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Articles 2521 - 2550 of 4281
Full-Text Articles in Entire DC Network
Improving Quality Of Use Case Documents Through Learning And User Interaction, Shuang Liu, Jun Sun, Hao Xiao, Bimlesh Wadhwa, Jin Song Dong, Xinyu Wang
Improving Quality Of Use Case Documents Through Learning And User Interaction, Shuang Liu, Jun Sun, Hao Xiao, Bimlesh Wadhwa, Jin Song Dong, Xinyu Wang
Research Collection School Of Computing and Information Systems
Use cases are widely used to capture user requirements based on interactions between different roles in the system. They are mostly documented in natural language and sometimes aided with graphical illustrations in the form of use case diagrams. Use cases serve as an important means to communicate among stakeholders, requirement engineers and system engineers as they are easy to understand and are produced early in the software development process. Having high quality use cases are beneficial in many ways, e.g., in avoiding inconsistency/incompleteness in requirements, in guiding system design, in generating test cases. In this work, we propose an approach …
Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata
Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata
Research Collection School Of Computing and Information Systems
We address the challenge of detecting and addressing advanced persistent threats (APTs) in a computer network, focusing in particular on the challenge of detecting data exfiltration over Domain Name System (DNS) queries, where existing detection sensors are imperfect and lead to noisy observations about the network’s security state. Data exfiltration over DNS queries involves unauthorized transfer of sensitive data from an organization to a remote adversary through a DNS data tunnel to a malicious web domain. Given the noisy sensors, previous work has illustrated that standard approaches fail to satisfactorily rise to the challenge of detecting exfiltration attempts. Instead, we …
Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo
Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Existing video search engines return a ranked list of videos for each user query, which is not convenient for browsing the results of query topics that have multiple facets, such as the "early life," "personal life," and "presidency" of a query "Barack Obama." Organizing video search results into semantically structured hierarchies with nodes covering different topic facets can significantly improve the browsing efficiency for such queries. In this paper, we introduce a hierarchical visualization approach for video search result browsing, which can help users quickly understand the multiple facets of a query topic in a very well-organized manner. Given a …
Static Loop Analysis And Its Applications, Xiaofei Xie
Static Loop Analysis And Its Applications, Xiaofei Xie
Research Collection School Of Computing and Information Systems
Loops are challenging structures in program analysis, and an effective loop analysis is crucial in the applications, such as symbolic execution and program verification. In the research, we will first perform a deep analysis and propose a classification according to the complexity of the loops. Then try to propose techniques for analyzing and summarizing different loops. At last, we apply the techniques in multiple applications.
Designing And Evaluating Business Process Models: An Experimental Approach, Yuecheng Martin Yu, Alexander Pelaez, Karl R. Lang
Designing And Evaluating Business Process Models: An Experimental Approach, Yuecheng Martin Yu, Alexander Pelaez, Karl R. Lang
Research Collection School Of Computing and Information Systems
This paper presents an experimental approach to compare the performance of alternative business process designs. We use an example case of an electronic group buying setting to demonstrate how our approach can be applied in practice. More specifically, we chose a standard business process, the sales process as implemented on a group buying platform, to illustrate how a business process may be redesigned in order to better meet the needs of customers. For that purpose, we introduce a social technology feature to support cooperation among buyers in the sales process and then analyze the performance impact of the proposed business …
Scaling Bdd-Based Timed Verification With Simulation Reduction, Truong Khanh Nguyen, Tian Huat Tan, Jun Sun, Jiaying Li, Yang Liu, Manman Chen, Jin Song Dong
Scaling Bdd-Based Timed Verification With Simulation Reduction, Truong Khanh Nguyen, Tian Huat Tan, Jun Sun, Jiaying Li, Yang Liu, Manman Chen, Jin Song Dong
Research Collection School Of Computing and Information Systems
Digitization is a technique that has been widely used in real-time model checking. With the assumption of digital clocks, symbolic model checking techniques (like those based on BDDs) can be applied for real-time systems. The problem of model checking real-time systems based on digitization is that the number of tick transitions increases rapidly with the increment of clock upper bounds. In this paper, we propose to improve BDD-based verification for real-time systems using simulation reduction. We show that simulation reduction allows us to verify timed automata with large clock upper bounds and to converge faster to the fixpoint. The presented …
Designing Minimal Effective Normative Systems With The Help Of Lightweight Formal Methods, Jianye Hao, Eunsuk Kang, Jun Sun, Daniel Jackson
Designing Minimal Effective Normative Systems With The Help Of Lightweight Formal Methods, Jianye Hao, Eunsuk Kang, Jun Sun, Daniel Jackson
Research Collection School Of Computing and Information Systems
Normative systems are an important approach to achieving effective coordination among (often an arbitrary number of) agents in multiagent systems. A normative system should be effective in ensuring the satisfaction of a desirable system property, and minimal (i.e., not containing norms that unnecessarily over-constrain the behaviors of agents). Designing or even automatically synthesizing minimal effective normative systems is highly non-trivial. Previous attempts on synthesizing such systems through simulations often fail to generate normative systems which are both minimal and effective. In this work, we propose a framework that facilitates designing of minimal effective normative systems using lightweight formal methods. Given …
A Decomposition Method For Estimating Recursive Logit Based Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
A Decomposition Method For Estimating Recursive Logit Based Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
Research Collection School Of Computing and Information Systems
Fosgerau et al. (2013) recently proposed the recursive logit (RL) model for route choice problems, that can be consistently estimated and easily used for prediction without any sampling of choice sets. Its estimation however requires solving many large-scale systems of linear equations, which can be computationally costly for real data sets. We design a decomposition (DeC) method in order to reduce the number of linear systems to be solved, opening the possibility to estimate more complex RL based models, for instance mixed RL models. We test the performance of the DeC method by estimating the RL model on two networks …
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Research Collection School Of Computing and Information Systems
Product reviews greatly influence purchase decisions in online shopping. A common burden of online shopping is that consumers have to search for the right answers through massive reviews, especially on popular products. Hence, estimating and predicting the helpfulness of reviews become important tasks to directly improve shopping experience. In this paper, we propose a new approach to helpfulness prediction by leveraging aspect analysis of reviews. Our hypothesis is that a helpful review will cover many aspects of a product at different emphasis levels. The first step to tackle this problem is to extract proper aspects. Because related products share common …
Landmark Reranking For Smart Travel Guide Systems By Combining And Analyzing Diverse Media, Junge Shen, Jialie Shen, Tao Mei, Xinbo Gao
Landmark Reranking For Smart Travel Guide Systems By Combining And Analyzing Diverse Media, Junge Shen, Jialie Shen, Tao Mei, Xinbo Gao
Research Collection School Of Computing and Information Systems
Advanced networking technologies and massive online social media have stimulated a booming growth of travel heterogeneous information in recent years. By employing such information, smart travel guide systems, such as landmark ranking systems, have been proposed to offer diverse online travel services. It is essential for a landmark ranking system to structure, analyze, and search the travel heterogeneous information to produce human-expected results. Therefore, currently the most fundamental yet challenging problems can be concluded: 1) how to fuse heterogeneous tourism information and 2) how to model landmark ranking. In this paper, a novel landmark search system is introduced based on …
An Efficient And Expressive Ciphertext-Policy Attribute-Based-Encryption Scheme With Partially Hidden Access Structures, Hui Cui, Deng, Robert H., Guowei Wu, Junzuo Lai
An Efficient And Expressive Ciphertext-Policy Attribute-Based-Encryption Scheme With Partially Hidden Access Structures, Hui Cui, Deng, Robert H., Guowei Wu, Junzuo Lai
Research Collection School Of Computing and Information Systems
A promising solution to protect data privacy in cloud storage services is known as ciphertext-policy attribute-based encryption (CP-ABE). However, in a traditional CP-ABE scheme, a ciphertext is bound with an explicit access structure, which may leak private information about the underlying plaintext in that anyone having access to the ciphertexts can tell the attributes of the privileged recipients by looking at the access structures. A notion called CP-ABE with partially hidden access structures [14, 15, 18, 19, 24] was put forth to address this problem, in which each attribute consists of an attribute name and an attribute value and the …
Efficient Tag Path Authentication Protocol With Less Tag Memory, Hongbing Wang, Yingjiu Li, Zongyang Zhang, Yunlei Zhao
Efficient Tag Path Authentication Protocol With Less Tag Memory, Hongbing Wang, Yingjiu Li, Zongyang Zhang, Yunlei Zhao
Research Collection School Of Computing and Information Systems
Logistical management has been advanced rapidly in these years, taking advantage of the broad connectivity of the Internet. As it becomes an important part of our lives, it also raises many challenging issues, e.g., the counterfeits of expensive goods pose a serious threat to supply chain management. As a result, path authentication becomes especially important in supply chain management, since it helps us maintain object pedigree and supply chain integrity. Meanwhile, tag path authentication must meet a series of security requirements, such as authentication, privacy, and unlinkability. In addition, the authentication protocol must be efficient.In 2011, the first tag path …
Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang
Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we study cross-domain sentiment classification with neural network architectures. We borrow the idea from Structural Correspondence Learning and use two auxiliary tasks to help induce a sentence embedding that supposedly works well across domains for sentiment classification. We also propose to jointly learn this sentence embedding together with the sentiment classifier itself. Experiment results demonstrate that our proposed joint model outperforms several state-of-the-art methods on five benchmark datasets.
An Efficient Privacy-Preserving Outsourced Calculation Toolkit With Multiple Keys, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Jian Weng
An Efficient Privacy-Preserving Outsourced Calculation Toolkit With Multiple Keys, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Jian Weng
Research Collection School Of Computing and Information Systems
In this paper, we propose a toolkit for efficient and privacy-preserving outsourced calculation under multiple encrypted keys (EPOM). Using EPOM, a large scale of users can securely outsource their data to a cloud server for storage. Moreover, encrypted data belonging to multiple users can be processed without compromising on the security of the individual user's (original) data and the final computed results. To reduce the associated key management cost and private key exposure risk in EPOM, we present a distributed two-trapdoor public-key cryptosystem, the core cryptographic primitive. We also present the toolkit to ensure that the commonly used integer operations …
Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo
Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo
Research Collection School Of Computing and Information Systems
Social media provides a convenient way for customers to express their feedback to companies. Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. In this paper, we use a machine learning approach to predict a customer’s feedback behavior based on her first feedback tweet. First, we identify a few categories of customers based on their feedback frequency and the sentiment of the feedback. We identify three main categories: spiteful, one-off, and kind. Next, we build a model to predict the category of a customer given her first feedback. We use profile and …
How To Break An Api: Cost Negotiation And Community Values In Three Software Ecosystems, Christopher Bogart, Christian K\303\244stner, James Herbsleb, Ferdian Thung
How To Break An Api: Cost Negotiation And Community Values In Three Software Ecosystems, Christopher Bogart, Christian K\303\244stner, James Herbsleb, Ferdian Thung
Research Collection School Of Computing and Information Systems
Change introduces conict into software ecosystems: breaking changes may ripple through the ecosystem and trigger rework for users of a package, but often developers can invest additional effort or accept opportunity costs to alleviate or delay downstream costs. We performed a multiple case study of three software ecosystems with different tooling and philosophies toward change, Eclipse, R/CRAN, and Node.js/npm, to understand how developers make decisions about change and change-related costs and what practices, tooling, and policies are used. We found that all three ecosystems differ substantially in their practices and expectations toward change and that those differences can be explained …
On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim
On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The popularity of social media platforms such as Twitter has led to the proliferation of automated bots, creating both opportunities and challenges in information dissemination, user engagements, and quality of services. Past works on profiling bots had been focused largely on malicious bots, with the assumption that these bots should be removed. In this work, however, we find many bots that are benign, and propose a new, broader categorization of bots based on their behaviors. This includes broadcast, consumption, and spam bots. To facilitate comprehensive analyses of bots and how they compare to human accounts, we develop a systematic profiling …
Privacy-Preserving Outsourced Calculation On Floating Point Numbers, Ximeng Liu, Robert H. Deng, Wenxiu Ding, Rongxing Lu
Privacy-Preserving Outsourced Calculation On Floating Point Numbers, Ximeng Liu, Robert H. Deng, Wenxiu Ding, Rongxing Lu
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for privacy-preserving outsourced calculation on floating point numbers (POCF). Using POCF, a user can securely outsource the storing and processing of floating point numbers to a cloud server without compromising on the security of the (original) data and the computed results. In particular, we first present privacy-preserving integer processing protocols for common integer operations. We then present an approach to outsourcing floating point numbers for storage in a privacy-preserving way, and securely processing commonly used floating point number operations on-the-fly. We prove that the proposed POCF achieves the goal of floating point number …
Partitioning Uncertain Workloads, Freddy Chua, Bernardo A. Huberman
Partitioning Uncertain Workloads, Freddy Chua, Bernardo A. Huberman
Research Collection School Of Computing and Information Systems
We present a method for determining the ratio of the tasks when breaking any complex workload in such a way that once the outputs from all tasks are joined, their full completion takes less time and exhibit smaller variance than when running on the undivided workload. To do that, we have to infer the capabilities of the processing unit executing the divided workloads or tasks. We propose a Bayesian Inference algorithm to infer the amount of time each task takes in a way that does not require prior knowledge on the processing unit capability. We demonstrate the effectiveness of this …
Finding Causality And Responsibility For Probabilistic Reverse Skyline Query Non-Answers, Yunjun Gao, Qing Liu, Gang Cheng, Linlin Zhou, Baihua Zheng
Finding Causality And Responsibility For Probabilistic Reverse Skyline Query Non-Answers, Yunjun Gao, Qing Liu, Gang Cheng, Linlin Zhou, Baihua Zheng
Research Collection School Of Computing and Information Systems
Causality and responsibility is an essential tool in the database community for providing intuitive explanations for answers/non-answers to queries. Causality denotes the causes for the answers/non-answers to queries, and responsibility represents the degree of a cause which reflects its influence on the answers/non-answers to queries. In this paper, we study the causality and responsibility problem (CRP) for the non-answers to probabilistic reverse skyline queries (PRSQ). We first formalize CRP on PRSQ, and then, we propose an efficient algorithm termed as CP to compute the causality and responsibility for the non-answers to PRSQ. CP first finds candidate causes, and then, it …
A Study On A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Deng, Robert H., Lingyun Ying, Wei He
A Study On A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Deng, Robert H., Lingyun Ying, Wei He
Research Collection School Of Computing and Information Systems
Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. Existing no-root approaches require users to launch a separate service via Android Debug Bridge (ADB) on an Android device, which would perform user-desired tasks. However, it is unusual for a third-party Android application to work with a separate native service via sockets, and it requires the application developers to have extra knowledge such …
Achieving Ind-Cca Security For Functional Encryption For Inner Products, Shiwei Zhang, Yi Mu, Guomin Yang
Achieving Ind-Cca Security For Functional Encryption For Inner Products, Shiwei Zhang, Yi Mu, Guomin Yang
Research Collection School Of Computing and Information Systems
Functional encryption allows the authorised parties to reveal partial information of the plaintext hidden in a ciphertext while in conventional encryption decryption is all-or-nothing. Focusing on the functionality of inner product evaluation (i.e. given vectors xxxx and yyyy, calculate ⟨xx,yy⟩⟨xx,yy⟩), Abdalla et al. (PKC 2015) proposed a functional encryption scheme for inner product functionality (FE-IP) with s-IND-CPA security. In some recent works by Abdalla et al. (eprint: Report 2016/11) and Agrawal et al. (CRYPTO 2016), IND-CPA secure FE-IP schemes have also been proposed. In order to achieve Indistinguishable under Chosen Ciphertext Attacks (IND-CCA security) for FE-IP, in this paper, we …
Proteus: Computing Disjunctive Loop Summary Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Yang Liu, Wei Le, Xiaohong Li
Proteus: Computing Disjunctive Loop Summary Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Yang Liu, Wei Le, Xiaohong Li
Research Collection School Of Computing and Information Systems
Loops are challenging structures for program analysis, especially when loops contain multiple paths with complex interleaving executions among these paths. In this paper, we first propose a classification of multi-path loops to understand the complexity of the loop execution, which is based on the variable updates on the loop conditions and the execution order of the loop paths. Secondly, we propose a loop analysis framework, named Proteus, which takes a loop program and a set of variables of interest as inputs and summarizes path-sensitive loop effects on the variables. The key contribution is to use a path dependency automaton (PDA) …
One-Round Attribute-Based Key Exchange In The Multi-Party Setting, Yangguang Tian, Guomin Yang, Yi Mu, Kaitai Liang, Yong Yu
One-Round Attribute-Based Key Exchange In The Multi-Party Setting, Yangguang Tian, Guomin Yang, Yi Mu, Kaitai Liang, Yong Yu
Research Collection School Of Computing and Information Systems
Attribute-based authenticated key exchange (AB-AKE) is a useful primitive that allows a group of users to establish a shared secret key and at the same time enables fine-grained access control. A straightforward approach to design an AB-AKE protocol is to extend a key exchange protocol using attribute-based authentication technique. However, insider security is a challenge security issue for AB-AKE in the multi-party setting and cannot be solved using the straightforward approach. In addition, many existing key exchange protocols for the multi-party setting (e.g., the well-known Burmester-Desmedt protocol) require multiple broadcast rounds to complete the protocol. In this paper, we propose …
A Novel Covert Channel Detection Method In Cloud Based On Xsrm And Improved Event Association Algorithm, Lina Wang, Weijie Liu, Neeraj Kumar, Debiao He, Cheng Tan, Debin Gao
A Novel Covert Channel Detection Method In Cloud Based On Xsrm And Improved Event Association Algorithm, Lina Wang, Weijie Liu, Neeraj Kumar, Debiao He, Cheng Tan, Debin Gao
Research Collection School Of Computing and Information Systems
Covert channel is a major threat to the information system security and commonly found in operating systems, especially in cloud computing environment. Owing to the characteristics in cloud computing environment such as resources sharing and logic boundaries, covert channels become more varied and difficult to find. Focusing on those problems, this paper presents a universal method for detecting covert channel automatically. To achieve a global detection, we leveraged a virtual machine event record mechanism in hypervisor to gather necessary metadata. Combining the shared resources matrix methodology with events association mechanism, we proposed a distinctive algorithm that can accurately locate and …
What Permissions Should This Android App Request?, Lingfeng Bao, David Lo, Xin Xia, Shanping Li
What Permissions Should This Android App Request?, Lingfeng Bao, David Lo, Xin Xia, Shanping Li
Research Collection School Of Computing and Information Systems
As Android is one of the most popular open source mobile platforms, ensuring security and privacy of Android applications is very important. Android provides a permission mechanism which requires developers to declare sensitive resources their applications need, and users need to agree with this request when they install (for Android API level 22 or lower) or run (for Android API level 23) these applications. Although Android provides very good official documents to explain how to properly use permissions, unfortunately misuses even for the most popular permissions have been reported. Recently, Karim et al. propose an association rule mining based approach …
Who Is Who In The Mailing List? Comparing Six Disambiguation Heuristics To Identify Multiple Addresses Of A Participant, Igor Scaliante Wiese, José Teodoro Da Silva, Igor Steinmacher, Christoph Treude, Marco Aurélio Gerosa
Who Is Who In The Mailing List? Comparing Six Disambiguation Heuristics To Identify Multiple Addresses Of A Participant, Igor Scaliante Wiese, José Teodoro Da Silva, Igor Steinmacher, Christoph Treude, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Many software projects adopt mailing lists for the communication of developers and users. Researchers have been mining the history of such lists to study communities' behavior, organization, and evolution. A potential threat of this kind of study is that users often use multiple email addresses to interact in a single mailing list. This can affect the results and tools, when, for example, extracting social networks. This issue is particularly relevant for popular and long-term Open Source Software (OSS) projects, which attract participation of thousands of people. Researchers have proposed heuristics to identify multiple email addresses from the same participant, however …
Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu
Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu
Research Collection School Of Computing and Information Systems
A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can …
Determining Quality- And Energy-Aware Multiple Contexts In Pervasive Computing Environments, Nirmalya Roy, Archan Misra, Sajal K. Das, Christine Julien
Determining Quality- And Energy-Aware Multiple Contexts In Pervasive Computing Environments, Nirmalya Roy, Archan Misra, Sajal K. Das, Christine Julien
Research Collection School Of Computing and Information Systems
In pervasive computing environments, understanding the context of an entity is essential for adapting the application behavior to changing situations. In our view, context is a high-level representation of a user or entity's state and can capture location, activities, social relationships, capabilities, etc. Inherently, however, these high-level context metrics are difficult to capture using uni-modal sensors only and must therefore be inferred using multi-modal sensors. A key challenge in supporting context-aware pervasive computing is how to determine multiple high-level context metrics simultaneously and energy-efficiently using low-level sensor data streams collected from the environment and the entities present therein. A key …
Integrated Software Fingerprinting Via Neural-Network-Based Control Flow Obfuscation, Haoyu Ma, Ruiqi Li, Xiaoxu Yu, Chunfu Jia, Debin Gao
Integrated Software Fingerprinting Via Neural-Network-Based Control Flow Obfuscation, Haoyu Ma, Ruiqi Li, Xiaoxu Yu, Chunfu Jia, Debin Gao
Research Collection School Of Computing and Information Systems
Dynamic software fingerprinting has been an important tool in fighting against software theft and pirating by embedding unique fingerprints into software copies. However, existing work uses methods from dynamic software watermarking as direct solutions in which secret marks are inside rather independent code modules attached to the software. This results in an intrinsic weakness against targeted collusive attacks since differences among software copies correspond directly to the fingerprint-related components. In this paper, we suggest a novel mode of dynamic fingerprinting called integrated fingerprinting, of which the goal is to ensure all fingerprinted software copies possess identical behaviors at semantic level. …