Lab

KOU Gömülü Sistemler Lab.

Featured research (2)

Due to their chaotic nature, underwater communication channels contain many adverse factors affecting the communication link quality and its performance. These adverse effects directly affect the data transfer between the source and the receiver. Absorption loss, which is one of these adverse factors, depends on depth, temperature, salinity, pH, and speed of sound, as well as frequency, and it has direct impact on the bandwidth used by the system and the distance required for reliable communication. In this study, the effects of variation of temperature, salinity, depth, and sound velocity on the channel bandwidth, channel capacity, and transmission power of the channels formed in the underwater environment in Erdek/Turkey were examined. Within the scope of the study, estimations of the bandwidth, capacity and transmission power parameters were conducted by using temperature, salinity, and sound velocity data relative to the depth recorded between July 2018 and December 2018. Cylindrical, spherical, and practical propagation models are used to compute the propagation loss. In contrast to the studies performed in the literature regarding absorption loss calculations, instead of using only the frequency-dependent approach, realistic models were created by including the effect of changes in the underwater environment in the channel estimation calculations using measurement data. Simplified absorption loss parameters for absorption loss calculations are proposed in the study. It was observed that the channel estimated within the scope of the study are compatible with the outputs obtained from the analysis.
The main purpose of DNS is to convert domain names into IPs. Due to the inadequate precautions taken for the security of DNS, it is used for malicious communication or data leakage. Within the scope of this study, a real-time deep network-based system is proposed on live networks to prevent the common DNS tunneling threats over DNS. The decision-making capability of the proposed system at the instant of threat on a live system is the particular feature of the study. Networks trained with various deep network topologies by using the data from Alexa top 1 million sites were tested on a live network. The system was integrated to the network during the tests to prevent threats in real-time. The result of the tests reveal that the threats were blocked with success rate of 99.91%. Obtained results confirm that we can block almost all tunnel attacks over DNS protocol. In addition, the average time to block each tunneled package was calculated to be 0.923 ms. This time clearly demonstrates that the network flow will not be affected, and no delay will be experienced in the operation of our system in real-time.

Lab head

Suhap Sahin
Department
  • Department of Computer Engineering

Members (8)

M. Ali Cavuslu
  • Koç Information and Defense Technologies Inc.
Sumeyya Ilkin
  • Kocaeli University
Mehmet Ali Altuncu
  • Kocaeli University
Hikmetcan Özcan
  • Kocaeli University
Taner Guven
  • Kocaeli University
Uğurcan Ergün
  • Kocaeli University
Ata Niyazov
  • Kocaeli University
Saffet Türkoğlu
  • Kocaeli University
Fatma Selin Hangişi
Fatma Selin Hangişi
  • Not confirmed yet
Oktay Duman
Oktay Duman
  • Not confirmed yet