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ردیف | عنوان | نوع |
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1 |
Probabilistic data structures for big data analytics: A comprehensive review
ساختار داده های احتمالی برای تجزیه و تحلیل داده های بزرگ: یک مرور جامع-2020 An exponential increase in the data generation resources is widely observed in last decade, because
of evolution in technologies such as-cloud computing, IoT, social networking, etc. This enormous
and unlimited growth of data has led to a paradigm shift in storage and retrieval patterns from
traditional data structures to Probabilistic Data Structures (PDS). PDS are a group of data structures
that are extremely useful for Big data and streaming applications in order to avoid high-latency
analytical processes. These data structures use hash functions to compactly represent a set of items
in stream-based computing while providing approximations with error bounds so that well-formed
approximations get built into data collections directly. Compared to traditional data structures, PDS use
much less memory and constant time in processing complex queries. This paper provides a detailed
discussion of various issues which are normally encountered in massive data sets such as-storage,
retrieval, query,etc. Further, role of PDS in solving these issues is also discussed where these data
structures are used as temporary accumulators in query processing. Several variants of existing PDS
along with their application areas have also been explored which give a holistic view of domains
where these data structures can be applied for efficient storage and retrieval of massive data sets.
Mathematical proofs of various parameters considered in the PDS have also been discussed in the
paper. Moreover, the relative comparison of various PDS with respect to various parameters is also
explored. Keywords: Big data | Internet of things (IoT) | Probabilistic data structures | Bloom filter | Quotient filter | Count min sketch | HyperLogLog counter | Min-hash Locality | sensitive hashing |
مقاله انگلیسی |
2 |
Unbalanced private set intersection cardinality protocol with low communication cost
پروتکل کاردینالیت تقاطع غیر متعادل مجموعه خصوصی با هزینه کم ارتباط-2020 Private set intersection cardinality (PSI-CA) allows two parties, the sender and receiver, to compute the
cardinality of the intersection, without revealing anything more to the other party. This paper focuses
on the unbalanced private data sets case, where two parties hold sets of private data items, such as
the users’ identifiers; and where the size of the receiver’s private data set is significantly smaller than
the size of the sender’s private data set. Two parties want to learn the cardinality of the intersection,
but nothing else. The commutative encryption inspires authors to develop a novel protocol to solve
the problem. Furthermore, by the application of the Bloom filter, the receiver can compute the output
more easily than by the method that the encryption is carried out on the sender’s private data set
when low-power mobile IoT devices are used. In the semi-honest model, we can prove the security
of our protocol when the sender’s data set is big enough. The experiment shows the deviation of our
protocol is negligible and the computation costs of our protocol. Keywords: Private set intersection cardinality | Commutative encryption | The Bloom filter |
مقاله انگلیسی |
3 |
Private membership test protocol with low communication complexity
پروتکل آزمون عضویت خصوصی با پیچیدگی ارتباطی پایین-2019 We introduce a practical method to perform private membership tests. In this method, clients are able to test
whether an item is in a set controlled by the server without revealing their query item to the server. After
executing the queries, the content of the servers set remains secret. One use case for a private membership test is
to check whether a file contains any malware by checking its signature against a database of malware samples in a
privacy preserving way. We apply the Bloom filter and the Cuckoo filter in the membership test procedure. In
order to achieve privacy properties, we present a novel protocol based on some homomorphic encryption
schemes. In our protocol, we rearrange the data in the set into N -dimensional hypercubes. We have implemented
our method in a realistic scenario where a client of an anti-malware company wants to privately check whether a
hash value of a given file is in the malware database of the company. The evaluation shows that our method is
feasible for real-world applications. We also have tested the performance of our protocol for databases of different
sizes and data structures with different dimensions: 2-dimensional, 3-dimensional and 4-dimensional hypercubes.
We present formulas to estimate the cost of computation and communication in our protocol. Keywords: Privacy enhancing technologies | Applied cryptography | Private information retrieval | Private membership test | Homomorphic encryption |
مقاله انگلیسی |
4 |
Bloom filter based optimization scheme for massive data handling in IoT environment
طرح بهینه سازی فیلتر مبتنی بر بلوم برای جاجایی داده های گسترده در محیط اینترنت اشیا-2018 With the widespread popularity of big data usage across various applications, need for efficient storage,
processing, and retrieval of massive datasets generated from different applications has become inevitable.
Further, handling of these datasets has become one of the biggest challenges for the research community
due to the involved heterogeneity in their formats. This can be attributed to their diverse sources of
generation ranging from sensors to on-line transactions data and social media access. In this direction,
probabilistic data structures (PDS) are suitable for large-scale data processing, approximate predictions,
fast retrieval and unstructured data storage. In conventional databases, entire data needs to be stored in
memory for efficient processing, but applications involving real time in-stream data demand time-bound
query output in a single pass. Hence, this paper proposes Accommodative Bloom filter (ABF), a variant
of scalable bloom filter, where insertion of bulk data is done using the addition of new filters vertically.
Array of m bits is divided into b buckets of l bits each and new filters of size ‘m/k′ are added to each
bucket to accommodate the incoming data. Data generated from various sensors has been considered for
experimental purposes where query processing is done at two levels to improve the accuracy and reduce
the search time. It has been found that insertion and search time complexity of ABF does not increase
with increase in number of elements. Further, results indicate that ABF outperforms the existing variants
of Bloom filters in terms of false positive rates and query complexity, especially when dealing with instream data
Keywords: Internet of Things ، Big data analytics ، Probabilistic data structures ، Bloom filter ، In-stream data processing |
مقاله انگلیسی |
5 |
Towards achieving flexible and verifiable search for outsourced database in cloud computing
به سوی دستیابی به جستجوی انعطاف پذیر و قابل اثبات برای پایگاه داده برون سپاری در محاسبات ابری-2017 The notion of outsourced database allows the data owner to outsource a database to the cloud service
provider (CSP), and then anyone can enjoy database services provided by the CSP. Some new security
and privacy concerns, e.g., query integrity, are inevitably raised because of losing physical control of data.
Recently, some researchers present a verifiable data integrity auditing protocol for outsourced database,
which satisfies both the correctness and completeness of search result even if the CSP intentionally returns
an empty set. However, for each attribute column, the data owner needs to count the number of data
tuples with the same value in advance. Any slight update operation may bring about huge computation
and communication overhead. This makes it very hard to be applicable to dynamic outsourced database
scenario. To address the above challenge, we propose a novel verifiable search scheme for outsourced
database based on invertible Bloom filter (IBF), which can achieve verifiability of search result without
the process of pre-counting. Furthermore, the proposed scheme is extended to multi-user setting by
incorporating multi-party searchable encryption (MPSE), which can resist collusion attack between
the CSP and any malicious users. Finally, security and efficiency evaluation show that the proposed
construction can achieve the desired security properties, while providing a comparable computation and
storage overhead.
Keywords: Database outsourcing | Invertible Bloom filter | Query auditing |
مقاله انگلیسی |
6 |
Providing robust security measures to Bloom filter based biometric template protection schemes
ارائه اقدامات امنیتی قوی برای طرح های حفاظت از قالب های بیومتریک بر اساس فیلتر بلوم-2017 Template protection is an essential requirement of biometric recognition systems. These
special methods are designed to provide the necessary security and privacy privileges to
the registered users of the biometric system. Similar to other security domains, these schemes
require to follow certain properties or characteristics like unlinkability, irreversibility and
low information leakage from the stored data. Ideally, these schemes must not result in any
degradation of the biometric recognition performance as a whole. Designing a system which
balances all these factors efficiently has been a major challenge. Contemporary frame
works generally relax one or more of these parameters in order to achieve their application
specific goals. However recently, a modified Bloom filter based scheme was proposed which
apparently provided competent security measures in addition to high recognition accu
racy rates. However subsequent studies refuted the security guarantees of the scheme by
providing adversarial attacks with practical bounds. In our work, we address this issue and
propose a modified Bloom filter based framework which provides all the desirable security
measures of a biometric template protection scheme. Not only have we theoretically proved
all the security notions of our model, but also experimentally verified our claims. Thus our
proposed design provides satisfactory security guarantees in addition to the implicit ad
vantages of using Bloom filters like speed and efficiency. Finally, there is no reduction in
the performance rates of the underlying system since we perform the matching of the bio
metric traits in their original forms (in contrast to some transformed space).
Keywords: Biometrics | Iris | Security | Bloom filters | Perfect secrecy |
مقاله انگلیسی |
7 |
Security analysis and improvement of some biometric protected templates based on Bloom filters
تجزیه و تحلیل امنیت و بهبود برخی از الگوهای محافظت بیومتریک بر اساس فیلترهای بلوم-2017 In this work, we develop an unlinkability and irreversibility analysis of the so-called Bloom filter-based
iris biometric template protection introduced at ICB 2013. We go further than the unlinkability analysis of
Hermans et al. presented at BIOSIG 2014. Firstly we analyse unlinkability on protected templates built from
two different iriscodes coming from the same iris whereas Hermans et al. analysed only protected templates
from the same iriscode. Moreover we introduce an irreversibility analysis that exploits non-uniformity of the
biometric data. Our experiments demonstrate new vulnerabilities of this scheme. Then we will discuss the
security of other similar protected biometric templates based on Blooms filters that have been suggested in
the literature since 2013. Finally we suggest a Secure Multiparty Computation (SMC) protocol, that benefits
of the alignment-free feature of this Bloom filter construction, in order to compute efficiently and securely
the matching scores.
Keywords:Bloom filter | Biometric security |
مقاله انگلیسی |
8 |
Routing on large scale mobile ad hoc networks using bloom filters
مسیریابی شبکه های ادهاک سیار در مقیاس بزرگ با استفاده از فیلتر بلوم-2014 A bloom filter is a probabilistic data structure used to test whether an element is a member
of a set. The bloom filter shares some similarities to a standard hash table but has a higher
storage efficiency. As a drawback, bloom filters allow the existence of false positives. These
properties make bloom filters a suitable candidate for storing topological information in
large-scale mobile ad hoc networks, where there is a considerable amount of data to be
exchanged. Bloom filters enable the transmission of reduced routing control messages to
save available bandwidth, and they require fewer node resources than traditional data
structures. Existing ad hoc routing protocols using bloom filters limit themselves to static
sensor networks or small/medium-scale mobile networks. In this study, we propose and
analyse a routing protocol suited for large scale mobile ad hoc networks (up to 3000 nodes)
that stores and disseminates topological information through a specific type of bloom filter
that is able to discard old elements. Logical overlays are then constructed with the proposed
data structures to indicate the distance to the destination nodes. This process allows
the routing protocol to reduce the number of control messages required to discover and
maintain routes. The proposed algorithm is validated via simulation and compared with
other well-known routing protocols developed for mobile ad hoc networks.
Keywords:
Routing protocol
Mobile ad hoc network
Bloom filter
Large-scale network |
مقاله انگلیسی |