12 research outputs found

    Types of lightweight cryptographies in current developments for resource constrained machine type communication devices: challenges and opportunities

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    Machine-type communication devices have become a vital part of the autonomous industrial internet of things and industry 4.0. These autonomous resource-constrained devices share sensitive data, and are primarily acquired for automation and to operate consistently in remote environments under severe conditions. The requirements to secure the sensitive data shared between these devices consist of a resilient encryption technique with affordable operational costs. Consequently, devices, data, and networks are made secure by adopting a lightweight cryptosystem that should achieve robust security with sufficient computational and communication costs and counter modern security threats. This paper offers in-depth studies on different types and techniques of hardware and software-based lightweight cryptographies for machine-type communication devices in machine-to-machine communication networks

    Data auditing and security in cloud computing: issues, challenges and future directions

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    Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discusse

    Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions

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    Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discussed

    Layer-based Privacy and Security Architecture for Cloud Data Sharing

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    The management of data while maintaining its utility and preservation of security scheme is a matter of concern for the cloud owner. In order to minimize the overhead at cloud service provider of applying security over each document and then send it to the client, we propose a layered architecture. This approach maintains security of the sensitive document and privacy of its data sensitivity. To make a balance between data security and utility, the proposed approach categorizes the data according to its sensitivity. Perseverance of various categorization requires different algorithmic schemes. We set up a cloud distributed environment where data is categorized into four levels of sensitivity; public, confidential, secret, top secret and a different approach has been used to preserve the security at each level. At the most sensitive layers i.e. secret and top secret data, we made a provision to detect the faulty node that is responsible for data leakage. Finally, experimental analysis is carried out to analyze the performance of the layered approach. The experimental results show that time taken (in ms) in processing 200 documents of size 20 MB is 437, 2239, 3142, 3900 for public, confidential, secret and top secret data respectively when the documents are distributed among distinct users, which proves the practicality of the proposed approach

    Location Privacy in VANETs: Improved Chaff-Based CMIX and Privacy-Preserving End-to-End Communication

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    VANETs communication systems are technologies and defined policies that can be formed to enable ITS applications to provide road traffic efficacy, warning about such issues as environmental dangers, journey circumstances, and in the provision of infotainment that considerably enhance transportation safety and quality. The entities in VANETs, generally vehicles, form part of a massive network known as the Internet of Vehicles (IoV). The deployment of large-scale VANETs systems is impossible without ensuring that such systems are themselves are safe and secure, protecting the privacy of their users. There is a risk that cars might be hacked, or their sensors become defective, causing inaccurate information to be sent across the network. Consequently, the activities and credentials of participating vehicles should be held responsible and quickly broadcast throughout a vast VANETs, considering the accountability in the system. The openness of wireless communication means that an observer can eavesdrop on vehicular communication and gain access or otherwise deduce users' sensitive information, and perhaps profile vehicles based on numerous factors such as tracing their travels and the identification of their home/work locations. In order to protect the system from malicious or compromised entities, as well as to preserve user privacy, the goal is to achieve communication security, i.e., keep users' identities hidden from both the outside world and the security infrastructure and service providers. Being held accountable while still maintaining one's privacy is a difficult balancing act. This thesis explores novel solution paths to the above challenges by investigating the impact of low-density messaging to improve the security of vehicle communications and accomplish unlinkability in VANETs. This is achieved by proposing an improved chaff-based CMIX protocol that uses fake messages to increase density to mitigate tracking in this scenario. Recently, Christian \etall \cite{vaas2018nowhere} proposed a Chaff-based CMIX scheme that sends fake messages under the presumption low-density conditions to enhance vehicle privacy and confuse attackers. To accomplish full unlinkability, we first show the following security and privacy vulnerabilities in the Christian \etall scheme: linkability attacks outside the CMIX may occur due to deterministic data-sharing during the authentication phase (e.g., duplicate certificates for each communication). Adversaries may inject fake certificates, which breaks Cuckoo Filters' (CFs) updates authenticity, and the injection may be deniable. CMIX symmetric key leakage outside the coverage may occur. We propose a VPKI-based protocol to mitigate these issues. First, we use a modified version of Wang \etall's \cite{wang2019practical} scheme to provide mutual authentication without revealing the real identity. To this end, a vehicle's messages are signed with a different pseudo-identity “certificate”. Furthermore, the density is increased via the sending of fake messages during low traffic periods to provide unlinkability outside the mix-zone. Second, unlike Christian \etall's scheme, we use the Adaptive Cuckoo Filter (ACF) instead of CF to overcome the effects of false positives on the whole filter. Moreover, to prevent any alteration of the ACFs, only RUSs distribute the updates, and they sign the new fingerprints. Third, mutual authentication prevents any leakage from the mix zones' symmetric keys by generating a fresh one for each communication through a Diffie–Hellman key exchange. As a second main contribution of this thesis, we focus on the V2V communication without the interference of a Trusted Third Party (TTP)s in case this has been corrupted, destroyed, or is out of range. This thesis presents a new and efficient end-to-end anonymous key exchange protocol based on Yang \etall's \cite{yang2015self} self-blindable signatures. In our protocol, vehicles first privately blind their own private certificates for each communication outside the mix-zone and then compute an anonymous shared key based on zero-knowledge proof of knowledge (PoK). The efficiency comes from the fact that once the signatures are verified, the ephemeral values in the PoK are also used to compute a shared key through an authenticated Diffie-Hellman key exchange protocol. Therefore, the protocol does not require any further external information to generate a shared key. Our protocol also does not require interfacing with the Roadside Units or Certificate Authorities, and hence can be securely run outside the mixed-zones. We demonstrate the security of our protocol in ideal/real simulation paradigms. Hence, our protocol achieves secure authentication, forward unlinkability, and accountability. Furthermore, the performance analysis shows that our protocol is more efficient in terms of computational and communications overheads compared to existing schemes.Kuwait Cultural Offic

    Information security and assurance : Proceedings international conference, ISA 2012, Shanghai China, April 2012

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    A patient agent controlled customized blockchain based framework for internet of things

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    Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph
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