AN APPROACH TOWARDS EXPLOITATION OF SOCIAL COMMUNICATIONS IN MOBILE SYSTEMS

Social network is the networking of communications which bond the people cooperatively and comprise the flow of information connecting people, business connections. Mobile social networks as promising social communication platforms have achieved enormous attention in recent times. Privacy preservation is an important issue of research in social networking. The protection of user’s privacy is connected to their profiles and their results of profile matching. The protocols of profile matching allow the users to get hold of the results of profile matching which enclose partial information of profile and can be categorized on the basis of profiles format and the types of matching functions into three classes such as non anonymity, conditional anonymity and full anonymity.  A family of novel protocols such as profile matching approaches of explicit comparison-based with conditional anonymity which allows two users to measure up to their values of attribute on a specific attribute devoid of revealing the values to each other; implicit comparison-based the responder organizes numerous categories of messages where two messages are created for each group; and implicit predicate-based with full anonymity permits the comparisons of numerous attributes intended for profile matching  were introduced

Efficient data intensive secure computation : fictional or real

Secure computation has the potential to completely reshape the cybersecruity landscape, but this will happen only if we can make it practical. Despite significant improvements recently, secure computation is still orders of magnitude slower than computation in the clear. Even with the latest technology, running the killer apps, which are often data intensive, in secure computation is still a mission impossible. In this paper, I present two approaches that could lead to practical data intensive secure computation. The first approach is by designing data structures. Traditionally, data structures have been widely used in computer science to improve performance of computation. However, in secure computation they have been largely overlooked in the past. I will show that data structures could be effective performance boosters in secure computation. Another approach is by using fully homomorphic encryption (FHE). A common belief is that FHE is too inefficient to have any practical applications for the time being. Contrary to this common belief, I will show that in some cases FHE can actually lead to very efficient secure computation protocols. This is due to the high degree of internal parallelism in recent FHE schemes. The two approaches are explained with Private Set Intersection (PSI) as an example. I will also show the performance figures measured from prototype implementations

Improved Secure Efficient Delegated Private Set Intersection

Private Set Intersection (PSI) is a vital cryptographic technique used for securely computing common data of different sets. In PSI protocols, often two parties hope to find their common set elements without needing to disclose their uncommon ones. In recent years, the cloud has been playing an influential role in PSI protocols which often need huge computational tasks. In 2017, Abadi et al. introduced a scheme named EO-PSI which uses a cloud to pass on the main computations to it and does not include any public-key operations. In EO-PSI, parties need to set up secure channels beforehand; otherwise, an attacker can easily eavesdrop on communications between honest parties and find private information. This paper presents an improved EO-PSI scheme which has the edge on the previous scheme in terms of privacy and complexity. By providing possible attacks on the prior scheme, we show the necessity of using secure channels between parties. Also, our proposed protocol is secure against passive attacks without having to have any secure channels. We measure the protocol's overhead and show that computational complexity is considerably reduced and also is fairer compared to the previous scheme.Comment: 6 pages, presented in proceedings of the 28th Iranian Conference on Electrical Engineering (ICEE 2020). Final version of the paper has been adde

Fair private set intersection with a semi-trusted arbiter

A private set intersection (PSI) protocol allows two parties to compute the intersection of their input sets privately. Most of the previous PSI protocols only output the result to one party and the other party gets nothing from running the protocols. However, a mutual PSI protocol in which both parties can get the output is highly desirable in many applications. A major obstacle in designing a mutual PSI protocol is how to ensure fairness. In this paper we present the first fair mutual PSI protocol which is efficient and secure. Fairness of the protocol is obtained in an optimistic fashion, i.e. by using an offline third party arbiter. In contrast to many optimistic protocols which require a fully trusted arbiter, in our protocol the arbiter is only required to be semi-trusted, in the sense that we consider it to be a potential threat to both parties' privacy but believe it will follow the protocol. The arbiter can resolve disputes without knowing any private information belongs to the two parties. This feature is appealing for a PSI protocol in which privacy may be of ultimate importance

Refereed Computation Delegation of Private Sequence Comparison in Cloud Computing

Abstract Sequence comparison has been widely used in many engineering systems, such as fuzzy keyword search, plagiarism detection, and comparison of gene sequences. However, when the length of the string is extraordinarily long, like the DNA sequence that contains millions of nucleotides, sequence comparison becomes an intractable work, especially when the DNA database is big and the computation resources are limited. Although the generic computation delegation schemes provide a theoretically feasible solution to this problem, it suffers from severe inefficiency when we directly substitute the general function by the sequence comparison function. In this paper, we focus on refereed computation delegation of sequence comparison and present the refereed computation delegation scheme of sequence comparison using multiple servers. In our scheme, the user can detect the dishonest servers and get the correct answer as long as there is one honest server. The direct application of our scheme is DNA sequence comparison of big gene database in medical system. Meanwhile, our scheme satisfies the security requirement of sequence privacy against the malicious adversaries. Moreover, since neither the fully homomorphic encryption nor the complicated proof systems are used for the problem generation and result verification, our solution clearly outperforms the existing schemes in terms of efficiency. The computation complexity of the user is reduced from O(mn) to O(log 2 (mn)), where m,n are the length of the sequences

Secure and Efficient Multiparty Private Set Intersection Cardinality

The article of record as published may be found at http://dx.doi.org/10.3934/amc.2020071In the field of privacy preserving protocols, Private Set Intersection (PSI) plays an important role. In most of the cases, PSI allows two parties to securely determine the intersection of their private input sets, and no other information. In this paper, employing a Bloom filter, we propose a Multiparty Private Set Intersection Cardinality (MPSI-CA), where the number of participants in PSI is not limited to two. The security of our scheme is achieved in the standard model under the Decisional Diffie-Hellman (DDH) assumption against semi-honest adversaries. Our scheme is flexible in the sense that set size of one participant is independent from that of the others. We consider the number of modular exponentiations in order to determine computational complexity. In our construction, communication and computation overheads of each participant is O(v max k) except that the complexity of the designated party is O(v1), where v max is the maximum set size, v1 denotes the set size of the designated party and k is a security parameter. Particularly, our MSPI-CA is the first that incurs linear complexity in terms of set size, namely O(nv max k), where n is the number of participants. Further, we extend our MPSI-CA to MPSI retaining all the security attributes and other properties. As far as we are aware of, there is no other MPSI so far where individual computational cost of each participant is independent of the number of participants. Unlike MPSI-CA, our MPSI does not require any kind of broadcast channel as it uses star network topology in the sense that a designated party communicates with everyone else