Related papers: Securing Content Sharing over ICN
Anonymous communication networks (ACNs) enable Internet browsing in a way that prevents the accessed content from being traced back to the user. This allows a high level of privacy, protecting individuals from being tracked by advertisers…
In this paper we present the design of name based access control scheme which facilitates data confidentiality by applying end-to-end encryption to data published on NDN with flexible fine-grained access control, which allows to define an…
In critical infrastructures, communication networks are used to exchange vital data among elements of Industrial Control Systems (ICSes). Due to the criticality of such systems and the increase of the cybersecurity risks in these contexts,…
This paper offers a prototype of a Hyperledger Fabric-IPFS based network architecture including a smart contract based encryption scheme that meant to improve the security of user's data that is being uploaded to the distributed ledger. A…
Information-centric networking (ICN) is one of the promising solutions that cater to the challenges of IP-based networking. ICN shifts the IP-based access model to a data-centric model. Named Data Networking (NDN) is a flexible ICN…
To securely leverage the advantages of Cloud Computing, recently a lot of research has happened in the area of "Secure Query Processing over Encrypted Data". As a concrete use case, many encryption schemes have been proposed for securely…
In recent years, 5G is widely used in parallel with IoT networks to enable massive data connectivity and exchange with ultra-reliable and low latency communication (URLLC) services. The internet requirements from user's perspective have…
We study a method for key predistribution in a network of $n$ users where pairwise keys are computed by hashing users' IDs along with secret information that has been (pre)distributed to the network users by a trusted entity. A…
Decentralized, distributed storage offers a way to reduce the impact of data silos as often fostered by centralized cloud storage. While the intentions of this trend are not new, the topic gained traction due to technological advancements,…
The design of secure and usable access schemes to personal data represent a major challenge of online social networks (OSNs). State of the art requires prior interaction to grant access. Sharing with users who are not subscribed or…
Traditional Content Delivery Networks (CDNs) built with traditional Internet technology are less and less able to cope with today's tremendous growth of content. Information Centric Networks (ICN), a proposed future Internet technology, may…
Encrypted data deduplication is an important technique for saving storage space and network bandwidth, which has been widely used in cloud storage. Recently, a number of schemes that solve the problem of data deduplication with dynamic…
Off-grid networks are recently emerging as a solution to connect the unconnected or provide alternative services to networks of possibly untrusted participants. The systems currently used, however, exhibit limitations due to their…
Payment channel network (PCN) is a layer-two scaling solution that enables fast off-chain transactions but does not involve on-chain transaction settlement. PCNs raise new privacy issues including balance secrecy, relationship anonymity and…
In a traditional cloud storage system, users benefit from the convenience it provides but also take the risk of certain security and privacy issues. To ensure confidentiality while maintaining data sharing capabilities, the…
Information-centric networking (ICN) has long been advocating for radical changes to the IP-based Internet. However, the upgrade challenges that this entails have hindered ICN adoption. To break this loop, the POINT project proposed a…
To establish secure (point-to-point and/or broadcast) communication channels among the nodes of a wireless sensor network is a fundamental task. To this end, a plethora of (socalled) key pre-distribution schemes have been proposed in the…
Binarized Neural Networks (BNN) offer efficient implementations for machine learning tasks and facilitate Privacy-Preserving Machine Learning (PPML) by simplifying operations with binary values. Nevertheless, challenges persist in terms of…
In this paper, we address the problem of secure distributed computation in scenarios where user data is not uniformly distributed, extending existing frameworks that assume uniformity, an assumption that is challenging to enforce in data…
Binarized Neural Networks (BNNs) are a class of deep neural networks designed to utilize minimal computational resources, which drives their popularity across various applications. Recent studies highlight the potential of mapping BNN model…