International Conference on Information Science and Applications 

About: International Conference on Information Science and Applications is an academic conference. The conference publishes majorly in the area(s): The Internet & Cloud computing. Over the lifetime, 797 publications have been published by the conference receiving 4320 citations.

Indoor positioning in Bluetooth networks using fingerprinting and lateration approach

Abstract: Global Positioning System (GPS) is a well known navigation system for outdoor applications; however this technology does not work in indoor environments. In order to overcome this limitation, Bluetooth technology can be employed. Furthermore, Bluetooth technology provides an accurate and low cost solution for short range wireless communication. Most of the digital devices provide the Bluetooth functionality which also makes it a good candidate for indoor positioning. In this paper, we use Bluetooth devices for indoor positioning and use signal based parameters such as received power level for position estimation. The accuracy of indoor positioning system is greatly dependant on the parameters selected for estimation and the measurements obtained from the environment. However, the measurements are corrupted by various environmental conditions such as temperature, reflection, presence of obstacles, human body and other communication signals. Therefore, we need to filter the measurements. This paper presents an experimental relationship between the received power level and distance using the standard radio propagation model. The idea behind this study is to provide an accurate distance estimate for Trilateration approach. Based on the experiments performed, the average error is minimized from 5.87 meters to 2.67 meters using gradient filter. The use of gradient filter improves the accuracy by 45 %.

Layer-Wise Relevance Propagation for Deep Neural Network Architectures

Abstract: We present the application of layer-wise relevance propagation to several deep neural networks such as the BVLC reference neural net and googlenet trained on ImageNet and MIT Places datasets. Layer-wise relevance propagation is a method to compute scores for image pixels and image regions denoting the impact of the particular image region on the prediction of the classifier for one particular test image. We demonstrate the impact of different parameter settings on the resulting explanation.

A Business Model for Cloud Computing Based on a Separate Encryption and Decryption Service

Abstract: Enterprises usually store data in internal storage and install firewalls to protect against intruders to access the data. They also standardize data access procedures to prevent insiders to disclose the information without permission. In cloud computing, the data will be stored in storage provided by service providers. Service providers must have a viable way to protect their clients' data, especially to prevent the data from disclosure by unauthorized insiders. Storing the data in encrypted form is a common method of information privacy protection. If a cloud system is responsible for both tasks on storage and encryption/decryption of data, the system administrators may simultaneously obtain encrypted data and decryption keys. This allows them to access information without authorization and thus poses a risk to information privacy. This study proposes a business model for cloud computing based on the concept of separating the encryption and decryption service from the storage service. Furthermore, the party responsible for the data storage system must not store data in plaintext, and the party responsible for data encryption and decryption must delete all data upon the computation on encryption or decryption is complete. A CRM (Customer Relationship Management) service is described in this paper as an example to illustrate the proposed business model. The exemplary service utilizes three cloud systems, including an encryption and decryption system, a storage system, and a CRM application system. One service provider operates the encryption and decryption system while other providers operate the storage and application systems, according to the core concept of the proposed business model. This paper further includes suggestions for a multi-party Service- Level Agreement (SLA) suitable for use in the proposed business model.

Food Recommendation System Using Clustering Analysis for Diabetic Patients

Abstract: Food and nutrition are a key to have good health. They are important for everyone to maintain a healthy diet especially for diabetic patients who have several limitations. Nutrition therapy is a major solution to prevent, manage and control diabetes by managing the nutrition based on the belief that food provides vital medicine and maintains a good health. Typically, diabetic patients need to avoid additional sugar and fat so the food pyramid is recommended to the patients for finding the substitution from the same food group. However, there is still a dietary diversity within food groups that can affect the diabetic patients. In this study, we proposed Food Recommendation System (FRS) by using food clustering analysis for diabetic patients. Our system will recommend the proper substituted foods in the context of nutrition and food characteristic. We used Self-Organizing Map (SOM) and K-mean clustering for food clustering analysis which is based on the similarity of eight significant nutrients for diabetic patient. At the end, the FRS was evaluated by nutritionists and it has performed very well and useful for nutrition area.

Location Privacy against Traffic Analysis Attacks in Wireless Sensor Networks

Abstract: Traffic analysis attacks are passive attacks that try to deduce the traffic pattern based on the eavesdropped information. Through analyzing the packet traffic, it can deduce the location of strategic nodes, and then launch an active attack to those locations, such as DoS attack. Therefore, defending against a traffic analysis attack is to prevent the adversary from tracing the location of critical sensor nodes. Due to the open wireless communication media exposing the context information to adversaries, we cannot use traditional encryption and authentication to prevent the adversaries from eavesdropping on the wireless communication. In this paper, we propose three schemes to defend against the traffic analysis attacks. Firstly, a random routing scheme (RRS) is proposed to provide path diversity. Secondly, we combine RRS with a dummy packet injection scheme (DPIS) to confuse the adversary by tracing or tracing back the forwarded packet to reach the receiver or source. Finally, an anonymous communication scheme (ACS) is proposed to hide the identities of all nodes that participate in packets transmission. Through security analysis and simulation, we can see that our proposed schemes can efficiently defend against traffic analysis attacks, take less delivery time and achieve uniform energy consumption.