257 research outputs found
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Morpheus: stream cipher for software & hardware applications
In a world where electronic devices with different characteristics are networked, privacy is an essential element for the communicating process. Privacy can be achieved by encryption algorithms with unique features based on the application that are deployed. In this paper a word-oriented stream cipher, or Morpheus, for both hardware and software devices, is proposed. Morpheus targets multimedia applications, such as Games-On-Demand or IPTV, where data are usually streamed over different kind of networks and devices. Morpheus behaves very well in all known statistical tests and is resilient to known attacks for both synchronous and self-synchronous encryption modes
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Adaptive authentication and key agreement mechanism for future cellular systems
Since the radio medium can be accessed by anyone, authentication of users is a very important element of a mobile network. Nowadays, in GSM/GPRS a challenge response protocol is used to authenticate the user to the mobile network. Similarly, in third generation mobile systems [3] a challenge response protocol was chosen in such a way as to achieve maximum compatibility with the current GSM security architecture. Both authentication mechanisms use symmetric key cryptography because of the limited processing power of the mobile devices. However, recent research [6] has shown that asymmetric, or public, key cryptography can be enabled successfully in future mobile terminals. In this paper, we propose a new adaptive authentication and key agreement protocol (AAKA) for future mobile communication systems. The novelty of AAKA and its main advantage over other challenge response protocols is that can be adaptive to the mobile environment and use symmetric and/or public key cryptography for user and network authentication
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Security enhancement for A5/1 without losing hardware efficiency in future mobile systems
A5/1 is the strong encryption algorithm which protects the air interface of the GSM cellular network. However, in the Fast Software Encryption Workshop 2000 two attacks, the biased birthday attack and the random subgraph attack against A5/1 were presented [1]. In this paper, we propose new security enhancements to improve A5/1 encryption algorithm from the biased birthday attack [1] and random subgraph attack [3] [4] in order to be used in future mobile communication systems. The improvements that make both attacks impractical are based on the clocking mechanism of the registers, and their key setup routine. Furthermore, we have increased the linear complexity of A5/1 to make the solution of the linear equations [2] impractical in real time systems. Finally, both original and modified versions of A5/1 were implemented easily in a CPLD device for 3rd generation mobile systems
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LEE: LightâWeight EnergyâEfficient encryption algorithm for sensor networks
Data confidentiality in wireless sensor networks is mainly achieved by RC5 and Skipjack encryption algorithms. However, both algorithms have their weaknesses, for example RC5 supports variable-bit rotations, which are computationally expensive operations and Skipjack uses a key length of 80-bits, which is subject to brute force attack. In this paper we introduce a light-weight energy- fficient encryption-algorithm (LEE) for tiny embedded devices, such as sensor network nodes. We present experimental results of LEE under real sensor nodes operating in TinyOS. We also discuss the secrecy of our algorithm by presenting a security analysis of various tests and cryptanalytic attacks
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The Lord of the Sense: A Privacy Preserving Reputation System for Participatory Sensing Applications
Electronic devices we use on a daily basis collect sensitive information without preserving userâs privacy. In this paper, we propose the lord of the sense (LotS), a privacy pre- serving reputation system for participatory sensing applications. Our system maintains the privacy and anonymity of information with the use of cryptographic techniques and combines voting approaches to support usersâ reputation. Furthermore, LotS maintains accountability by tracing back a misbehaving user while maintaining k-anonymity. A detailed security analysis is presented with the current advantages and disadvantages of our system
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NAVI: Novel authentication with visual information
Text-based passwords, despite their well-known drawbacks, remain the dominant user authentication scheme implemented. Graphical password systems, based on visual information such as the recognition of photographs and / or pictures, have emerged as a promising alternative to the aggregate reliance on text passwords. Nevertheless, despite the advantages offered they have not been widely used in practice since many open issues need to be resolved. In this paper we propose a novel graphical password scheme, NAVI, where the credentials of the user are his username and a password formulated by drawing a route on a predefined map. We analyze the strength of the password generated by this scheme and present a prototype implementation in order to illustrate the feasibility of our proposal. Finally, we discuss NAVIâs security features and compare it with existing graphical password schemes as well as text-based passwords in terms of key security features, such aspassword keyspace, dictionary attacks and guessing attacks. The proposed scheme appears to have the same or better performance in the majority of the security features examined
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Evaluating the Provision of Botnet Defences using Translational Research Concepts.
Botnet research frequently draws on concepts from other fields. An example is the use of epidemiological models when studying botnet propagation, which facilitate an understanding of bot spread dynamics and the exploration of behavioural theory. Whilst the literature is rich with these models, it is lacking in work aimed at connecting the insights of theoretical research with day-to-day practice. To address this, we look at botnets through the lens of implementation science, a discipline from the field of translational research in health care, which is designed to evaluate the implementation process. In this paper, we explore key concepts of implementation science, and propose a framework-based approach to improve the provision of security measures to network entities. We demonstrate the approach using existing propagation models, and discuss the role of implementation science in malware defence
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SAnoVs: Secure Anonymous Voting Scheme for clustered ad hoc networks
In this paper we propose a secure anonymous voting scheme (SAnoVS) for re-clustering in the ad-hoc network. SAnoVS extends our previous work of degree-based clustering algorithms by achieving anonymity and confidentiality of the voting procedure applied to select new cluster heads. The security of SAnoVS is based on the difficulty of computing discrete logarithms over elliptic curves, the intractability of inverting a one-way hash function and the fact that only neighboring nodes contribute to the generation of a shared secret. Furthermore, we achieve anonymity since our scheme does not require any identification information as we make use of a polynomial equation system combined with pseudo-random coordinates. The security analysis of our scheme is demonstrated with several attacks scenarios.examined with several attack scenarios and experimental results
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ForChaos: Real Time Application DDoS detection using Forecasting and Chaos Theory in Smart Home IoT Network
Recently, D/DoS attacks have been launched by zombie IoT devices in smart home networks. They pose a great threat to to network systems with Application Layer DDoS attacks being especially hard to detect due to their stealth and seemingly legitimacy. In this paper, we propose we propose ForChaos, a lightweight detection algorithm for IoT devices, that is based on forecasting and chaos theory to identify flooding and DDoS attacks. For every time-series behaviour collected, a forecasting-technique prediction is generated, based on a number of features, and the error between the two values is calcualted. In order to assess the error of the forecasting from the actual value, the lyapunov exponent is used to detect potential malicious behaviour. In NS-3 we evaluate our detection algorithm through a series of experiments in Flooding and Slow-Rate DDoS attacks. The results are presented and discussed in detail and compared with related studies, demonstrating its effectiveness and robustness
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