Counterfeited products are costing the global economy hundreds of billions of dollars annually. Radio frequency identification(RFID) technology provides a promising solution for this problem, wherein each product is fitted with a secure tag, which is difficult to forge. However, RFID technology is faced with numerous security threats, for example, if the communication link between the reader and the tag is compromised, then it will be possible for a malicious adversary to obtain the private data stored on the device. Tag cloning attacks have also been demonstrated to be feasible, which severely undermines the capabilities of the RFID technology to protect against counterfeiting. One solution to this problem is the use of authentication protocol; however, existing schemes do not support mutual authentication and are still vulnerable to tag cloning attacks. In this paper, a new security mechanism is proposed, which consists of a lightweight three-flights mutual authentication protocol and an anti-counterfeit tag design. The proposed solution is based on combining the Rabin public-key encryption scheme with physically unclonable functions (PUF) technology. The security of the proposed protocol is systematically analysed and compared with existing schemes. The implementation cost of the proposed security primitives, assuming the 1024-bit public key, is 10139 GEs, which is suitable for low-cost RFID tags. Our results show that the proposed design is up-to 50% more area-efficient compared to systems based on Elliptic Curve Cryptography (ECC).
H umanity has faced an outbreak first time after the second world war. The origin of Covid-19 is Wuhan, China and it was announced initially in December 2019 [1]. By 6 January 2021, the spreading of this outbreak is quite fast around the world, and more than 87.2 million people have infected over 192 countries [2]. Besides, 1.88 million people have died due to Covid-19. To date, various timeseries forecasting models have played an important role in the maintenance of health public systems. Additionally, governments obtain information about the spread and consequences of infectious diseases through these models. In this sense, governments have taken some precautions to reduce the spreading speed of Covid-19 based on the results of these models, such as declare a curfew at regular intervals, quarantines etc. [3]. In the field of case forecasting, various studies have been proposed to predict Covid-19 cases. More detailed information about the proposed studies are available in the literature (Literature Review Section.).
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