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Articles 4321 - 4350 of 8495
Full-Text Articles in Computer Sciences
Constant-Size Ciphertexts In Threshold Attribute-Based Encryption Without Dummy Attributes, Willy Susilo, Guomin Yang, Fuchun Guo, Qiong Huang
Constant-Size Ciphertexts In Threshold Attribute-Based Encryption Without Dummy Attributes, Willy Susilo, Guomin Yang, Fuchun Guo, Qiong Huang
Research Collection School Of Computing and Information Systems
Attribute-based encryption (ABE) is an augmentation of public key encryption that allows users to encrypt and decrypt messages based on users' attributes. In a (t, s) threshold ABE, users who can decrypt a ciphertext must hold at least t attributes among the s attributes specified by the encryptor. At PKC 2010, Herranz, Laguillaumie and Raft& proposed the first threshold ABE with constant-size ciphertexts. In order to ensure the encryptor can flexibly select the attribute set and a threshold value, they use dummy attributes to satisfy the decryption requirement. The advantage of their scheme is that any addition or removal of …
A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma
A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma
Research Collection School Of Computing and Information Systems
Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the perpetual software vendor adopts one …
Multigeneration Product Diffusion In The Presence Of Strategic Consumers, Zhiling Guo, Jianqing Chen
Multigeneration Product Diffusion In The Presence Of Strategic Consumers, Zhiling Guo, Jianqing Chen
Research Collection School Of Computing and Information Systems
Frequent new product releases pose significant challenges for firms as they manage successive generations of product diffusion. We develop an analytical model to study the effect of different purchase options by strategic consumers on a firm's profit and the firm's strategies for the timing and pricing of its successive generations of product diffusion. We show that consumers' strategic behavior, although adversely affecting the sales of the first-generation product, positively influences the sales of the second-generation product through an initial “seeding” effect. The influence of strategic consumers on profit and sales depends largely on the discount-to-price ratio of the first generation …
An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal
An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal
Research Collection School Of Computing and Information Systems
Ciphertext-policy attribute-based encryption (CP-ABE) has been regarded as one of the promising solutions to protect data security and privacy in cloud storage services. In a CP-ABE scheme, an access structure is included in the ciphertext, which, however, may leak sensitive information about the underlying plaintext and the privileged recipients in that anyone who sees the ciphertext is able to learn the attributes of the privileged recipients from the associated access structure. In order to address this issue, CP-ABE with partially hidden access structures was introduced where each attribute is divided into an attribute name and an attribute value and the …
Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau
Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade off-amenable …
Engagemon: Multi-Modal Engagement Sensing For Mobile Games, Sinh Huynh, Seungmin Kim, Jeonggil Ko, Rajesh Krishna Balan, Youngki Lee
Engagemon: Multi-Modal Engagement Sensing For Mobile Games, Sinh Huynh, Seungmin Kim, Jeonggil Ko, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Understanding the engagement levels players have with a game is a useful proxy for evaluating the game design and user experience. This is particularly important for mobile games as an alternative game is always just an easy download away. However, engagement is a subjective concept and usually requires fine-grained highly disruptive interviews or surveys to determine accurately. In this paper, we present EngageMon, a first-of-its-kind system that uses a combination of sensors from the smartphone (touch events), a wristband (photoplethysmography and electrodermal activity sensor readings), and an external depth camera (skeletal motion information) to accurately determine the engagement level of …
Sclib: A Practical And Lightweight Defense Against Component Hijacking In Android Applications, Daoyuan Wu, Yao Cheng, Debin Gao, Yingjiu Li, Robert H. Deng
Sclib: A Practical And Lightweight Defense Against Component Hijacking In Android Applications, Daoyuan Wu, Yao Cheng, Debin Gao, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cross-app collaboration via inter-component communication is a fundamental mechanism on Android. Although it brings the benefits such as functionality reuse and data sharing, a threat called component hijacking is also introduced. By hijacking a vulnerable component in victim apps, an attack app can escalate its privilege for operations originally prohibited. Many prior studies have been performed to understand and mitigate this issue, but no defense is being deployed in the wild, largely due to the deployment difficulties and performance concerns. In this paper we present SCLib, a secure component library that performs in-app mandatory access control on behalf of app …
Mining Sandboxes: Are We There Yet?, Lingfeng Bao, Tien Duy B. Le, David Lo
Mining Sandboxes: Are We There Yet?, Lingfeng Bao, Tien Duy B. Le, David Lo
Research Collection School Of Computing and Information Systems
The popularity of Android platform on mobile devices has attracted much attention from many developers and researchers, as well as malware writers. Recently, Jamrozik et al. proposed a technique to secure Android applications referred to as mining sandboxes. They used an automated test case generation technique to explore the behavior of the app under test and then extracted a set of sensitive APIs that were called. Based on the extracted sensitive APIs, they built a sandbox that can block access to APIs not used during testing. However, they only evaluated the proposed technique with benign apps but not investigated whether …
An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal
An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal
Research Collection School Of Computing and Information Systems
Ciphertext-policy attribute-based encryption (CP-ABE) has been regarded as one of the promising solutions to protect data security and privacy in cloud storage services. In a CP-ABE scheme, an access structure is included in the ciphertext, which, however, may leak sensitive information about the underlying plaintext and the privileged recipients in that anyone who sees the ciphertext is able to learn the attributes of the privileged recipients from the associated access structure. In order to address this issue, CP-ABE with partially hidden access structures was introduced where each attribute is divided into an attribute name and an attribute value and the …
The Way You Move: The Effect Of A Robot Surrogate Movement In Remote Collaboration, Martin Feick, Lora Oehlberg, Anthony Tang, André Miede, Ehud Sharlin
The Way You Move: The Effect Of A Robot Surrogate Movement In Remote Collaboration, Martin Feick, Lora Oehlberg, Anthony Tang, André Miede, Ehud Sharlin
Research Collection School Of Computing and Information Systems
In this paper, we discuss the role of the movement trajectory and velocity enabled by our tele-robotic system (ReMa) for remote collaboration on physical tasks. Our system reproduces changes in object orientation and position at a remote location using a humanoid robotic arm. However, even minor kinematics differences between robot and human arm can result in awkward or exaggerated robot movements. As a result, user communication with the robotic system can become less efficient, less fluent and more time intensive.
Education In The Age Of Artificial Intelligence: How Will Technology Shape Learning?, Keng Siau
Education In The Age Of Artificial Intelligence: How Will Technology Shape Learning?, Keng Siau
Research Collection School Of Computing and Information Systems
The age of Artificial Intelligence (AI) is here! Higher education needs to prepare students for a world in which AI plays an increasingly dominant role. What are the jobs that can be replaced easily? How would higher education be affected in the age of AI, robotics, machine learning, and automation? How can higher education excel and flourish in the age of AI?
Building Trust In Artificial Intelligence, Machine Learning, And Robotics, Keng Siau, Weiyu Wang
Building Trust In Artificial Intelligence, Machine Learning, And Robotics, Keng Siau, Weiyu Wang
Research Collection School Of Computing and Information Systems
In this article, we look at trust in artificial intelligence, machine learning (ML), and robotics. We first review the concept of trust in AI and examine how trust in AI may be different from trust in other technologies. We then discuss the differences between interpersonal trust and trust in technology and suggest factors that are crucial in building initial trust and developing continuous trust in artificial intelligence.
Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu
Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
The feasibility of using vibration energy harvesting (VEH) as an energy-efficient receiver for short-range acoustic data communication has been investigated recently. When data was encoded in acoustic signal within the energy harvesting frequency band and transmitted through a speaker, a VEH receiver was capable of decoding the data by processing the harvested energy signal. Although previous work created new opportunities for simultaneous energy harvesting and communication using the same hardware, the communication makes annoying sounds as the energy harvesting frequency band lies within the sensitive region of human auditory system. In this work, we present a novel modulation scheme to …
Visualizing Research Impact Through Citation Data, Yong Wang, Conglei Shi, Liangyue Li, Hanghang Tong, Huamin Qu
Visualizing Research Impact Through Citation Data, Yong Wang, Conglei Shi, Liangyue Li, Hanghang Tong, Huamin Qu
Research Collection School Of Computing and Information Systems
Research impact plays a critical role in evaluating the research quality and influence of a scholar, a journal, or a conference. Many researchers have attempted to quantify research impact by introducing different types of metrics based on citation data, such as h-index, citation count, and impact factor. These metrics are widely used in the academic community. However, quantitative metrics are highly aggregated in most cases and sometimes biased, which probably results in the loss of impact details that are important for comprehensively understanding research impact. For example, which research area does a researcher have great research impact on? How does …
Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz Khan, Nirmalya Roy, Archan Misra
Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz Khan, Nirmalya Roy, Archan Misra
Research Collection School Of Computing and Information Systems
We investigate the problem of making human activityrecognition (AR) scalable–i.e., allowing AR classifiers trainedin one context to be readily adapted to a different contextualdomain. This is important because AR technologies can achievehigh accuracy if the classifiers are trained for a specific individualor device, but show significant degradation when the sameclassifier is applied context–e.g., to a different device located ata different on-body position. To allow such adaptation withoutrequiring the onerous step of collecting large volumes of labeledtraining data in the target domain, we proposed a transductivetransfer learning model that is specifically tuned to the propertiesof convolutional neural networks (CNNs). Our model, …
An Lstm Model For Cloze-Style Machine Comprehension, Shuohang Wang, Jing Jiang
An Lstm Model For Cloze-Style Machine Comprehension, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Machine comprehension is concerned with teaching machines to answer reading comprehension questions. In this paper we adopt an LSTM-based model we designed earlier for textual entailment and propose two new models for cloze-style machine comprehension. In our first model, we treat the document as a premise and the question as a hypothesis, and use an LSTM with attention mechanisms to match the question with the document. This LSTM remembers the best answer token found in the document while processing the question. Furthermore, we observe some special properties of machine comprehension and propose a two-layer LSTM model. In this model, we …
Urlnet: Learning A Url Representation With Deep Learning For Malicious Url Detection, Hung Le, Hong Quang Pham, Doyen Sahoo, Steven C. H. Hoi
Urlnet: Learning A Url Representation With Deep Learning For Malicious Url Detection, Hung Le, Hong Quang Pham, Doyen Sahoo, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of blacklists, which cannot be exhaustive, and cannot detect newly generated malicious URLs. To address this, recent years have witnessed several efforts to perform Malicious URL Detection using Machine Learning. The most popular and scalable approaches use lexical properties of the URL string by extracting Bag-of-words like features, followed by applying machine learning models such as SVMs. There are also other features designed by experts to improve the prediction performance of the …
W-Air: Enabling Personal Air Pollution Monitoring On Wearables, Balz Maag, Zimu Zhou, Lothar Thiele
W-Air: Enabling Personal Air Pollution Monitoring On Wearables, Balz Maag, Zimu Zhou, Lothar Thiele
Research Collection School Of Computing and Information Systems
Accurate, portable and personal air pollution sensing devices enable quantification of individual exposure to air pollution, personalized health advice and assistance applications. Wearables are promising (e.g., on wristbands, attached to belts or backpacks) to integrate commercial off-the-shelf gas sensors for personal air pollution sensing. Yet previous research lacks comprehensive investigations on the accuracies of air pollution sensing on wearables. In response, we proposed W-Air, an accurate personal multi-pollutant monitoring platform for wearables. We discovered that human emissions introduce non-linear interference when low-cost gas sensors are integrated into wearables, which is overlooked in existing studies. W-Air adopts a sensor-fusion calibration scheme …
An Efficient And Privacy-Preserving Biometric Identification Scheme In Cloud Computing, Liehuang Zhu, Chuan Zhang, Chang Xu, Ximeng Liu, Cheng Huang
An Efficient And Privacy-Preserving Biometric Identification Scheme In Cloud Computing, Liehuang Zhu, Chuan Zhang, Chang Xu, Ximeng Liu, Cheng Huang
Research Collection School Of Computing and Information Systems
Biometric identification has become increasingly popular in recent years.With the development of cloud computing, database owners are motivated to outsource the large size of biometric data and identification tasks to the cloud to get rid of the expensive storage and computation costs, which, however, brings potential threats to users’ privacy. In this paper, we propose an efficient and privacy-preserving biometric identification outsourcing scheme. Specifically, the biometric: To execute a biometric identification, the database owner encrypts the query data and submits it to the cloud. The cloud performs identification operations over the encrypted database and returns the result to the database …
A New Revocable And Re-Delegable Proxy Signature And Its Application, Shengmin Xu, Guomin Yang, Yi Mu
A New Revocable And Re-Delegable Proxy Signature And Its Application, Shengmin Xu, Guomin Yang, Yi Mu
Research Collection School Of Computing and Information Systems
With the popularity of cloud computing and mobile Apps, on-demand services such as on-line music or audio streaming and vehicle booking are widely available nowadays. In order to allow efficient delivery and management of the services, for large-scale on-demand systems, there is usually a hierarchy where the service provider can delegate its service to a top-tier (e.g., countrywide) proxy who can then further delegate the service to lower level (e.g., region-wide) proxies. Secure (re-)delegation and revocation are among the most crucial factors for such systems. In this paper, we investigate the practical solutions for achieving re-delegation and revocation utilizing proxy …
Vmkdo: Verifiable Multi-Keyword Search Over Encrypted Cloud Data For Dynamic Data-Owner, Yibin Miao, Jianfeng Ma, Ximeng Liu, Zhiquan Liu, Limin Shen, Fushan Wei
Vmkdo: Verifiable Multi-Keyword Search Over Encrypted Cloud Data For Dynamic Data-Owner, Yibin Miao, Jianfeng Ma, Ximeng Liu, Zhiquan Liu, Limin Shen, Fushan Wei
Research Collection School Of Computing and Information Systems
The advantages of cloud computing encourage individuals and enterprises to outsource their local data storage and computation to cloud server, however, data security and privacy concerns seriously hinder the practicability of cloud storage. Although searchable encryption (SE) technique enables cloud server to provide fundamental encrypted data retrieval services for data-owners, equipping with a result verification mechanism is still of prime importance in practice as semi-trusted cloud server may return incorrect search results. Besides, single keyword search inevitably incurs many irrelevant results which result in waste of bandwidth and computation resources. In this paper, we are among the first to tackle …
A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma
A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma
Research Collection School Of Computing and Information Systems
Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3744/. Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the …
Do Your Friends Make You Buy This Brand?: Modeling Social Recommendation With Topics And Brands, Minh Duc Luu, Ee Peng Lim
Do Your Friends Make You Buy This Brand?: Modeling Social Recommendation With Topics And Brands, Minh Duc Luu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Consumer behavior and marketing research have shown that brand has significant influence on product reviews and product purchase decisions. However, there is very little work on incorporating brand related factors into product recommender systems. Meanwhile, the similarity in brand preference between a user and other socially connected users also affects her adoption decisions. To integrate seamlessly the individual and social brand related factors into the recommendation process, we propose a novel model called Social Brand–Item–Topic (SocBIT). As the original SocBIT model does not enforce non-negativity, which poses some difficulty in result interpretation, we also propose a non-negative version, called SocBIT(Formula …
Attributed Social Network Embedding, Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua
Attributed Social Network Embedding, Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Embedding network data into a low-dimensional vector space has shown promising performance for many real-world applications, such as node classification and entity retrieval. However, most existing methods focused only on leveraging network structure. For social networks, besides the network structure, there also exists rich information about social actors, such as user profiles of friendship networks and textual content of citation networks. These rich attribute information of social actors reveal the homophily effect, exerting huge impacts on the formation of social networks. In this paper, we explore the rich evidence source of attributes in social networks to improve network embedding. We …
Attribute-Based Cloud Storage With Secure Provenance Over Encrypted Data, Hui Cui, Robert H. Deng, Yingjiu Li
Attribute-Based Cloud Storage With Secure Provenance Over Encrypted Data, Hui Cui, Robert H. Deng, Yingjiu Li
Research Collection School Of Computing and Information Systems
To securely and conveniently enjoy the benefits of cloud storage, it is desirable to design a cloud data storage system which protects data privacy from storage servers through encryption, allows fine-grained access control such that data providers can expressively specify who are eligible to access the encrypted data, enables dynamic user management such that the total number of data users is unbounded and user revocation can be carried out conveniently, supports data provider anonymity and traceability such that a data provider’s identity is not disclosed to data users in normal circumstances but can be traced by a trusted authority if …
Risk-Sensitive Stochastic Orienteering Problems For Trip Optimization In Urban Environments, Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh
Risk-Sensitive Stochastic Orienteering Problems For Trip Optimization In Urban Environments, Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh
Research Collection School Of Computing and Information Systems
Orienteering Problems (OPs) are used to model many routing and trip planning problems. OPs are a variantof the well-known traveling salesman problem where the goal is to compute the highest reward path thatincludes a subset of vertices and has an overall travel time less than a specified deadline. However, the applicabilityof OPs is limited due to the assumption of deterministic and static travel times. To that end, Campbellet al. extended OPs to Stochastic OPs (SOPs) to represent uncertain travel times (Campbell et al. 2011). Inthis article, we make the following key contributions: (1) We extend SOPs to Dynamic SOPs (DSOPs), …
Modelling Domain Relationships For Transfer Learning On Retrieval-Based Question Answering Systems In E-Commerce, Jianfei Yu, Minghui Qiu, Jing Jiang, Jun Huang, Shuangyong Song, Wei Chu, Haiqing Chen
Modelling Domain Relationships For Transfer Learning On Retrieval-Based Question Answering Systems In E-Commerce, Jianfei Yu, Minghui Qiu, Jing Jiang, Jun Huang, Shuangyong Song, Wei Chu, Haiqing Chen
Research Collection School Of Computing and Information Systems
Nowadays, it is a heated topic for many industries to build automatic question-answering (QA) systems. A key solution to these QA systems is to retrieve from a QA knowledge base the most similar question of a given question, which can be reformulated as a paraphrase identification (PI) or a natural language inference (NLI) problem. However, most existing models for PI and NLI have at least two problems: They rely on a large amount of labeled data, which is not always available in real scenarios, and they may not be efficient for industrial applications. In this paper, we study transfer learning …
Secure Fine-Grained Access Control And Data Sharing For Dynamic Groups In The Cloud, Shengmin Xu, Guomin Yang, Yi Mu, Robert H. Deng
Secure Fine-Grained Access Control And Data Sharing For Dynamic Groups In The Cloud, Shengmin Xu, Guomin Yang, Yi Mu, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cloud computing is an emerging computing paradigm that enables users to store their data in a cloud server to enjoy scalable and on-demand services. Nevertheless, it also brings many security issues, since cloud service providers (CSPs) are not in the same trusted domain as users. To protect data privacy against untrusted CSPs, existing solutions apply cryptographic methods (e.g., encryption mechanisms) and provide decryption keys only to authorized users. However, sharing cloud data among authorized users at a fine-grained level is still a challenging issue, especially when dealing with dynamic user groups. In this paper, we propose a secure and efficient …
Building Deep Networks On Grassmann Manifolds, Zhiwu Huang, J. Wu, Gool L. Van
Building Deep Networks On Grassmann Manifolds, Zhiwu Huang, J. Wu, Gool L. Van
Research Collection School Of Computing and Information Systems
Learning representations on Grassmann manifolds is popular in quite a few visual recognition tasks. In order to enable deep learning on Grassmann manifolds, this paper proposes a deep network architecture by generalizing the Euclidean network paradigm to Grassmann manifolds. In particular, we design full rank mapping layers to transform input Grassmannian data to more desirable ones, exploit re-orthonormalization layers to normalize the resulting matrices, study projection pooling layers to reduce the model complexity in the Grassmannian context, and devise projection mapping layers to respect Grassmannian geometry and meanwhile achieve Euclidean forms for regular output layers. To train the Grassmann networks, …
Enhanced Vireo Kis At Vbs 2018, Phuong Anh Nguyen, Yi-Jie Lu, Hao Zhang, Chong-Wah Ngo
Enhanced Vireo Kis At Vbs 2018, Phuong Anh Nguyen, Yi-Jie Lu, Hao Zhang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The VIREO Known-Item Search (KIS) system has joined the Video Browser Showdown (VBS) [1] evaluation benchmark for the first time in year 2017. With experiences learned, the second version of VIREO KIS is presented in this paper. Considering the color-sketch based retrieval, we propose a simple grid-based approach for color query. This method allows the aggregation of color distributions in video frames into a shot representation, and generates the pre-computed rank list for all available queries which reduces computational resources and favors a recommendation module. With focusing on concept based retrieval, we modify our multimedia event detection system at TRECVID …