performance that tends to decrease when used in real terms.
Implementasi Single Sign-On Menggunakan Google Identity, REST dan OAuth 2.0 Berbasis Scrum I Kadek Dendy Senapartha
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 2 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i2.3437

Abstract

Single Sign-On (SSO) is a technology that can support user convenience in accessing a system. By using SSO, a user only needs to authenticate once to get access to a system. OAuth 2.0 is one of the protocols that can be implemented on the SSO system. Currently, many Application Service Providers (ASP) support the OAuth 2.0 protocol thus providing convenience in the development of a more standard SSO system. Google Identity is one of the services provided by Google that can be used to build SSO systems using the OAuth 2.0 protocol. Application of the request and response methods provided by the protocol specification OAuth 2.0 and Representational State Transfer (REST) architecture of the system implementation can also make SSO systems more secure. In its implementation, the use of an agile system development methodology with the Scrum framework is used to increase speed and flexibility. The results of this research show that the use of Google Identity, REST, and OAuth 2.0 can provide easy user access, guarantee access validity, accelerate client-server data exchange and simplify the SSO implementation process.