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2020-09-08
Isnan Imran, Muh. Ikhdar, Putrada, Aji Gautama, Abdurohman, Maman.  2019.  Detection of Near Field Communication (NFC) Relay Attack Anomalies in Electronic Payment Cases using Markov Chain. 2019 Fourth International Conference on Informatics and Computing (ICIC). :1–4.
Near Field Communication (NFC) is a short- range wireless communication technology that supports several features, one of which is an electronic payment. NFC works at a limited distance to exchange information. In terms of security, NFC technology has a gap for attackers to carry out attacks by forwarding information illegally using the target NFC network. A relay attack that occurs due to the theft of some data by an attacker by utilizing close communication from NFC is one of them. Relay attacks can cause a lot of loss in terms of material sacrifice. It takes countermeasures to overcome the problem of electronic payments with NFC technology. Detection of anomalous data is one way that can be done. In an attack, several abnormalities can be detected which can be used to prevent an attack. Markov Chain is one method that can be used to detect relay attacks that occur in electronic payments using NFC. The result shows Markov chain can detect anomalies in relay attacks in the case of electronic payment.
2019-04-01
Usuzaki, S., Aburada, K., Yamaba, H., Katayama, T., Mukunoki, M., Park, M., Okazaki, N..  2018.  Interactive Video CAPTCHA for Better Resistance to Automated Attack. 2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU). :1–2.
A “Completely Automated Public Turing Test to Tell Computers and Humans Apart” (CAPTCHA) widely used online services so that prevents bots from automatic getting a large of accounts. Interactive video type CAPTCHAs that attempt to detect this attack by using delay time due to communication relays have been proposed. However, these approaches remain insufficiently resistant to bots. We propose a CAPTCHA that combines resistant to automated and relay attacks. In our CAPTCHA, the users recognize a moving object (target object) from among a number of randomly appearing decoy objects and tracks the target with mouse cursor. The users pass the test when they were able to track the target for a certain time. Since the target object moves quickly, the delay makes it difficult for a remote solver to break the CAPTCHA during a relay attack. It is also difficult for a bot to track the target using image processing because it has same looks of the decoys. We evaluated our CAPTCHA's resistance to relay and automated attacks. Our results show that, if our CAPTHCA's parameters are set suitable value, a relay attack cannot be established economically and false acceptance rate with bot could be reduced to 0.01% without affecting human success rate.