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Non-Fungible Tokens (or, for short, NFT) establish the ownership and the authenticity of digital assets. Regardless the high security levels provided by blockchain, are not excluded the cases where the ownership of a digital object may be claimed ...

Malicious users may tamper forensic digital images for various reasons including among others the creation of false evidences. In this work we propose a tamper detection and localization technique for forensic digital images detecting whether a ...

Watermarking is a method for the verification of the authenticity of a digital object. In this work we investigate the watermarking of audio signals utilizing watermarked images. We present a multiple watermarking scheme for the watermarking of digital ...

In this work, we present an algorithmic technique for text indexing based on the utilization of classes of synonyms. The method proposed in this study utilizes a set of synonym classes in order to develop a more abstract representation of a given text ...

In this paper we present an integrated graph-based framework that utilizes relations between groups of System-calls, in order to detect whether an unknown software sample is malicious or benign, and to a further extent to classify it to a known malware ...

In this paper we present a graph-based framework that, utilizing relations between groups of System-calls, detects whether an unknown software sample is malicious or benign, and classifies a malicious software to one of a set of known malware families. In ...

In this paper, we present the development of an algorithmic framework for the behavioral detection of malicious software utilizing a set of measurements to explore the structural characteristics of behavioral graphs. We first present the construction of ...

In this work we propose a graph-based model that, utilizing relations between groups of System-calls, distinguishes malicious from benign software samples utilizing a behavioral graph representing their interaction with the operating system. More ...

In this paper, we propose a graph-based algorithmic technique for malware detection, utilizing the System-call Dependency Graphs (ScDG) obtained through taint analysis traces. We leverage the grouping of system-calls into system-call groups with respect ...

The spread of malicious software among computing devices nowadays poses a major threat to the systems security. Since both the use of mobile devices and the growth of malwares propagation increase rapidly, we are interested in investigating how the time ...

As long as the use of distributed systems and Cloud Computing is significantly increasing, the amount of threats concerning the security of such systems and the data stored in them set great challenges on the application of Trusted Computing. In this ...

We study the propagation of a malicious software in a network of mobile devices, which are moving in a specific city area, and establish time bounds for the activation of a counter-measure (i.e., an antivirus or a cleaner) in order to prevent pandemic. ...

In this paper we present a graph-based algorithmic technique for classifying unknown malware samples. In order for our model to be resistant against strong mutation of malicious software, we apply our classification technique on a weighted directed ...

In this paper, we propose a graph-based algorithmic technique for 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 ...