Traffic Anomaly Detection in DDoS Flooding Attack

Researches have been conducted to overcome Distributed Denial of Service (DDoS) flooding attack. Beside the use of signature based detection, anomaly based detection is also used to detect the attack. Several methods such as statistic, information theory, data mining and forecasting have been proposed. In several researches, they just focused to detect the traffic anomaly, but not to recognize the types of anomaly that were detected such as flashcrowd, types of botnet, types of DDoS, and prevention action. In this paper we categorize anomaly traffic detection system based on process and capability focus. Anomaly detection system process including traffic features, preprocessing, and detection process. Capability focus based on each main research problem to be solved, there are detectingonly anomaly, types of anomaly, and prevention system that include process to overcome the attack. At the end of paper, we provide overview of research direction and opportunities that may be done in future research.

Integration of Kleptoware as Keyboard Keylogger for Input Recorder Using Teensy USB Development Board

Operating a computer to perform everyday tasks is sure to require input devices. The common human interface devices for operating a computer are mouse and keyboard. It means that modifying input devices can be alternative way to do monitoring and logging activity from a user. A keylogger is able to do such functions, but various hardware and software keylogger on the market are easily detectable either physically or by antivirus software. Those limitations can be avoided by hiding a keylogger directly into the keyboard. This key logger is implemented using Teensy 2.0 USB development board, which differs between the PS/2 and USB variant. Results of analysis shows that the keylogger in undetectable physically and works correctly just like any normal keyboard. The drawbacks are reduced performance as in increasing delay between held keystrokes, key ghosting and key jamming.

AN IMPLEMENTATION OF DATA ENCRYPTION FOR INTERNET OF THINGS USING BLOWFISH ALGORITHM ON FPGA

Information security has become an important issue in data communications. One method to ensure the security of data is to use cryptographic method. Cryptography is a method to encode the information to keep the information from being hacked by the other party. The implementation of cryptography is used a significant amount of computer resources. Various range application of blowfish algorithm can be implemented for data encryption sent from an Internet of Things physical network which have IP-based data. In this research, blowfish algorithm is implemented on FPGA using VHDL programming language, and monitored the number of FPGA resource that is used. The blowfish algorithm is analyzed by computing certain metrics performances such as security, encryption time, avalanche effect, and throughput from multiple testing scenarios for system reliability. The testing showed that blowfish algorithm gave a good performance when implemented in FPGA and show a good alternative to proposed as network security on Internet of Things.

Analysing Kleptodata Process on Android Operating System

“The popularity of Android smartphones has increased the number of security threats. One of the security threats is data theft. This study implemented and analyzed the data theft (kleptodata) process on Android operating system. To help the research we built a system that exploits several Android features. An already installed Android application can get the permission to download and install another application. Then the downloaded application may run in the background. The other feature exploited is the permission-based security system on Android, where the user was unable to review the permissions asked by application. The user may accept or ignore all of the permission asked. We also incorporated the inter-application communication features on Android, to split the applications used into two different applications, making it harder to detect the system as malicious application. The results found is that the malware application used is capable to perform kleptodata attack, with the SMS logs being sent into server. As the time of testing in May 2014, several commonly used antivirus on the Market still unable to detect the application used to help the process as malicious, since it wasn’t matched with any previous malwares’ signature.”