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Cloud computing is used to connect several number of remote servers through Internet to accumulate and recover large data anywhere and anytime. As of the conventional privacy defending process, there is a possibility for malevolent assault on the sensitive information accumulated in the cloud. In this research, the authors have proposed a competent large data convert among privacy defending by Hadoop map reduce in the cloud. The procedure exploits fuzzy C‐means clustering (FCM) algorithm grouping the data. For dimensionality reduction, map reduce framework will be used. In evaluation module, the recommended technique performed with the aid of K‐nearest neighbour (KNN) classification algorithm in this phase using KNN technique to check the convolution process based on the threshold value, which is improving the utility of the privacy data. The consequence acquired illustrates that authors' proposed scheme has enhanced the clustering exactness and also accomplishes the effectual convolution procedure to improve the privacy. From the experimental results, the proposed research achieved an effective clustering accuracy 76.07% and the existing K‐means approach gets the clustering accuracy of 73.5% which is minimum value when compared to the proposed researches. The suggested technique is implemented in JAVA with Cloud Sim platform. [ABSTRACT FROM AUTHOR]

In distributed systems there is often a need to store and share sensitive information (e.g., encryption keys, digital signatures, login credentials etc.) among the devices. It is also generally the case that this piece of information cannot be entrusted to any individual device since the malfunction or compromising of one node could jeopardize the security of the entire system. Even if the information is split among the devices, there is still a risk when an attacker can compromise a group of them. Therefore we have designed and implemented a secure and robust secret sharing scheme to enable a more resilient sharing of confidential information. This solution provides three important features: (i) it uses threshold secret sharing to split the information into shares to be kept by all devices in the system; so the information can only be retrieved collaboratively by groups of devices; (ii) it guarantees the privacy of the confidential information under a certain number of passive hijacking attacks; and (iii) it ensures the integrity of the confidential information against any number of hijackers who actively and collusively attack the devices. It is able to identify all the compromised devices, while still keeping the secret unforgeable to attackers. [ABSTRACT FROM AUTHOR]

Internet protocol security (IPSec), secure sockets layer (SSL)/transport layer security (TLS) and other security protocols necessitate high throughput hardware implementation of cryptographic functions. In recent literature, cryptographic functions implemented in software, application specific integrated circuit (ASIC) and field programmable gate array (FPGA). They are not necessarily optimized for throughput. Due to the various side‐channel based attacks on cache and memory, and various malware based exfiltration of security keys and other sensitive information, cryptographic enclave processors are implemented which isolates the cryptographically sensitive information like keys. We propose a partitioned enclave architecture targeting IPSec, TLS and SSL where the partitioned area ensures that the processor data‐path is completely isolated from the secret‐key memory. The security processor consists of a Trivium random number generator, Rivest–Shamir–Adleman (RSA), advanced encryption standard (AES) and KECCAK cryptos. We implement three different optimized KECCAK architectures. The processing element (PE) handles all communication interfaces, data paths, and control hazards of network security processor. The memory of KECCAK and AES communication is done via a direct memory access controller to reduce the PE overhead. The whole system is demonstrated by FPGA implementation using Vivado 2015.2 on Artix‐7 (XC7A100T, CSG324). The performances of the implemented KECCAKs are better in terms of security, throughput and resource than the existing literature. [ABSTRACT FROM AUTHOR]

With the big-data and mobile Internet era coming, sensitive information (SI) in various applications plays a key role; even more, they can be an important part of the authentication between clients and servers. However, how to measure security or sensitivity degrees of SI is an open issue. Furthermore, no effective method can detect covert channel of SI thieves in Advanced Persistent Threat attacks. To deal with these problems, we propose a new design, called software-defined networking (SDN)-based SI Protection, in which sensitivity degree can be measured by using Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution, and SI covert channel can be detected based on OpenFlow in SDN. To our best knowledge, it is the first defined sensitivity degree for SI and novel flow-table design in SI data flow switch. Most significantly, our proposal can apply integrated semantics of leakage points and accident attacks into security analysis and switch protocol in Operating System or network. To verify our proposal, experimental tests are performed in social network platforms, field test results have demonstrated that this proposal can capture security level for SI as expected, detect any kinds of potential leakage points in data lifetime, describe fine-grained semantics of accidental attacks, and detect illegal data flow of SI in network layer. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In the security system, there is a lot of sensitive information, and the leakage of the secret key will cause security failure. In this Letter, combining the fault injection analysis of SM4 (Chinese block cipher algorithm standard), a key leakage Trojan payload circuit that requires only 4 XOR gates was designed and verified. By estimation, the area and power consumption is <1% of that in popular solutions. The scheme was successfully verified using FPGA. This Letter makes contribution to the defence for key‐leakage type Trojan. [ABSTRACT FROM AUTHOR]

Collaborative traffic‐monitoring (CTM) systems exploit the location information continuously collected from vehicles. Location data are very sensitive information that made privacy a major obstacle for the widespread usage of CTM systems. The way how this data are generated and used is very important for users' privacy and data quality as well. Recently, two CTM approaches have been proposed, the first relies on a dedicated infrastructure that is called vehicular ad hoc networks (VANETs), and the second utilises the existing underlying infrastructure such as cellular and wireless networks. In this study, the authors propose a privacy aware collaborative traffic monitoring system (PA‐CTM) that considers the privacy and security properties of VANETs and existing infrastructures. PA‐CTM provides a client server architecture that relies on existing infrastructures and enhances privacy by: (i) Using a robust pseudonym providing system for anonymous access. Pseudonyms enable users to be authenticated anonymously by the traffic server without having their identities revealed. It also allows revealing identities for law enforcement purposes when necessary. Users are able to change their pseudonyms and hence hide their complete trajectory information form traffic server. (ii) Utilising a novel autonomous location update mechanism (ALUM) that does not rely on a trusted third party and uses only local parameters (speed and direction) for triggering a location update or pseudonym change. These performance results showed that ALUM is effective for traffic monitoring in terms of both privacy and utility. [ABSTRACT FROM AUTHOR]

The storage of fingerprints is an important issue as this biometric modality is more and more deployed for real applications. Considering minutiae templates as sensitive information, a key question concerns the secure and privacy management of this digital identity. Indeed, if an attacker obtains the minutiae template of a subject, he/she will be able to generate a fingerprint having the same characteristics. Instead of directly storing the minutiae templates, the authors propose in this study a new adaptation of BioHashing to generate a cancellable template in the context of un‐ordered set of noisy minutiae features. To the authors knowledge, little interest has been paid in the literature to the question of protecting minutiae template by BioHashing until now. Using the FVC2002 benchmark database, they show the effectiveness of the proposed approach in term of privacy preservation. They show how the proposed method copes with irreversibility and diversity properties and therefore can be efficient in a realistic context. [ABSTRACT FROM AUTHOR]