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The Controller area network (CAN) is the most extensively used in-vehicle network. It is set to enable communication between a number of electronic control units (ECU) that are widely found in most modern vehicles. CAN is the de facto in-vehicle network standard due to its error avoidance techniques and similar features, but it is vulnerable to various attacks. In this research, we propose a CAN bus intrusion detection system (IDS) based on convolutional neural networks (CNN). U-CAN is a segmentation model that is trained by monitoring CAN traffic data that are preprocessed using hamming distance and saliency detection algorithm. The model is trained and tested using publicly available datasets of raw and reverse-engineered CAN frames. With an F1Score of 0.997, U-CAN can detect DoS, Fuzzy, spoofing gear, and spoofing RPM attacks of the publicly available raw CAN frames. The model trained on reverse-engineered CAN signals that contain plateau attacks also results in a true positive rate and false-positive rate of 0.971 and 0.998, respectively., 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), 27 June 2022 - 01 July 2022, Alamitos, CA, USA

In an incineration plant, remote operation from a centralized control room is now possible, but inspection and cleaning of equipment still require a worker to visit the site. When the plant owner reduces the number of workers due to operation costs, it will be standard for a single worker to visit the site. Therefore, it is necessary to monitor the location of workers in real-time to detect unexpected human accidents quickly. Conventional methods use radio waves, such as Wi-Fi and Bluetooth, but there is little demand for communication equipment in the incineration plant. However, there is not enough demand for communication facilities in the incineration plant. It is too large to bear the cost of installing wireless access points, and Bluetooth Low Energy (BLE) beacons just for positioning. Therefore, we are focusing on magnetism using for indoor positioning method. In addition, the incineration plant has a lot of types of equipment that contains a wide range of magnetized metals, large motors, and generators. We could observe the magnetic peculiarity at each point. Based on these assumptions, we have developed a new indoor positioning method at the incineration plant. This paper describes the development of an indoor positioning system for an incineration plant. And we propose three methods for fingerprinting matching: Point matching, Path matching, and DTW matching. The average positioning errors of these methods are 6.89 m, 0.05 m, and 0.06 m, respectively., Comment: 6 pages

Nowadays, vehicles are equipped with multiple Electronic Control Units (ECUs) each of which communicates with one another using a specification called Controller Area Network (CAN). CAN provides its own share of benefits in modernizing automobiles, but it also brought along a security issue to the automotive industry. CAN bus does not have any mechanism for encrypting or authenticating CAN payloads. As a countermeasure against these drawbacks, we have experimented on identifying intrusions in the CAN bus using Long Short-Term Memory Networks (LSTM). LSTM networks are trained with features extracted from reverse engineered packets. In a specific range of time windows, we have extracted three parameters, the number of packets, the bit flip rate and the average time difference that are used to train LSTM. The trained LSTM is later then used to predict all the three features which will be combined to a single anomaly signal using a root mean squared error. Depending on which side of the threshold appears the anomaly signal value, we managed to identify anomalies in an acceptable performance rate, up to F1 score of 98%. We have tested our methods with a variety of attacks on the CAN bus and demonstrated how effective our detection methods is.

Recently, cyberattacks on Controller Area Network (CAN) whichis one of the automotive networks are becoming a severe problem.CAN is a protocol for communicating among Electronic ControlUnits (ECUs) and it is a de-facto standard of automotive networks.Some security researchers point out several vulnerabilities in CANsuch as unable to distinguish spoofing messages due to no authenti cation and no sender identification. To prevent a malicious messageinjection, at least we should identify the malicious senders by ana lyzing live messages. In previous work, a delay-time based methodcalled Divider to identify the sender node has been proposed. How ever, Divider could not identify ECUs which have similar variationsbecause Divider’s measurement clock has coarse time-resolution.In addition, Divider cannot adapt a drift of delay-time caused by thetemperature drift at the ambient buses. In this paper, we proposea super fine delay-time based sender identification method withTime-to-Digital Converter (TDC). The proposed method achievesan accuracy rate of 99.67% in the CAN bus prototype and 97.04% ina real-vehicle. Besides, in an environment of drifting temperature,the proposed method can achieve a mean accuracy of over 99%., The 16th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2021) will be held as a virtual event due to COVID-19 from June 7th to June 11th, 2021.

A controller area network (CAN) is a communication protocol for in-vehicle networks. Communication between electronic control units (ECUs) is facilitated by the CAN bus. This communication protocol provides no authentication or encryption to prevent the consequences of cyberattacks. As a security measure for this protocol, we have proposed an intrusion detection system (IDS) using a convolutional neural network (CNN). The CNN is trained on recurrence images generated from the encoded labels of CAN frame arbitration IDs, thus Rec-CNN. Using recurrence plots helps us capture the temporal dependency in the sequence of arbitration IDs unlike the state-of-art method, which does not capture this information. We have tested the proposed method on a publicly available dataset with denial of service (DoS), fuzzy, spoofing-gear, and spoofing-RPM attacks, resulting in an accuracy of 0.999. Furthermore, we have experimented with the method on our target vehicle. The proposed method can classify our simulated attacks with an accuracy of 0.999 in an attack frequency of 10 ms.

Online applications adoption, and success are driven by a multitude of factors among them the service response time. This is natural as users tend to prefer a faster service than a slower. However, it is challenging to deliver consistently fast response times due to performance variability inherent to the infrastructure running the application; This performance variability causes a fraction of user requests to experience unusual latency called tail latency. In this work, a Linear Regression Based Replica Selection Algorithm is proposed. The regression model helps to estimate how long a specific query is going to take to be serviced, and based on this information, a server with more or less resources is chosen to service the query. Experiments done using data generated by a fleet of buses show that the proposed approach is successful in reducing the higher percentiles latency up to 30 % in some cases while not impacting negatively the throughput., 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)

CAN uses no authentication and encryption mechanisms for secure communication. To solve the security issues of the CAN bus, a deep learning-based intrusion detection systems have been proposed. But due to the high dimensional property of the CAN bus data, it was not possible to create an effective Intrusion Detection System (IDS) in the CAN bus that can take the property of the CAN data into consideration. In this paper, we are proposing a Long Short-Term Memory Networks (LSTM) based IDS that can handle the high dimensional property of the CAN bus data . Unlike the conventional methods which required a single network architecture for each unique arbitration ID, our method gives a single overall anomaly signal over a certain detection window without the need for reverese-engineering the CAN bus data. Using this anomaly signal we have managed to achieve 100% detection precision for insertion, fuzzy and targeted attacks in our data and in a public data that is prepared for this specific purpose., 2020 30th International Telecommunication Networks and Applications Conference (ITNAC)

In search and rescue (SAR) operation, the potential of Unmanned Aerial Vehicles (UAVs) gathers great attention. Existing studies have made various experiments to find victims by a UAVs with a single sensor, e.g., one of an optical camera, a thermal infrared camera, and a radio wave signal. However, the experimental environments are limited to show the performance of the sensor. Since there are various SAR missions, it is difficult to choose the best sensor for all environments. Then, to enhance the UAV performance, we need to consider multiple sensors to find a victim efficiently. In the paper, we investigate optical camera and thermal infrared camera for finding a victim helpfully. In the investigation, we observed the differences between their images by distance and brightness to find a human., SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor SystemsNovember 2020

The number of computer controlled vehicles throughout the world is rising at a staggering speed. Even though this enhances the driving experience, it opens a new security hole in the automotive industry. To alleviate this issue, we are proposing an intrusion detection system (IDS) to the controller area network (CAN), which is the de facto communication standard of present-day vehicles. We implemented an IDS based on the analysis of ID sequences. The IDS uses a trained Long-Short Term Memory (LSTM) to predict an arbitration ID that will appear in the future by looking back to the last 20 packet arbitration IDs. The output from the LSTM network is a softmax probability of all the 42 arbitration IDs in our test car. The softmax probability is used in two approaches for IDS. In the first approach, a single arbitration ID is predicted by taking the class which has the highest softmax probability. This method only gave us an accuracy of 0.6. Applying this result in a real vehicle would give us a lot of false negatives, hence we devised a second approach that uses log loss as an anomaly signal. The evaluated log loss is compared with a predefined threshold to see if the result is in the anomaly boundary. Furthermore, We have tested our approach using insertion, drop and illegal ID attacks which greatly outperform the conventional method with practical F1 scores of 0.9, 0.84, and 1.0 respectively., 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops),23-27 March 2020,Austin, TX, USA, USA

In recent years, some bus companies have raised revenue by reviewing the route plan using the number of passengers. The company has a system that can automatically counts the number of passengers on an ongoing basis. But they are costly because they use cameras and sensors those are dedicated for counting. It is too expensive for bus companies that really need to reconsider their route planning to introduce the system. In order to solve this problem and realize efficient operation, we propose a method to count passengers by using a drive recorder and sensors those are already equipped with buses. Drive recorders and various sensors will be obliged by the government to be set up by bus operators in the future. We constructed a model using Random Forest Regression with the position of the bus from the GPS module in the buses, the position of the bus stop used for operation management, and the number of passengers estimated from the image processing method combining YOLOv3 and Deep SORT. As a result, the average correct answer rate when the passengers get on and off are 96.2% and 70.1% respectively. Our method which utilized non-dedicated camera achieved higher correct answer rate than the conventional method which utilizes dedicated camera for counting passenger., 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops),Kyoto, Japan, Japan

In bus companies, it is important for an operation manager to grasp operation states of vehicles from a viewpoint of safety management and improving an operation efficiency. Currently, for allowing operation managers to grasp operation states of vehicles, drivers should record operation states by manually operating a recorder called ”Digital-tachograph.” However, operating the digital tachograph is a heavy burden to the driver. In addition, the records may have driver's human error. In order to solve these problems and to realize efficient operation, we propose a method for automatic classification of operation states using sensor data obtained from buses. We implemented a classifier using Random Forest with the sensor data. As a results of experiments, the correct answer rate was 0.92 or more in each condition unless it was irregular operation., 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops),Athens, Greece

In bus companies, it is important for the operation manager to grasp operation states of the vehicle from the viewpoint of safety management and improving the operation efficiency. Currently, for allowing the operation manager to grasp operation states of the vehicle, the driver records operation states by manually operating a recorder called `Digital-tachograph'. However, operating a digital tachograph is a heavy burden to the driver. In this research, in order to solve this problem and to realize efficient operation, we propose a method for automatic classification of operation states using sensor data obtained from the buses. We implemented a classifier using Random Forest with the sensor data. The correct answer rate was 0.9 or more in each condition unless it was irregular operation., 2017 IEEE International Conference on Big Data (Big Data),Boston, MA, USA

International audience; The Kalray MPPA-256 processor is based on a recent low-energy manycore architecture. In this article, we investigate its performance in multiprecision arithmetic for number-theoretic applications. We have developed a library for modular arithmetic that takes full advantage of the particularities of this architecture. This is in turn used in an implementation of the ECM, an algorithm for integer factorization using elliptic curves. For parameters corresponding to a cryptanalytic context, our implementation compares well to state-of-the-art implementations on GPU, while using much less energy.

Pairings on hyperelliptic curves have been applied to many cryptographic schemes, and it is important to exploit methods that increase the speed of various pairings and their curves. Additionally, multiple pairings should be performed efficiently in some cryptographic application such as attribute-based encryption or functional encryption. We propose an efficient extension field construction method that defines a curve and its ηT pairing. We also implemented the parallel arithmetic on extension fields and multiple ηT pairings in parallel and reported experimental timing results. We achieved timing of 12.7ms and 52.0ms per pairing when computed 1248 pairings by using GPU Tesla K20c. We took the extension degree of base field m = 487 which is greater than the parameter m = 367, 439 that was appropriate for the ηT pairing at the 128-bit security level. By normalization of experimental result, we achieved a certain level of speeding up of the ηT pairing compared to the state-of-the-art CPU implementation. In addition, we achieved scalability with the extension degree of base field in our parallel implementation by performing Karatsuba multiplications between multiple elements of extension field in parallel.

Resource discovery is an essential function for distributed mobile applications integrated in vehicular communication systems. Key requirements of the mobile resource discovery are wide-area geographic-based discovery and scalable resource discovery not only inside a vehicular ad-hoc network but also through the Internet. While a number of resource discovery solutions have been proposed, most of them have focused on specific scale of network. Furthermore, managing a large number of mobile resources in the Internet raises a scalability issue due to the mobility of vehicles. In this paper, we design a solution to wide area geographical mobile resource discovery in heterogeneous networks composed of numerous mobile networks possibly connected to the Internet. The proposed system relies on a hierarchical publish-subscribe architecture and geographic routing so that users can locate resources according to geographical coordinates without scalability issue. Furthermore we propose a location management mechanism for mobile resources, which enables to reduce periodic updates of geographical location. Numerical analysis and simulation results show that our system can discover mobile resources without overloading both mobile network and the Internet.

SUMMARY With the rapid rise in the demand for location related service, communication devices such as PDAs or cellar phones must be able to search and manage information related to the geographical location. To leverage location-related information is useful to get an in-depth perspective on environmental circumstances, such as traffic conditions or weather information. To handle the large number of information and queries communication devices generate in the current ubiquitous environment, some scalable mechanism must be required. DHTs and some overlay networks supporting range search are proposed. However, these overlay networks can not process queries of geographical region search. In this paper, we propose a overlay network called “Mill” which can efficiently manage information related to the geographical location. In DHT based overlay networks, each node has responsibility to manage a part of the whole hash table. DHTs provide scalable systems and support fast search. However, DHTs are not good at solving geographical search (range search), because hash function only supports exact match. In the Mill network, each node manages a part of ID-space calculated by “Z-ordering,” which represents squire surface of the earth. This structure of ID-space enables to process region queries easily and fast. And Mill supports any scale of region search. We evaluate proposed system by using traffic infomation generator called “HAKONIWA.” Simulation results show that the performance of Mill is good as well as other DHT systems. In addtion, Mill provedes more efficient region search than other overlay networks supporting range search.

There are some cases regarding information propagation over a wide area, such as Vehicle-to-Vehicle (V2V) communications, in which an end-to-end path does not exist, due to the non-uniform density of vehicles. In order to solve this problem, Delay Tolerant Network (DTN) architectures have been studied to facilitate message delivery in V2V communications. However, existing message delivery methods for the purpose of information sharing do not consider the efficiency of message passing communications. As a result, information can be lost, due to a decrease in the efficiency of information propagation. In order to increase the efficiency of information propagation, we propose a vehicle clustering algorithm, based on the similarity of geographic locations and trajectories. This contributes to efficient message passing communication. In order to evaluate our proposal, we carry out a simulation. The simulation results confirm that our proposed method provides higher message reachability, and utilizes bandwidth more efficiency than existing methods., PerCom Workshops 2015: IEEE International Conference on Pervasive Computing and Communication Workshops, Mar 23-27, 2015, St. Louis, MO, USA

Personal computing with affordable computers and their peripheral devices becomes more popular. To use such devices more efficiently and improve their usability, people want to share surrounding peripheral devices between computers without any modification of their own computing environments. The recent device sharing technologies in the pervasive computing area are not sufficient for the peripheral devices of personal computers because these technologies do not provide the network-transparency for applications and device drivers. In this paper, we propose USB/IP as a transparent device sharing mechanism over IP network. This advanced device sharing mechanism is based on the modern sophisticated peripheral interfaces and their supports in operating systems. By the Virtual Host Controller Interface Driver we have implemented as a peripheral bus driver, users can share diverse devices over networks without any modification in existing operating systems and applications. The experiments show that USB/IP has fairly practical I/O performance for various USB devices, including isochronous ones. We also describe the performance optimization criteria for the further improvements.

One of the most challenging fields in vehicular communications has been the experimental assessment of protocols and novel technologies. Researchers usually tend to simulate vehicular scenarios and/or partially validate new contributions in the area by using constrained testbeds and carrying out minor tests. In this line, the present work reviews the issues that pioneers in the area of vehicular communications and, in general, in telematics, have to deal with if they want to perform a good evaluation campaign by real testing. The key needs for a good experimental evaluation is the use of proper software tools for gathering testing data, post-processing and generating relevant figures of merit and, finally, properly showing the most important results. For this reason, a key contribution of this paper is the presentation of an evaluation environment called AnaVANET, which covers the previous needs. By using this tool and presenting a reference case of study, a generic testing methodology is described and applied. This way, the usage of the IPv6 protocol over a vehicle-to-vehicle routing protocol, and supporting IETF-based network mobility, is tested at the same time the main features of the AnaVANET system are presented. This work contributes in laying the foundations for a proper experimental evaluation of vehicular networks and will be useful for many researchers in the area., in EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 2014

The experimental evaluation of wireless and mobile networks is a challenge that rarely substitutes simulation in research works. This statement is even more evident in vehicular communications, due to the equipment and effort needed to obtain significant and realistic results. In this paper, key issues in vehicular experimental evaluation are analyzed by an evaluation tool called AnaVANET, especially designed for assessing the performance of vehicular networks. This software processes the output of well-known testing tools such as ping or iperf, together with navigation information, to generate geo-aware performance figures of merit both in numeric and graphical forms. Its main analysis capabilities are used to validate the good performance in terms of delay, packet delivery ratio and throughput of NEMO, when using a road-side segment based on IPv6 GeoNetworking.

In emerging vehicular communication systems, each vehicle periodically broadcasts safety messages, which contains various vehicle parameters such as location and velocity. While safety messages are designed for advanced road safety and traffic efficiency, a significant concern is that eavesdroppers can track the vehicle's trajectory. In particular, this tracking is easily performed in low vehicle density environments. To address this location privacy issue, we propose a location privacy protection method in such environments using dummy node messages. In our approach, from an eavesdropper's view, the vehicle density is increased by the generation of dummy node messages. Simulation results show that our proposed method reduces tracking probability in high/low vehicle density environments., ITST 2013: 13th International Conference on ITS Telecommunications, Nov 5-7, 2013, Tampere, Finland

Publish/Subscribe mechanism is one of key technologies for handling real-time data stream in decentralized environments. While recent studies have showed that publish/subscribe systems should support not only data filtering but also in-network data processing, scalability issue is addressed due to data concentrations on specific nodes. To solve the scalability issue, we propose a Publish/Subscribe system consisting of two-tier overlay network: one overlay network is designed as a geographic overlay network, which is used to maintain fundamental information, on the other hand, data transfer networks are constructed to perform in-network data processing and dynamic load balancing. By using these two networks, we could implement geographic based dynamic subscription reallocation mechanism. This mechanism enables to achieve scalability and avoid data/load concentrations on large-scale Publish/Subscribe systems. We present an evaluation of the our approach through simulation. We compare our approach to another DHT based Publish/Subscribe system, focusing on data transfer during subscription. Our results show that our dynamic subscription reallocation approach avoids data concentration to specific node., AINA 2013: 27th International Conference on Advanced Information Networking and Applications Workshops, Mar 25-28, 2013, Barcelona, Spain

Exchanging traffic information among nearby vehicles is one of the communication scenarios in the field of intelligent transport systems (ITS). An important question in this scenario is ”How can traffic information be delivered to only one subset of nearby vehicles in the same road traffic situation?", for example, to only congested traffic in a certain lane. In this demonstration, we propose a dynamic IPv6 multicast group assignment mechanism using GPS, an accelerometer and a magnetometer embedded in smartphones. Our mechanism enables each vehicle to find the relevant vehicles, and to compose a temporary IPv6 multicast address. Our mechanism can deliver traffic information to a group of vehicles in a particular situation. This demonstration, carried out on virtual traffic congestion, shows an information-sharing scenario using a prototype of the proposed mechanism, implemented as an Android application called TrafficCam. Our application demonstrates the usefulness of the proposed mechanism., CCNC 2013: 10th IEEE Consumer Communications and Networking Conference, Jan 11-14, 2013, Las Vegas, NV, USA

The cloud computing paradigm is now widely used thanks to its scalable on-demand resource management techniques. Since one of the most important challenges of cloud computing services is to stably provide their consumers with computing resources, it is necessary to investigate the performance of cloud computing services in actual operations. To study the realistic performance of cloud computing services, we propose in this paper deploying and operating a distributed cloud computing system as a web-based, nationwide image delivery service for the annual baseball championship game in Japan. Measurement results show that the proposed system has worked stably, though it raised some performance issues related to the highly loaded VM., SAINT 2012: 12th IEEE/IPSJ International Symposium on Applications and the Internet, July 16-20, 2012, Izmir, Turkey

International audience; Service discovery is an essential component for distributed mobile applications in vehicular communication systems. While there have been numerous service discovery protocols, applications for vehicular communication systems pose additional requirements: discover services according to geographical position inside dynamic mobile environments. In this article, we propose a geographical location aware service discovery mechanism for vehicular ad-hoc networks (VANETs). The proposed mechanism exploits an IPv6 multicast service discovery protocol on IPv6 GeoNet-working specified by the GeoNet project. Thanks to the GeoBroadcast mechanism, it efficiently propagates service discovery messages to a subset of nodes inside a relevant geographical area with encapsulating IPv6 multicast packets. We implemented the proposed mechanism to the ns-3 network simulator, furthermore we integrated the prototype system using CarGeo6, an open source implementation of IPv6 GeoNetworking, with openSLP. Our simulation and real field evaluation results show the system can discover services with low latency and low bandwidth usage in VANETs even via multi-hop.

Service discovery is an essential component for applications in vehicular communication systems. While there have been numerous service discovery protocols dedicated to a local network, mobile ad-hoc networks and the Internet, in vehicular communication systems, applications pose additional requirements; They need to discover services according to geographical position. In this paper, we propose a location-aware service discovery mechanism for Vehicular Ad-hoc NETwork (VANET). The proposed mechanism exploits IPv6 multicast on top of IPv6 GeoNetworking specified by the GeoNet project. Thanks to the GeoBroadcast mechanism, it efficiently propagates service discovery messages to a subset of nodes inside a relevant geographical area with encapsulating IPv6 multicast packets. We implemented the mechanism using CarGeo6, an open source implementation of IPv6 GeoNetworking. Our real field evaluation shows the system can discover services with low latency and low bandwidth usage in VANETs., ITST 2011: 11th International Conference on ITS Telecommunications, Aug 23-25, 2011, St. Petersburg, Russia

The total solar eclipse of July 22, 2009 was the longest that of the 21st century, many astronomy shows were held in Asia. To transmit this valuable moment to a distant area with enough liveliness, we considered a mechanism how to transmit. Only that transmits the image of the corona or the diamond ring which the moon lines up with the sun like existing methods, it is difficult to say that we can transmit a total solar eclipse perfectly. In this research, we succeeded in transmitting not only the image of the sun but also the image of the whole sky all with an atmosphere., SIGGRAPH ASIA 2009: 2nd ACM SIGGRAPH Conference and Exhibition in Asia, 16-19 Dec 2009, Yokohama, Japan

To search the contents through WWW in consideration of user's circumstance condition, search engines should make use of some information such as current time, user's location, user's schedule and so on. We propose an information retrieval method that effectively uses both user's and content's metadata based on TPO (time, position, occasion). We implement a prototype of information retrieval system based on the proposed method, which consists of query generation part, contents matching part, and matched results scoring part. In our query generation part, we reduce user's overload of choosing metadata. And a user becomes possible to retry sorting the matching results., PACRIM 2005: IEEE Pacific Rim Conference on Communications, Computers and signal Processing, Aug 24-26, 2005, Victoria, BC, Canada

Recently, the telepresence which allows us to experience a remote site through a virtualized real world has been investigated. We have already proposed telepresence systems using omni-directional images which enable the user to look around a virtualized dynamic real scene. The system gives the feeling of high presence to the user. However, conventional systems are not networked but are implemented as stand-alone systems that use immersive displays. In this paper we propose a networked telepresence system which enables the user to see a virtualized real world easily in network environments. This paper describes the system implementation using real-time and stored omni-directional video streams as well as its experiments., PCM 2004 : Pacific Rim Conference on Multimedia , Nov 30-Dec 3, 2004 , Tokyo, Japan

In this paper, we propose a dynamic QoS adaptation mechanism for the networked virtual reality (VR) system to improve responsiveness to the users and introduce a live video into an networked VR system. To keep presentation quality as much as possible from point of view of user’s perception when network and local system resources are going to starve, we introduce the notion of an importance of presence (IoP) of objects. In case of the resource starvation, our VR system reduces QoSs of both Computer Graphic (CG) objects and Video objects based on IoP. That is, the quality of the object whose IoP is the lowest in the virtual space is reduced.