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Patkos T.,FORTH ICS | Bikakis A.,University College London | Flouris G.,FORTH ICS
Principles of Knowledge Representation and Reasoning: Proceedings of the 15th International Conference, KR 2016 | Year: 2016

Users' reviews, comments and votes on the Social Web form the modern version of word-of-mouth communication, which has a huge impact on people's habits and businesses. Nonetheless, there are only few attempts to formally model and analyze them using Computational Models of Argument, which achieved a first significant step in bringing these two fields closer. In this paper, we attempt their further integration by formalizing standard features of the Social Web, such as commentary and social voting, and by proposing methods for the evaluation of the comments' quality and acceptance. Copyright © 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.


Goktas E.,VU University Amsterdam | Athanasopoulos E.,FORTH ICS | Bos H.,VU University Amsterdam | Portokalidis G.,Stevens Institute of Technology
Proceedings - IEEE Symposium on Security and Privacy | Year: 2014

As existing defenses like ASLR, DEP, and stack cookies are not sufficient to stop determined attackers from exploiting our software, interest in Control Flow Integrity (CFI) is growing. In its ideal form, CFI prevents flows of control that were not intended by the original program, effectively putting a stop to exploitation based on return oriented programming (and many other attacks besides). Two main problems have prevented CFI from being deployed in practice. First, many CFI implementations require source code or debug information that is typically not available for commercial software. Second, in its ideal form, the technique is very expensive. It is for this reason that current research efforts focus on making CFI fast and practical. Specifically, much of the work on practical CFI is applicable to binaries, and improves performance by enforcing a looser notion of control flow integrity. In this paper, we examine the security implications of such looser notions of CFI: are they still able to prevent code reuse attacks, and if not, how hard is it to bypass its protection? Specifically, we show that with two new types of gadgets, return oriented programming is still possible. We assess the availability of our gadget sets, and demonstrate the practicality of these results with a practical exploit against Internet Explorer that bypasses modern CFI implementations. © 2014 IEEE.


Polychronakis M.,Columbia University | Anagnostakis K.G.,Niometrics | Markatos E.P.,FORTH ICS
Proceedings - Annual Computer Security Applications Conference, ACSAC | Year: 2010

A promising method for the detection of previously unknown code injection attacks is the identification of the shellcode that is part of the attack vector using payload execution. Existing systems based on this approach rely on the self-decrypting behavior of polymorphic code and can identify only that particular class of shellcode. Plain, and more importantly, metamorphic shellcode do not carry a decryption routine nor exhibit any self-modifications and thus both evade existing detection systems. In this paper, we present a comprehensive shellcode detection technique that uses a set of runtime heuristics to identify the presence of shellcode in arbitrary data streams. We have identified fundamental machine-level operations that are inescapably performed by different shellcode types, based on which we have designed heuristics that enable the detection of plain and metamorphic shellcode regardless of the use of self-decryption. We have implemented our technique in Gene, a code injection attack detection system based on passive network monitoring. Our experimental evaluation and real-world deployment show that Gene can effectively detect a large and diverse set of shellcode samples that are currently missed by existing detectors, while so far it has not generated any false positives. © 2010 ACM.


Papavasileiou V.,University of Crete | Flouris G.,FORTH ICS | Fundulaki I.,FORTH ICS | Kotzinos D.,TEI of Serres | Christophides V.,University of Crete
ACM Transactions on Database Systems | Year: 2013

With the increasing use of Web 2.0 to create, disseminate, and consume large volumes of data, more and more information is published and becomes available for potential data consumers, that is, applications/services, individual users and communities, outside their production site. The most representative example of this trend is Linked Open Data (LOD), a set of interlinked data and knowledge bases. The main challenge in this context is data governance within loosely coordinated organizations that are publishing added-value interlinked data on the Web, bringing together issues related to data management and data quality, in order to support the full lifecycle of data production, consumption, and management. In this article, we are interested in curation issues for RDF(S) data, which is the default data model for LOD. In particular, we are addressing change management for RDF(S) data maintained by large communities (scientists, librarians, etc.) which act as curators to ensure high quality of data. Such curated Knowledge Bases (KBs) are constantly evolving for various reasons, such as the inclusion of new experimental evidence or observations, or the correction of erroneous conceptualizations. Managing such changes poses several research problems, including the problem of detecting the changes (delta) between versions of the same KB developed and maintained by different groups of curators, a crucial task for assisting them in understanding the involved changes. This becomes all the more important as curated KBs are interconnected (through copying or referencing) and thus changes need to be propagated from one KB to another either within or across communities. This article addresses this problem by proposing a change language which allows the formulation of concise and intuitive deltas. The language is expressive enough to describe unambiguously any possible change encountered in curated KBs expressed in RDF(S), and can be efficiently and deterministically detected in an automated way. Moreover, we devise a change detection algorithm which is sound and complete with respect to the aforementioned language, and study appropriate semantics for executing the deltas expressed in our language in order to move backwards and forwards in a multiversion repository, using only the corresponding deltas. Finally, we evaluate through experiments the effectiveness and efficiency of our algorithms using real ontologies from the cultural, bioinformatics, and entertainment domains. © 2013 ACM.


Petsas T.,FORTH ICS | Papadogiannakis A.,FORTH ICS | Polychronakis M.,Columbia University | Markatos E.P.,FORTH ICS | Karagiannis T.,Microsoft
Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC | Year: 2013

Mobile applications (apps) have been gaining rising popularity due to the advances in mobile technologies and the large increase in the number of mobile users. Consequently, several app distribution platforms, which provide a new way for developing, downloading, and updating software applications in modern mobile devices, have recently emerged. To better understand the download patterns, popularity trends, and development strategies in this rapidly evolving mobile app ecosystem, we systematically monitored and analyzed four popular third-party Android app marketplaces. Our study focuses on measuring, analyzing, and modeling the app popularity distribution, and explores how pricing and revenue strategies affect app popularity and developers' income. Our results indicate that unlike web and peer-to-peer file sharing workloads, the app popularity distribution deviates from commonly observed Zipf-like models. We verify that these deviations can be mainly attributed to a new download pattern, to which we refer as the clustering effect. We validate the existence of this effect by revealing a strong temporal affinity of user downloads to app categories. Based on these observations, we propose a new formal clustering model for the distribution of app downloads, and demonstrate that it closely fits measured data. Moreover, we observe that paid apps follow a different popularity distribution than free apps, and show how free apps with an ad-based revenue strategy may result in higher financial benefits than paid apps. We believe that this study can be useful to appstore designers for improving content delivery and recommendation systems, as well as to app developers for selecting proper pricing policies to increase their income. Copyright 2013 ACM.


Vasiliadis G.,FORTH ICS | Polychronakis M.,Columbia University | Ioannidis S.,FORTH ICS
Proceedings of the ACM Conference on Computer and Communications Security | Year: 2011

Network intrusion detection systems are faced with the challenge of identifying diverse attacks, in extremely high speed networks. For this reason, they must operate at multi-Gigabit speeds, while performing highly-complex per-packet and per-flow data processing. In this paper, we present a multi-parallel intrusion detection architecture tailored for high speed networks. To cope with the increased processing throughput requirements, our system parallelizes network traffic processing and analysis at three levels, using multi-queue NICs, multiple CPUs, and multiple GPUs. The proposed design avoids locking, optimizes data transfers between the different processing units, and speeds up data processing by mapping different operations to the processing units where they are best suited. Our experimental evaluation shows that our prototype implementation based on commodity off-the-shelf equipment can reach processing speeds of up to 5.2 Gbit/s with zero packet loss when analyzing traffic in a real network, whereas the pattern matching engine alone reaches speeds of up to 70 Gbit/s, which is an almost four times improvement over prior solutions that use specialized hardware. © 2011 ACM.


Kondylakis H.,FORTH ICS | Plexousakis D.,FORTH ICS
Proceedings of the ACM SIGMOD International Conference on Management of Data | Year: 2011

The evolution of ontologies is an undisputed necessity in ontology-based data integration. Yet, few research efforts have focused on addressing the need to reflect ontology evolution onto the underlying data integration systems. We present Exelixis, a web platform that enables query answering over evolving ontologies without mapping redefinition. This is achieved by rewriting queries among ontology versions. First, changes between ontologies are automatically detected and described using a high level language of changes. Those changes are interpreted as sound global-as-view (GAV) mappings. Then query expansion is applied in order to consider constraints from the ontology and unfolding to apply the GAV mappings. Whenever equivalent rewritings cannot be produced we a) guide query redefinition and/or b) provide the best "over- approximations", i.e. the minimally-containing and minimally-generalized rewritings. For the demonstration we will use four versions of the CIDOC-CRM ontology and real user queries to show the functionality of the system. Then we will allow conference participants to directly interact with the system to test its capabilities. © 2011 Authors.


Bushkov V.,Ecole Polytechnique Federale de Lausanne | Fatourou P.,University of Crete | Fatourou P.,Ecole Polytechnique Federale de Lausanne | Dziuma D.,FORTH ICS | Guerraoui R.,Ecole Polytechnique Federale de Lausanne
Annual ACM Symposium on Parallelism in Algorithms and Architectures | Year: 2014

We show that it is impossible to design a transactional memory system which ensures parallelism, i.e. transactions do not need to synchronize unless they access the same application objects, while ensuring very little consistency, i.e. a consistency condition, called weak adaptive consistency, introduced here and which is weaker than snapshot isolation, processor consistency, and any other consistency condition stronger than them (such as opacity, serializability, causal serializability, etc.), and very little liveness, i.e. that transactions eventually commit if they run solo.


Vasiliadis G.,FORTH ICS | Athanasopoulos E.,FORTH ICS | Polychronakis M.,Columbia University | Ioannidis S.,FORTH ICS
Proceedings of the ACM Conference on Computer and Communications Security | Year: 2014

Protecting the confidentiality of cryptographic keys in the event of partial or full system compromise is crucial for containing the impact of attacks. The Heartbleed vulnerability of April 2014, which allowed the remote leakage of secret keys from HTTPS web servers, is an indicative example. In this paper we present PixelVault, a system for keeping cryptographic keys and carrying out cryptographic operations exclusively on the GPU, which allows it to protect secret keys from leakage even in the event of full system compromise. This is possible by exposing secret keys only in GPU registers, keeping PixelVault's critical code in the GPU instruction cache, and preventing any access to both of them from the host. Due to the non-preemptive execution mode of the GPU, an adversary that has full control of the host cannot tamper with PixelVault's GPU code, but only terminate it, in which case all sensitive data is lost. We have implemented a PixelVault-enabled version of the OpenSSL library that allows the protection of existing applications with minimal modifications. Based on the results of our evaluation, PixelVault not only provides secure key storage using commodity hardware, but also significantly speeds up the processing throughput of cryptographic operations for server applications. Copyright is held by the owner/author(s).


Papadogiannakis A.,FORTH ICS | Polychronakis M.,Columbia University | Markatos E.P.,FORTH ICS
Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC | Year: 2013

Many network monitoring applications must analyze traffic beyond the network layer to allow for connection-oriented analysis, and achieve resilience to evasion attempts based on TCP segmentation. However, existing network traffic capture frameworks provide applications with just raw packets, and leave complex operations like flow tracking and TCP stream reassembly to application developers. This gap leads to increased application complexity, longer development time, and most importantly, reduced performance due to excessive data copies between the packet capture subsystem and the stream processing module. This paper presents the Stream capture library (Scap), a network monitoring framework built from the ground up for stream-oriented traffic processing. Based on a kernel module that directly handles flow tracking and TCP stream reassembly, Scap delivers to userlevel applications flow-level statistics and reassembled streams by minimizing data movement operations and discarding uninteresting traffic at early stages, while it inherently supports parallel processing on multi-core architectures, and uses advanced capabilities of modern network cards. Our experimental evaluation shows that Scap can capture all streams for traffic rates two times higher than other stream reassembly libraries, and can process more than five times higher traffic loads when eight cores are used for parallel stream processing in a pattern matching application. Copyright 2013 ACM.

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