• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.113-120
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• 2022

In this paper, we analyze the feasibility of the IP spoofing attack exploiting null security algorithms in 5G networks based on 3GPP standard specifications. According to 3GPP standard specifications, the initial Registration Request message is not protected by encryption and integrity. The IP spoofing attack exploits the vulnerability that allows a malicious gNB (next generation Node B) to modify the contents of the initial Registration Request message of a victim UE (User Equipment) before forwarding it to AMF (Access and Mobility Management Function). If the attack succeeds, the victim UE is disconnected from the 5G network and a malicious UE gets Internet services, while the 5G operator will charge the victim UE. In this paper, we analyze the feasibility of the IP spoofing attack by analyzing whether each signaling message composing the attack conforms to the 3GPP Rel-17 standard specifications. As a result of the analysis, it is determined that the IP spoofing attack is not feasible in the 5G system implemented according to the 3GPP Rel-17 standard specifications.

• ETRI Journal
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• v.36 no.1
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• pp.183-186
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• 2014

In this letter, we consider a cooperation system with multiple untrusted relays (URs). To keep the transmitted information confidential, we obtain joint channel characteristics (JCCs) through combining the channels from the source to the destination. Then, in the null space of the JCCs, jammers construct artificial noise to confuse URs when the source node broadcasts its data. Through a distributed implementation algorithm, the weight of each node can be obtained from its own channel state information. Simulation results show that high-level security of the system can be achieved when internal and external eavesdroppers coexist.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1939-1946
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• 2011

Expander graphs are useful in the design and analysis of communication networks. Mukhopadhyay et. al introduced a method to generate a family of expander graphs based on nongroup two predecessor single attractor CA(Cellular Automata). In this paper we propose a method to generate a family of expander graphs based on 60/102 Null boundary CA(NBCA) which is a group CA. The spectral gap generated by our method is larger than that of Mukhopadhyay et. al [12]. As an application we give an algorithm which generate one-way functions whose security lies on the combinatorial properties of our expander graphs. the one-way function using d-regular graph generated by the 60/102 NBCA is based on the Goldreich's construction [5].

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.49-56
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• 2023

Machine learning methods diversely applied to the Internet of Things (IoT) field have been successful due to the enhancement of computer processing power. They offer an effective way of detecting malicious intrusions in IoT because of their high-level feature extraction capabilities. In this paper, we proposed a novel feature selection method for malicious intrusion detection in IoT by using an evolutionary technique - Genetic Algorithm (GA) and Machine Learning (ML) algorithms. The proposed model is performing the classification of BoT-IoT dataset to evaluate its quality through the training and testing with classifiers. The data is reduced and several preprocessing steps are applied such as: unnecessary information removal, null value checking, label encoding, standard scaling and data balancing. GA has applied over the preprocessed data, to select the most relevant features and maintain model optimization. The selected features from GA are given to ML classifiers such as Logistic Regression (LR) and Support Vector Machine (SVM) and the results are evaluated using performance evaluation measures including recall, precision and f1-score. Two sets of experiments are conducted, and it is concluded that hyperparameter tuning has a significant consequence on the performance of both ML classifiers. Overall, SVM still remained the best model in both cases and overall results increased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.859-867
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• 2016

The Global Positioning System is a navigation system that has been developed by the United States for military use. Currently, many countries, including the Republic of Korea, use GPS for civilian and military uses. However, as useful as it is, GPS is vulnerable to its Jamming signal, as the strength of the signal from satellites is very weak. In this paper, a novel jamming signal detection and cancellation method is proposed when a narrow-band jamming signal is included in the GPS received signal. At the GPS receiver, the received signal is transformed to a frequency domain sample by Fast Fourier Transform. In order to suppress the Spectral Leakage, the Blackman-Harris window is used. The proposed jamming signal cancellation algorithm will find the frequency sample with maximum power and null the maximum sample in addition to some lateral samples. If the GPS receiver is designed with FFT of size 128 to 512, it is shown that 42 samples are optimal to cancel the narrow-band jamming signal.