Dynamic Software Birthmark for Java Based on Heap Memory Analysis

Chan, Patrick; Hui, Lucas Chi Kwong; Yiu, Siu-Ming

doi:10.1007/978-3-642-24712-5_8

Cited by 12 publications

(3 citation statements)

References 10 publications

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“…Specifically in Java, there have been several research uses of HPROF data-e.g., most directly for different kinds of heap visualization [Aftandilian et al 2010;Reiss 2009]. Other dynamic analyses use heap profiling data to check aliasing properties [Potanin et al 2004], analyze synchronization performance [Hofer et al 2015], generate software birthmarks [Chan et al 2011], or diagnose memory leaks [Maxwell et al 2010].…”

Section: Related Workmentioning

confidence: 99%

Heaps don't lie: countering unsoundness with heap snapshots

Grech

Fourtounis

Francalanza

et al. 2017

Proc. ACM Program. Lang.

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Static analyses aspire to explore all possible executions in order to achieve soundness. Yet, in practice, they fail to capture common dynamic behavior. Enhancing static analyses with dynamic information is a common pattern, with tools such as Tamiflex. Past approaches, however, miss significant portions of dynamic behavior, due to native code, unsupported features (e.g., invokedynamic or lambdas in Java), and more. We present techniques that substantially counteract the unsoundness of a static analysis, with virtually no intrusion to the analysis logic. Our approach is reified in the HeapDL toolchain and consists in taking whole-heap snapshots during program execution, that are further enriched to capture significant aspects of dynamic behavior, regardless of the causes of such behavior. The snapshots are then used as extra inputs to the static analysis. The approach exhibits both portability and significantly increased coverage. Heap information under one set of dynamic inputs allows a static analysis to cover many more behaviors under other inputs. A HeapDL-enhanced static analysis of the DaCapo benchmarks computes 99.5% (median) of the call-graph edges of unseen dynamic executions (vs. 76.9% for the Tamiflex tool).

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Section: Related Workmentioning

confidence: 99%

Heaps don't lie: countering unsoundness with heap snapshots

Grech

Fourtounis

Francalanza

et al. 2017

Proc. ACM Program. Lang.

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“…Kakimoto et al [ 12 ] analyzed the birthmark similarities in ArgoUML and visualized them using multidimensional scaling. Chan et al [ 13 ] proposed a dynamic software birthmark system for systems designed in Java based on the object reference graph. The method was evaluated for huge programs and most of them were megabytes in size.…”

Section: Related Workmentioning

confidence: 99%

A Novel Rules Based Approach for Estimating Software Birthmark

Nazir

Shahzad

Khan

et al. 2015

The Scientific World Journal

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Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark.

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“…Software watermark and fingerprint have been used for a long time with the realization but these techniques have some limitations. Some of the researchers and practitioners of industry are using forward-looking versions of software watermark [1][2][3][4][5][6][7][8][9][10][11][12], fingerprints [13,14], software clone [15,16], and software birthmark [17][18][19][20][21][22][23][24][25][26][27][28][29]. Detection of plagiarism is relevant area to these mentioned software detection methods which are used for source code theft and discovery of similarities among the original and duplicated source codes [30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Modelling Features-Based Birthmarks for Security of End-to-End Communication System

Nazir

Khan

et al. 2020

Security and Communication Networks

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Feature-based software birthmark is an essential property of software that can be used for the detection of software theft and many other purposes like to assess the security in end-to-end communication systems. Research on feature-based software birthmark shows that using the feature-based software birthmark joint with the practice of software birthmark estimation together can deliver a right and influential method for detecting software piracy and the amount of piracy done by a software. This can also guide developers in improving security of end-to-end communication system. Modern day software industry and systems are in demand to have an unbiased method for comparing the features-based birthmark of software competently, and more concretely for the detecting software piracy and assessing the security of end-to-end communication systems. In this paper, we proposed a mathematical model, which is based on a differential system, to present feature-based software birthmark. The model presented in this paper provides an exclusive way for the features-based birthmark of software and then can be used for comparing birthmark and assessing security of end-to-end communication systems. The results of this method show that the proposed model is efficient in terms of effectiveness and correctness for the features-based software birthmark comparison and security assessment purposes.

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Dynamic Software Birthmark for Java Based on Heap Memory Analysis

Cited by 12 publications

References 10 publications

Heaps don't lie: countering unsoundness with heap snapshots

Heaps don't lie: countering unsoundness with heap snapshots

A Novel Rules Based Approach for Estimating Software Birthmark

Modelling Features-Based Birthmarks for Security of End-to-End Communication System

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