Visible to the public Biblio

Filters: Author is Gupta, Divya  [Clear All Filters]
2022-03-08
Gupta, Divya, Wadhwa, Shivani, Rani, Shalli.  2021.  On the Role of Named Data Networking for IoT Content Distribution. 2021 6th International Conference on Communication and Electronics Systems (ICCES). :544–549.
The initially designed internet aimed to create a communication network. The hosts share specific IP addresses to establish a communication channel to transfer messages. However, with the advancement of internet technologies as well as recent growth in various applications such as social networking, web sites, and number of smart phone users, the internet today act as distribution network. The content distribution for large volume traffic on internet mainly suffers from two issues 1) IP addresses allocation for each request message and 2) Real time content delivery. Moreover, users nowadays care only about getting data irrespective of its location. To meet need of the hour for content centric networking (CCN), Information centric networking (ICN) has been proposed as the future internet architecture. Named data networks (NDN) found its roots under the umbrella of ICN as one of its project to overcome the above listed issues. NDN is based on the technique of providing named data retrieval from intermediate nodes. This conceptual shift raises questions on its design, services and challenges. In this paper, we contribute by presenting architectural design of NDN with its routing and forwarding mechanism. Subsequently, we cover services offered by NDN for request-response message communication. Furthermore, the challenges faced by NDN for its implementation has been discussed in last.
2017-05-18
Ananth, Prabhanjan, Gupta, Divya, Ishai, Yuval, Sahai, Amit.  2014.  Optimizing Obfuscation: Avoiding Barrington's Theorem. Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security. :646–658.

In this work, we seek to optimize the efficiency of secure general-purpose obfuscation schemes. We focus on the problem of optimizing the obfuscation of Boolean formulas and branching programs – this corresponds to optimizing the "core obfuscator" from the work of Garg, Gentry, Halevi, Raykova, Sahai, and Waters (FOCS 2013), and all subsequent works constructing general-purpose obfuscators. This core obfuscator builds upon approximate multilinear maps, where efficiency in proposed instantiations is closely tied to the maximum number of "levels" of multilinearity required. The most efficient previous construction of a core obfuscator, due to Barak, Garg, Kalai, Paneth, and Sahai (Eurocrypt 2014), required the maximum number of levels of multilinearity to be O(l s3.64), where s is the size of the Boolean formula to be obfuscated, and l s is the number of input bits to the formula. In contrast, our construction only requires the maximum number of levels of multilinearity to be roughly l s, or only s when considering a keyed family of formulas, namely a class of functions of the form fz(x)=phi(z,x) where phi is a formula of size s. This results in significant improvements in both the total size of the obfuscation and the running time of evaluating an obfuscated formula. Our efficiency improvement is obtained by generalizing the class of branching programs that can be directly obfuscated. This generalization allows us to achieve a simple simulation of formulas by branching programs while avoiding the use of Barrington's theorem, on which all previous constructions relied. Furthermore, the ability to directly obfuscate general branching programs (without bootstrapping) allows us to efficiently apply our construction to natural function classes that are not known to have polynomial-size formulas.