A survey of static software watermarking

Hamilton, James; Danicic, Sebastian

doi:10.1109/worldcis17046.2011.5749891

Cited by 25 publications

(9 citation statements)

References 56 publications

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“…First patented software watermarking efforts used the idea of code replacement; that is, the watermark value replaced the pre-decided part of code [29], [30]. Monden et al have explored watermarking of java programs and proposed several techniques by swapping byte code within dummy methods (implemented as jmark) [31], [32].…”

Section: G Code Replacement Algorithmsmentioning

confidence: 99%

KeySplitWatermark: Zero Watermarking Algorithm for Software Protection Against Cyber-Attacks

et al. 2020

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Cyber-attacks are evolving at a disturbing rate. Data breaches, ransomware attacks, cryptojacking, malware and phishing attacks are now rampant. In this era of cyber warfare, the software industry is also growing with an increasing number of software being used in all domains of life. This evolution has added to the problems of software vendors and users where they have to prevent a wide range of attacks. Existing watermark detection solutions have a low detection rate in the software. In order to address this issue, this paper proposes a novel blind Zero code based Watermark detection approach named KeySplitWatermark, for the protection of software against cyber-attacks. The algorithm adds watermark logically into the code utilizing the inherent properties of code and gives a robust solution. The embedding algorithm uses keywords to make segments of the code to produce a key-dependent on the watermark. The extraction algorithms use this key to remove watermark and detect tampering. When tampering increases to a certain user-defined threshold, the original software code is restored making it resilient against attacks. KeySplitWatermark is evaluated on tampering attacks on three unique samples with two distinct watermarks. The outcomes show that the proposed approach reports promising results against cyber-attacks that are powerful and viable. We compared the performance of our proposal with state-of-the-art works using two different software codes. Our results depict that KeySplitWatermark correctly detects watermarks, resulting in up to 15.95 and 17.43 percent reduction in execution time on given code samples with no increase in program size and independent of watermark size.

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Section: G Code Replacement Algorithmsmentioning

confidence: 99%

KeySplitWatermark: Zero Watermarking Algorithm for Software Protection Against Cyber-Attacks

et al. 2020

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“…Wang, et al (2018) encode the watermark by causing a program exception and monitoring the exception handling. Academics have also concentrated work in dynamic watermarking by making a software fingerprint distinct in terms of data structures (Kamela and Albluwib 2009) or using graph theory (Bento et al 2019) (Hamilton and Danicic 2020) (Colberg, Huntworth et al 2004).…”

Section: Related Workmentioning

confidence: 99%

Analyzing the Performance of Block-Splitting in LLVM Fingerprinting

Mahoney

Sigillito

Smolinski

et al. 2022

iccws

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This paper expands and builds upon previous work reported at the 2021 ICCWS concerning Executable Steganography and software intellectual property protection via fingerprinting. Software fingerprinting hides some type of unique identification into the binary program artifact so that a proof of ownership can be established if the artifact turns up elsewhere. In our previous work, it was noted that “fingerprints are a special case of watermarks, with the difference being that each fingerprint is unique to each copy of a program”. This prior work emphasized making the fingerprint independent of the machine architecture; that is, performing the operations on an intermediate representation (IR). LLVM was used as the target IR, which is a compiler “middleware” language that is then converted into machine code in a later step. Both a static fingerprinting method, where the serial number or data is embedded and visible by inspection, and a dynamic method, where the code must be executed, were explored. The dynamic method only incurs an overhead if the proof code is executed and has very minimal impact if the proof code is not executed. However, the static fingerprint was accomplished by shuffling the order of basic blocks in the software in a manner that represents the serial number data, and this would have an impact on both the execution speed and the program size. This paper reports on subsequent research to improve the quantity of data which could be encoded by rearranging the blocks in a program and increasing the number of blocks by splitting them into smaller fragments, thus allowing for more potential orderings and therefore more data. Contributions in the currentwork are twofold. First, the experimental infrastructure has been refined so that the fingerprinting actions take place within the compiler itself as opposed to an external LLVM parser. Second, code has been introduced to limit the upper bound on the size of a block and to split blocks which are larger than this upper bound. We evaluate the resultant overhead and performance of the block splitting method and report negligible increases based on the block-splitting technique.

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“…Software watermarking involves embedding a unique identifier within a piece of software, to discourage the copying of software [67,75,77]. Watermarking does not prevent copyright infringement but instead discourages it by providing a means to identify the creator of a piece of software and/or the origin of copied software.…”

Section: Watermark Communitiesmentioning

confidence: 99%

“…These visualisations might also be useful for locating software watermarks [38,[75][76][77] or malware [36,166] within programs -allowing us to define better software watermarks, or easily remove malware.…”

Section: Visualising Software Dependence With Slice Graphsmentioning

confidence: 99%