Supeno Djanali

Classification of EEG Signals Using Single Channel Independent Component Analysis, Power Spectrum, and Linear Discriminant Analysis

Epilepsy is a neurological disorder of the brain that can generate epileptic seizures when abnormal excessive activity occurs in the brain. The seizure is marked by brief episodes of involuntary movement of the body, and sometimes followed by unconsciousness. In this study, the EEG classification system was performed to predict whether EEG signals belong to normal individuals, epileptic patients in seizure free or seizure condition. The EEG dataset contains 5 sets of 100 EEG segments which is referred to as set A to set E. The classification system consisted of three scenarios. One of the scenarios involved the methods of Single Channel Independent Component Analysis (SCICA), power spectrum, and a neural network. The results were compared to the results without implementing SCICA. The last experiment showed the effect of using Linear Discriminant Analysis (LDA) to reduce the features of power spectrum. The results gave the accuracies for 3, 4, and 5 classes. By applying SCICA, all the accuracies were improved significantly with the maximum accuracy of 94 % for 3 classes.

SQL injection detection and prevention system with raspberry Pi honeypot cluster for trapping attacker

One of the most common security attack for web application is SQL injection. It is an attack to acquire access to applications database through injection of script or malicious query attributes. This attack can be executed in any page of web application which interacts with database. SQL injection could be more dangerous if the victim was an enterprise system such as online banking. Many methods have been researched and developed to prevent SQL injection attacks. One of them is the use of a honeypot. This paper proposed a method for increasing systems capability to detect and prevent SQL injection attacks based on removal of SQL query attribute values and honeypot for trapping attackers. A honeypot is placed as decoy system to hide actual web server from attacker. Malicious queries from attackers will be sent to honeypot while normal queries will be sent directly to the real web server. Honeypot is also used to provide activity logging of each attack which can be used for further analysis. We play with Raspberry Pi because it is cheap and effective to be used as a honeypot. Due to its limited computational ability, we make cluster to improve its power. Based on conducted experiments, we could achieve up to 64% accuracy of SQL injection attack. Moreover, with the redirection, our honeypot could get more attack data to be analyzed.

Increasing the capacity of the secret data using DEpixels blocks and adjusted RDE-based on grayscale images

One of the main purposes of data hiding is to secure the messages while transmitting via a public network such as the internet. As known, there are so many types of data hiding such as hiding text inside text, text inside video, and text inside digital image. It is also known that, Difference Expansion has become a powerful method in data hiding using digital images. For instance, it is known that data hiding is needed in so many fields such as health, military, and finance. Especially for reversible data hiding which has the ability to return the same secret data and cover image after the extraction operation. In this paper, we focus on how to increase the capacity of the secret message as high as possible while maintaining the quality of the stego image. We will present a scheme that has modified the previous method by enlarging the pixel blocks to be as a matrix 4 by 4 that can hide 15 bits per block. In addition, we have modified the scheme of RDE to make the difference values smaller since that will bring also a chance for increasing the capacity and may improve the quality of the stego image. The experimental results have shown that the capacity has surely and hugely increased.

Modifikasi Route Discovery pada Ad-hoc On Demand Distance Vector (AODV) Berdasarkan Level Konektivitas One-Hop Node di VANETs

Vehicular Ad hoc Networks (VANETs) merupakan pengembangan dari Mobile Ad hoc Network (MANET) dimana node memiliki karakteristik dengan mobilitas yang sangat tinggi dan terbatas pada pola pergerakannya. Ada banyak routing protocol yang dapat diimplementasikan pada VANETs, salah satunya adalah Ad hoc On demand Distance Vector (AODV). AODV merupakan salah satu routing protocol yang termasuk dalam klasifikasi reactive routing protocol, sebuah protokol yang hanya akan membuat rute ketika node sumber membutuhkannya. AODV memiliki dua fase, yaitu route discovery dan route maintenance. Route discovery digunakan untuk meminta dan meneruskan informasi rute yang terdiri dari proses pengiriman Route Request (RREQ) dan Route Reply (RREP). Modifikasi pada Tugas Akhir ini akan dilakukan pada proses route discovery berdasarkan level konektivitas one-hop node, yaitu dengan cara mengeliminasi jumlah forwarding node yang bertugas untuk mengirim ulang (re-broadcast) RREQ. Hal ini dilakukan agar dapat meningkatkan kinerja protokol AODV untuk mencari rute yang stabil dengan cara memodifikasi beberapa bagian dari mekanisme pengiriman paket RREQ. Dari hasil uji coba, AODV yang dimodifikasi berhasil meningkatkan nilai Packet Delivery Ratio (PDR) hingga 9,19%, penurunan nilai Routing Overhead (RO) hingga 2,17%, dan penurunan nilai Forwarded Route Request (RREQ F) hingga 31,62%.

MODIFIKASI PROTOKOL AODV-BR MENGGUNAKAN LINK EXPIRATION TIME (LET) UNTUK MENINGKATKAN STABILITAS LINK DI LINGKUNGAN MOBILE Ad-Hoc NETWORK (MANET)

AODV protocol is a protocol that is fairly mature in mobile Ad-Hoc network. But the traditional AODV protocol in some ways it seems less satisfying, especially on the stability of data transmission. Development continues, one of which AODV-Backup Routing which became known AODV-BR, were present to address the stability issues of data delivery by providing a backup route, however, AODV-BR still use traditional routing paths that are vulnerable to termination due to the formation of these calculations are based on minimum hop. This study proposes a modified AODV-BR with reliability be the ability to build main route and to choose the route up to the value of the highest stability was then called AODV-Stable bacukp Routing (AODV-SBR). Armed algorithms Link Expiration Time with node movement calculation technique, so the AODV-SBR is able to calculate the value of the minimum and maximum connectivity nodes in a route as the main reference in establishing a delivery route data more stable. The results test of the both protocols in Packet Delivery Ratio (PDR), Throughput, End-to-En Delay and Routing Overhead shows that performance of AODV-SBR better than AODV-BR

Feature extraction using combination of intrinsic mode functions and power spectrum for EEG signal classification

The measurement of brain electrical activity recorded as EEG signals finds most application in epilepsy. EEG waveforms carry information about the underlying neural system dynamics and show different features amongst epilepsy syndromes. In this research, empirical mode decomposition (EMD) and power spectrum were employed to extract the features from EEG dataset of healthy participants, and epilepsy patients with seizure and seizure free conditions. The recorded EEG signals are represented by 500 signal segments from 5 sets of different conditions. The sum of Intrinsic Mode Function (IMF) power spectrum components gave 10 features for 50 components, and 20 features for 25 components, which were used as the classification inputs for artificial neural networks and random forest classifiers. The classifications were carried out for 3, 4, and 5 classes. From the experiments, the highest average accuracy was obtained for 3 classes using 20 features of power spectrum from the sum of 6 IMFs. For use of 6 IMFs, the accuracies had the maximum values of 92.4%, 90.4%, and 78.6% for 3, 4, and 5 classes respectively. It also improved the accuracy significantly for 5 classes.

A conceptual information of technology framework to support rice farming in timor leste

Agriculture is one of the main means of livelihood for the people of Timor Leste. Data shows that the Timor Leste annual rice consumption is 140 tonnes, while farmers only produce 60 tonnes per year [1]. One factor is that, the farmers still use traditional ways to tackle pests and diseases and when the weather forecast is not accurate. The condition of infrastructure, geographic, and communication services is a major obstacle for ministry of agriculture to have a monitoring, provide solutions, and control over agricultural issues in Timor Leste [2]. Therefore, it needs information technology to establish communication between farmers and the Ministry of Agriculture. This paper presents the multi-language framework concept namely Tetun, Indonesian, Portuguese, and English, because most of the people in Timor Leste still use the four languages for everyday communication. The aim of the framework concept is to describe a process of real time communication services with the farmers. The system acts as an expert to answer questions or to solve problems of farmers regarding pest and disease problems at any time, and hopefully it will increase agricultural productivity.

VERIFIKASI SIGNATURE PADA KOLABORASI SISTEM DETEKSI INTRUSI JARINGAN TERSEBAR DENGAN HONEYPOT

Sistem Deteksi Intrusi atau IDS merupakan suatu sistem yang banyak digunakan oleh para administrator jaringan untuk mendeteksi adanya usaha-usaha penyusupan secara proaktif berdasarkan signature atau anomali dengan cara mengeluarkan alert (peringatan) sebagai hasil dari pendeteksiannya. Namun dalam implementasinya, IDS terkadang mengeluarkan alert yang salah (true negative) atau tidak dapat mendeteksi intrusi yang bersifat Zero-Day attack, sehingga menyebabkan administrator kesulitan dalam menganalisa serangan dan tindakan yang tepat selanjutnya. Untuk menyelesaikan permasalahan yang terjadi, maka perlu dilakukan suatu kolaborasi antar IDS maupun dengan teknologi keamanan jaringan yang lain dengan tujuan untuk membuat pendeteksian intrusi menjadi lebih baik. Pada penelitian ini, diajukan suatu bentuk Kolaborasi IDS dengan teknologi keamanan jaringan, yaitu dengan Honeypot. Selain itu diajukan pula suatu mekanisme perbaikan signature hasil analisis Honeypot dengan tujuan agar signature bisa langsung digunakan oleh IDS tanpa terjadi kesalahan. Pengujian pada lima belas skenario serangan yang dilakukan menunjukkan bahwa konsep kolaborasi dan mekanisme perbaikan signature yang diajukan mampu mereduksi alert true negative dan zero-day attack sebesar 85%. Karena dari lima belas skenario serangan hanya dua skenario serangan yang tidak berhasil terdeteksi oleh IDS dan Honeypot.

ANALYSIS RESOURCE AWARE FRAMEWORK BY COMBINING SUNSPOT AND IMOTE2 PLATFORM WIRELESS SENSOR NETWORKS USING DISTANCE VECTOR ALGORITHM

Efficiency energy and stream data mining on Wireless Sensor Networks (WSNs) are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA) framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC) and Light Weight Frequent Item (LWF). The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime of wireless sensor improve up to ± 16.62%. Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN) adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA) framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC) dan Light Weight Frequent Item (LWF). Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai ± 16,62%.