Profesor DR Milan D. Petković (1906-1987)

Babić, Rade R.; Živić, Radoslav; Stanković-Babić, Gordana; Milošević, Zoran; Mitrović, Vladimir

doi:10.5633/amm.2012.0311s

Cited by 3 publications

(7 citation statements)

References 0 publications

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“…Finally, Babic et al [3] achieved the malware detection by k-testable tree automata inference from system-call data flow dependence graphs. To this point we ought to underline that in this work the authors use the same data-set that we borrow from Domagoj Babic's web-page [2]. Thus, this work provides a fair instance to compare our model's results.…”

Section: Detection Resultsmentioning

confidence: 99%

“…Table 1. (a) System-calls appeared during the execution of a program π from a malware family Hupigon, (b) System-call dependencies [2].…”

Section: Id System-call Namementioning

confidence: 99%

“…Next, we illustrate a simple example that includes the system-call traces obtained through dynamic taint analysis [3] during the execution of a sample from malware family Hupigon, downloaded from Domagoj Babic's personal webpage [2], and we explain how the ScD graph is constructed after the whole process. Observing the data from the Table 1, we can see the construction of the ScD graph D[π] that is a directed acyclic graph (dag); see, Figure 1.…”

Section: Id System-call Namementioning

confidence: 99%

“…Additionally, it is of major importance to mention that we do not perform any taint malware analysis on the samples due to the risk posed to the systems connected to the same network. Thus, we downloaded the initial Systemcall Dependency Graphs produced by taint analysis from the web-page of Domagoj Babic [2] and transformed each sample's ScD graph D[π] into GrD graph D * [π], based on the grouping of system-calls presented in Table 2. The set F of the 48 malware families along with their sizes (i.e., number of members) are listed in Table 4.…”

Section: Experimental Designmentioning

confidence: 99%

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A graph-based model for malicious code detection exploiting dependencies of system-call groups

Nikolopoulos

Polenakis

2015

Proceedings of the 16th International Conference on Computer Systems and Technologies

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In this paper we present an elaborated graph-based algorithmic technique for efficient malware detection. More precisely, we utilize the system-call dependency graphs (or, for short ScD graphs), obtained by capturing taint analysis traces and a set of various similarity metrics in order to detect whether an unknown test sample is a malicious or a benign one. For the sake of generalization, we decide to empower our model against strong mutations by applying our detection technique on a weighted directed graph resulting from ScD graph after grouping disjoint subsets of its vertices. Additionally, we have developed a similarity metric, which we call NP-similarity, that combines qualitative, quantitative, and relational characteristics that are spread among the members of known malware families to archives a clear distinction between graphrepresentations of malware and the ones of benign software. Finally, we evaluate our detection model and compare our results against the results achieved by a variety of techniques proving the potentials of our model.

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Section: Detection Resultsmentioning

confidence: 99%

“…Table 1. (a) System-calls appeared during the execution of a program π from a malware family Hupigon, (b) System-call dependencies [2].…”

Section: Id System-call Namementioning

confidence: 99%

Section: Id System-call Namementioning

confidence: 99%

Section: Experimental Designmentioning

confidence: 99%

See 2 more Smart Citations

A graph-based model for malicious code detection exploiting dependencies of system-call groups

Nikolopoulos

Polenakis

2015

Proceedings of the 16th International Conference on Computer Systems and Technologies

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“…Sindrom (grčki: συνδρομή -uspeti zajedno; la tinski: syndroma) u kliničkoj medicini predstavlja skup me đusobno povezanih simptoma (znakova) koji čine jednu koherentnu nozološk ucelinu (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16). Sindrom či ne najmanje tri međusobno povezana simptoma koji se uvek javljaju zajedno obrazujući "klinički trija ssimptoma", mada sindrom mogu da obrazuju i više simptoma.…”

Section: Uvodunclassified

Radiological picture of ophthalmic syndrome

Babić¹,

Stanković-Babić²,

Govedarović³

et al. 2020

Medicinska reč

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It's common for the syndromes indicate to the author or authors who discovered them. The paper aims to show the image of X-rays and ophthalmic syndrome and to point out to those who can be recognized by the proper radiological and ophthalmologic examination. The work is based on knowledge and experience of the author and co-author of the acquired long experience in the profession, acquired many years of ophthalmology and radiological material, the papers presented in the relevant national and international journals, history and local and foreign literary press. Are shown in - Syndrom Stuger-Weber-Krabbe, Syndrome Wyburn-Mason, Syndrome Von Hippel-Lindau, Syndrome Crouzon, Syndrome Apertand Syndrome Saethre-Chotzen. The authors conclude that ophthalmic syndromes have their own specificity in radiologically-ophthalmologic image.

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