1,956 research outputs found
Cyber Threat Intelligence : Challenges and Opportunities
The ever increasing number of cyber attacks requires the cyber security and
forensic specialists to detect, analyze and defend against the cyber threats in
almost realtime. In practice, timely dealing with such a large number of
attacks is not possible without deeply perusing the attack features and taking
corresponding intelligent defensive actions, this in essence defines cyber
threat intelligence notion. However, such an intelligence would not be possible
without the aid of artificial intelligence, machine learning and advanced data
mining techniques to collect, analyse, and interpret cyber attack evidences. In
this introductory chapter we first discuss the notion of cyber threat
intelligence and its main challenges and opportunities, and then briefly
introduce the chapters of the book which either address the identified
challenges or present opportunistic solutions to provide threat intelligence.Comment: 5 Page
RADIS: Remote Attestation of Distributed IoT Services
Remote attestation is a security technique through which a remote trusted
party (i.e., Verifier) checks the trustworthiness of a potentially untrusted
device (i.e., Prover). In the Internet of Things (IoT) systems, the existing
remote attestation protocols propose various approaches to detect the modified
software and physical tampering attacks. However, in an interoperable IoT
system, in which IoT devices interact autonomously among themselves, an
additional problem arises: a compromised IoT service can influence the genuine
operation of other invoked service, without changing the software of the
latter. In this paper, we propose a protocol for Remote Attestation of
Distributed IoT Services (RADIS), which verifies the trustworthiness of
distributed IoT services. Instead of attesting the complete memory content of
the entire interoperable IoT devices, RADIS attests only the services involved
in performing a certain functionality. RADIS relies on a control-flow
attestation technique to detect IoT services that perform an unexpected
operation due to their interactions with a malicious remote service. Our
experiments show the effectiveness of our protocol in validating the integrity
status of a distributed IoT service.Comment: 21 pages, 10 figures, 2 table
Know Your Enemy: Stealth Configuration-Information Gathering in SDN
Software Defined Networking (SDN) is a network architecture that aims at
providing high flexibility through the separation of the network logic from the
forwarding functions. The industry has already widely adopted SDN and
researchers thoroughly analyzed its vulnerabilities, proposing solutions to
improve its security. However, we believe important security aspects of SDN are
still left uninvestigated. In this paper, we raise the concern of the
possibility for an attacker to obtain knowledge about an SDN network. In
particular, we introduce a novel attack, named Know Your Enemy (KYE), by means
of which an attacker can gather vital information about the configuration of
the network. This information ranges from the configuration of security tools,
such as attack detection thresholds for network scanning, to general network
policies like QoS and network virtualization. Additionally, we show that an
attacker can perform a KYE attack in a stealthy fashion, i.e., without the risk
of being detected. We underline that the vulnerability exploited by the KYE
attack is proper of SDN and is not present in legacy networks. To address the
KYE attack, we also propose an active defense countermeasure based on network
flows obfuscation, which considerably increases the complexity for a successful
attack. Our solution offers provable security guarantees that can be tailored
to the needs of the specific network under consideratio
To NACK or not to NACK? Negative Acknowledgments in Information-Centric Networking
Information-Centric Networking (ICN) is an internetworking paradigm that
offers an alternative to the current IP\nobreakdash-based Internet
architecture. ICN's most distinguishing feature is its emphasis on information
(content) instead of communication endpoints. One important open issue in ICN
is whether negative acknowledgments (NACKs) at the network layer are useful for
notifying downstream nodes about forwarding failures, or requests for incorrect
or non-existent information. In benign settings, NACKs are beneficial for ICN
architectures, such as CCNx and NDN, since they flush state in routers and
notify consumers. In terms of security, NACKs seem useful as they can help
mitigating so-called Interest Flooding attacks. However, as we show in this
paper, network-layer NACKs also have some unpleasant security implications. We
consider several types of NACKs and discuss their security design requirements
and implications. We also demonstrate that providing secure NACKs triggers the
threat of producer-bound flooding attacks. Although we discuss some potential
countermeasures to these attacks, the main conclusion of this paper is that
network-layer NACKs are best avoided, at least for security reasons.Comment: 10 pages, 7 figure
ODIN: Obfuscation-based privacy-preserving consensus algorithm for Decentralized Information fusion in smart device Networks
The large spread of sensors and smart devices in urban infrastructures are motivating research in the area of the Internet of Things (IoT) to develop new services and improve citizens’ quality of life. Sensors and smart devices generate large amounts of measurement data from sensing the environment, which is used to enable services such as control of power consumption or traffic density. To deal with such a large amount of information and provide accurate measurements, service providers can adopt information fusion, which given the decentralized nature of urban deployments can be performed by means of consensus algorithms. These algorithms allow distributed agents to (iteratively) compute linear functions on the exchanged data, and take decisions based on the outcome, without the need for the support of a central entity. However, the use of consensus algorithms raises several security concerns, especially when private or security critical information is involved in the computation.
In this article we propose ODIN, a novel algorithm allowing information fusion over encrypted data. ODIN is a privacy-preserving extension of the popular consensus gossip algorithm, which prevents distributed agents from having direct access to the data while they iteratively reach consensus; agents cannot access even the final consensus value but can only retrieve partial information (e.g., a binary decision). ODIN uses efficient additive obfuscation and proxy re-encryption during the update steps and garbled circuits to make final decisions on the obfuscated consensus. We discuss the security of our proposal and show its practicability and efficiency on real-world resource-constrained devices, developing a prototype implementation for Raspberry Pi devices
Identifying Emotions in Social Media: Comparison of Word-emotion lexica
In recent years, emotions expressed in social media messages have become a vivid research topic due to their influence on the spread of misinformation and online radicalization over online social networks. Thus, it is important to correctly identify emotions in order to make inferences from social media messages. In this paper, we report on the performance of three publicly available word-emotion lexicons (NRC, DepecheMood, EmoSenticNet) over a set of Facebook and Twitter messages. To this end, we designed and implemented an algorithm that applies natural language processing (NLP) techniques along with a number of heuristics that reflect the way humans naturally assess emotions in written texts. In order to evaluate the appropriateness of the obtained emotion scores, we conducted a questionnaire-based survey with human raters. Our results show that there are noticeable differences between the performance of the lexicons as well as with respect to emotion scores the human raters provided in our surve
Poseidon: Mitigating Interest Flooding DDoS Attacks in Named Data Networking
Content-Centric Networking (CCN) is an emerging networking paradigm being
considered as a possible replacement for the current IP-based host-centric
Internet infrastructure. In CCN, named content becomes a first-class entity.
CCN focuses on content distribution, which dominates current Internet traffic
and is arguably not well served by IP. Named-Data Networking (NDN) is an
example of CCN. NDN is also an active research project under the NSF Future
Internet Architectures (FIA) program. FIA emphasizes security and privacy from
the outset and by design. To be a viable Internet architecture, NDN must be
resilient against current and emerging threats. This paper focuses on
distributed denial-of-service (DDoS) attacks; in particular we address interest
flooding, an attack that exploits key architectural features of NDN. We show
that an adversary with limited resources can implement such attack, having a
significant impact on network performance. We then introduce Poseidon: a
framework for detecting and mitigating interest flooding attacks. Finally, we
report on results of extensive simulations assessing proposed countermeasure.Comment: The IEEE Conference on Local Computer Networks (LCN 2013
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