Furon , A general framework for robust watermarking security , Signal Processing , vol. DOI : Cayre, C. Fontaine, and T. Kerckhoffs , La cryptographic militaire , J. Militaires , vol. Cover and J. Thomas , Elements of Information Theory, ser. Wiley series in Telecommunications , Moulin and R. Koetter , Data-Hiding Codes , Proc. IEEE , pp. Mihcak, R. Venkatesan, and M. Kesal , Cryptanalysis of discrete-sequence spread spectrum watermarks , Proc. Workshop Digital Watermarking , pp. Eggers, R. Bas and J. Chen and G. Wornell , Quantization index modulation: a class of provably good methods for digital watermarking and information embedding , IEEE Transactions on Information Theory , vol.
Bloom, I. Cox, T. Kalker, J. Linnartz, M. Miller et al.
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Maes, T. Linnartz, J. In this work, we propose a novel pairing-free certificateless aggregate signature scheme with strong anonymity for HWSN. The scheme does not only achieves data integrity and authenticity, but solves private-key compromise problem and provides countermeasure against privilege escalation.
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The performance analysis and comparison show that the scheme has a significant efficiency in terms of computation and communication overhead. Therefore, the proposed scheme is more suitable for practical applications in a resource-constraint Internet-of-Things IoT environment. In recent years, a great improvement has been made, however, in practical applications, the utility of original data is highly susceptible to noise, and thus, it limits its application and extension. To address the above problem, a new differential privacy method based on smooth sensitivity has been proposed in this paper.
Using this method, the datasets utility is improved greatly by reducing the amount of noise that is added. Keywords : differential privacy; privacy protection; data publish; smooth sensitivity; k-anonymous. Most of the existing security schemes demand computational power beyond the computational capacity of WSNs making them unsuitable security schemes for WSNs routing protocols. In this work, a lightweight security and privacy scheme for WSNs routing protocol is developed.
An elliptic curve cryptography, scalar blinding, symmetric encryption, and modified Diffie Hellman key exchange protocol are adopted to evolve an additive perturbation that ensures data integrity, and an effective authentication that ensure confidentiality during routing. The security analysis shows that our scheme is secured against possible known attacks and performs better than some of the considered state-of- the-art schemes used in WSNs. Both the analytical and experimental results not only show that the proposed scheme requires lower computational power but with increase level of security and speed.
However, most existing methods ignore personal anonymity requirements. In these approaches, the microdata consists of three categories of attribute: explicit-identifier, quasi-identifier, and sensitive attribute. In fact, the data sensitivity should be determined by individuals. An attribute is semi-sensitive if it contains both QI and sensitive values. In this paper, we propose a novel anonymization approach, called local anatomy, to address personalized privacy protection.
Local anatomy partitions the tuples who consider the value as sensitive into buckets inside each attribute. We conduct some experiments to illustrate that local anatomy can protect all the sensitive values and preserve great information utility. Additionally, we also present the concept of intelligent anonymization system as our direction of future work.
Keywords : data publishing; personalized privacy protection; semi-sensitive attribute. In recent years, many researchers have constructed AES s-box variants by changing the values of the parameters in the equation of AES s-box generation algorithm. The strength of these S-box variants is mainly evaluated against the cryptographic properties like avalanche effect, non-linearity, and bit independence criteria, however, there are many other important cryptographic properties of s-box, which need to be evaluated before adopting the s-box in a cipher algorithm.
In this paper, ten cryptographic properties are evaluated for the cryptographic strength of AES s-box variants. The results of five properties namely differential and linear probability, non-linear measurement, balance property and algebraic degree remains the same for any s-box variant, it is due to isomorphic equivalence nature of the variants. Whereas, strict avalanche effect, bit independence criteria, correlation immunity, cyclic property and fix point property showed different results for different s-box variant, which are highlighted in this paper.
The results of s-box variants for above mentioned cryptographic properties are compared with the standard AES s-box. Finally, the conclusion of overall security of s-box variants with respect to these ten properties is conferred. It is drastically revolutionizing the way people interact with each other. Publishing data of social network users for researchers, academicians, advertising organizations etc.
Lots of techniques have been proposed for preserving the privacy of individuals handling different types of attack scenarios used by adversaries. In this paper, we address a new attack model i. An algorithm Optimized K-anonymization has been devised that can deal with two types of attacks i. The experimental results illustrate that our proposed algorithm can preserve the identification of individuals and subsequently maintain the utility of data.
Fog computing is a pattern which expands cloud computing and the provision of related services to the network edge. Therefore, fog computing was recently introduced to provide storage and network services between end users and traditional cloud computing data centers.
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The present study aimed to consider the structure, architecture, and applications of fog computing and analyze its differences and similarities with cloud computing, examine forensics in these networks and finally, present a new approach in this regard. Keywords : Cloud computing; fog computing; forensics; Internet of Things; software-defined networks. Criminals may deny committing a crime, but LEAs are hindered in proving it by the limited processing capabilities of human analysis.
While initial crime scene investigation emphasizes finding actionable intelligence as quickly as possible, lab forensics focuses on reconstructing the case and cross-referencing the evidence to find the truth. Both are critical parts of the investigative response to cyber security incidents. By advocating an intelligence-led response to crime scene investigation and lab forensics, we aim to turn theory into practice for LEAs, supporting the resolution of cyber security incidents and the understanding of what happened.
By working through the different processes and activities in practical exercises, we aim to enable LEAs to implement a response strategy for combating cyber crime. Copy-move forgery is a very common type of forgery used to change the meaning of the image. This paper proposes the passive blind forensic technique to detect the copy-move forgery in the image.
The performance of the proposed method is verified with 45 original and forged images.
Mean absolute error
To test the robustness of the algorithm, forged images with various attacks, such as scaling, rotation, small object and multiple copy-move pasting are considered. The experimental results reveal that the proposed technique identifies and locates the forged area even when the images are contaminated with rotation or scaling attacks. This method also can effectively detect multiple copy-move forgeries.
The comparison of the proposed method is carried out with the existing methods in terms of detection accuracy, recall, and precision. The simulation results show that for the most of the cases the proposed method outperforms the existing methods. The key design methodology used in this research work is based on calculation of threshold value at every node regarding the power consumption rate of the node during processing, allowable delay at node with respect to the bounded delay and the packet processing rate. A cross layer approach of communication has been presented at the junction of data link layer and network layer in order to distribute the total route searching overhead for application specific packets among both the layers.
The proposed protocol displays superior performance in terms of throughput, delay and more network life time when compared with conventional AODV protocol which can be derived from the simulation results of Network Simulator NS 2. Characteristics of the CLM are investigated and used to develop a symmetric handwriting document encryption scheme that consists of three phases.
The segmentation phase divides a handwriting image into graphemes. The permutation phase shuffles pixel locations of each grapheme. Finally, the substitution phase modifies pixel intensity values of the corresponding permutated grapheme utilizing the chaotic logarithmic map. Experimental results indicate that the proposed CLM poses interesting characteristics such as wide range chaotic behaviour, robust chaos, s-unimodality, and high sensitivity to a small change in initial condition. In addition, statistical results indicate the superior permutation and substitution properties of the proposed encryption scheme over other image encryption schemes of the same structure.
In this paper, we propose and develop DroidMD, a scalable self-improvement based tool, based on auto optimization of signature set, which detect malicious apps in the market at source code level. A prototype has been developed tested and implemented to detect malware in applications.
We implement and evaluate our approach on almost 30, applications including 27, benign and 3, malware applications. DroidMD detects malware in different applications at partial level and full level. It analyzes only the applications code, which increase its reliability. DroidMD detected similar malware code fragments in different malware families and also victim source code files from benign applications.
Additionally, DroidMD detects similar code fragments which were injected into many applications, which can be the indication of malware. Our evaluation of DroidMD demonstrates that our approach is very efficient in detecting malware at large scale with high accuracy of Keywords : Mobile security; Mobile software; Malware detection; Code clones; Android apps reusability; Android evolution. This challenge can be overcome at least partially by developing systematically risk- driven security objectives and controls for the target system, and determining how to offer sufficient evidence of its security performance via metrics.
The target system of our investigation is an Android platform utilized for public safety and security mobile networks. We develop and analyse the security objectives and controls for these systems based on a technological risk analysis.
fcam-api.my.to/qoxy-conocer-personas.php In addition, we investigate how effective and efficient security metrics can be developed for the target system, and describe implementation details of enhanced security controls for authentication, authorization, and integrity objectives. Our analysis includes implementation details of selected security controls and a discussion of their security effectiveness.
It also includes conceptualization and description of adaptive security for an Android platform which can improve the flexibility and effectiveness of these security controls and end-users confidence in service providers.