• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.113-123
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• 2023

This paper introduces the Cherry system, a user-independent blockchain donation system. This is a procedure that is delivered to the beneficiary's bank account through a virtual account when a donor makes a donation, so there is no difference from the existing donation delivery method from the user's point of view However, within the blockchain, Cherry Points, a virtual currency based on the user ID, are issued and delivered to the beneficiary, while all transactions and the beneficiary's usage history are managed on the blockchain. By adopting this method, there was an improvement in blockchain performance, with transaction processing exceeding 1,000 TPS in typical transaction condition and service completion within 21.3 seconds. By applying the automatic influence control algorithm to this system, the influence according to stake, which is an individual donation, is greatly reduced to 0.3 after 2 months, thereby concentrating influence could be controlled automatically. In addition, it was designed to enable micro tracking by adding a tracking function by timestamp to the donation ledger for each individual ID, which greatly improved the transparency in the use of donations. From a service perspective, existing blockchain donation systems were handled as limited donation delivery methods. Since it is a direct service in a user-independent method, convenience has been greatly improved by delivering donations in various forms.

• The Korean Journal of Food And Nutrition
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• v.11 no.1
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• pp.11-19
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• 1998

This study was performed to investigate the information of food preference of workers for meal served by industry foodservice. The subjects were composed of 212 office workers and 220 laborers. The results were obtained as follows : 50.7% of the subjects were 30∼39 years old ; 72.0% of them had high school education ; the type of favored food was Korean style cooked rice ; food taste was the most important point in food selection. Preference form main foods : Cooked rice was preferred the most by the subjects. Both office workers and laborers liked Kalkooksoo and vegetable bread and cooked rice covered with beef was preferred by office workers and cooked rice covered with raw fish pieces was preferred by laborers. Also they disliked Hash rice, Curry rice and rice-cake soup in the pattern. Preference for side-dish : The Acceptances for side-dishes were high in soybean paste soup(office workers : 37.5%, laborers : 31.5%), hot chowder of corvina(26.1%, 25.7%), kimchi stew(30.5%, 28.8%), beef broiled in soy(32.5%, 30.5%), baked fish(32.5%, 31.9%), pachon(20.7%, 25.9%), a meat inside a razor clam(25.1$, 29.2%) and Chinese cabbage kimchi(44.5%, 46.3%), in that order by both of them. But in office workers, seasoned bean sprouts and steamed beef-rib were shown to have high preference and in laborers seasoned spinach and steamed pork-rib were high. Preference of snacks : The preferences for snacks were high in milk(office workers : 50.3%, laborers : 48.5%), Songpean(28.9%, 30.1%), coffee(30.8%, 32.5%), Sikhye(18.8%, 17.5%), in that order by two groups.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.683-694
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• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.