Trust-based recommendation systems in Internet of Things: a systematic literature review

Abstract

During the past decades, in the era of wireless communications and embedded system, the concept of the Internet of Things (IoT) was first presented by Kevin Ashton in the year 1999 [1]. Along with the tremendous growth in the number of sensing devices connected to the Internet, we were a witness of emerging IoT into healthcare, transportation system, smart cities, agriculture, and other enterprises. The IoT benefits cooperation of diverse computing systems such as sensors and smart devices to cloud computers. On the other side, the internet and mobile communication facilitate the spatiotemporal connection between distant people with common experience and values. More recently, technological evolution is introduced by intelligent sensor devices installed in the physical and virtual realm of IoT to act as or on behalf of human beings: the virtual robots [2]. This creates the possibility for physical objects present in a self-organized manner without a central administration and leads to meaningful human-machine interaction in IoT scenario [3].

Analysis of Vulnerabilities That Can Occur When Generating One-Time Password

“…However, in this process, if the first extraction information and the next one are the same, all three bytes of the extraction data are duplicated. For example, when the least significant byte arr [19] of the cipher text is 0x42, the extraction information is 0x02, which is LSB 4-bit, and the first extraction data is arr [2]. Then, LSB 4-bit of arr [2] is the second extraction information.…”

“…For example, when the least significant byte arr [19] of the cipher text is 0x42, the extraction information is 0x02, which is LSB 4-bit, and the first extraction data is arr [2]. Then, LSB 4-bit of arr [2] is the second extraction information. At this time, if the LSB 4-bit of arr [2] is also 0x02, the second extracted data is arr [2] again.…”

“…Then, LSB 4-bit of arr [2] is the second extraction information. At this time, if the LSB 4-bit of arr [2] is also 0x02, the second extracted data is arr [2] again. The third and last process is the same.…”

“…As a result, a total of three bytes are duplicated. Example output is arr [2] In this case, the probability that a duplicate situation occurs in the extraction algorithm can be obtained as follows. Since the bit string is the output of the encryption algorithm, i.i.d is satisfied between all bits.…”

“…It also has the property of randomness, which makes it mathematically impossible to infer the next password from the current one. It is known to be highly secure because of these features, and it can be used as an authentication service in Information & Communication Technology (ICT) [2] fields such as mobile-payment [3,4] and mobile-cloud computing [5,6].…”