University intelligentsia in the making of maps: post-university networks and political change in Slovenia and Poland

The present paper is a result of research done in Slovenia and Poland while the author was a fellow of the Open Society Institute, Budapest between March 2002 and March 2003. The paper looks into the role of a section of university educated intelligentsia in the making of independent Slovenia out of communist Yugoslavia and in the transition of Poland from a one-party communist rule to a multi-party democracy

Lambda hyperonic effect on the normal driplines

A generalized mass formula is used to calculate the neutron and proton drip lines of normal and lambda hypernuclei treating non-strange and strange nuclei on the same footing. Calculations suggest existence of several bound hypernuclei whose normal cores are unbound. Addition of Lambda or, Lambda-Lambda hyperon(s) to a normal nucleus is found to cause shifts of the neutron and proton driplines from their conventional limits.Comment: 6 pages, 4 tables, 0 figur

Method and system for source authentication in group communications

A method and system for authentication is provided. A central node for issuing certificates to a plurality of nodes associated with the central node in a network is also provided. The central node receives a first key from at least one node from among the plurality of nodes and generates a second key based on the received first key and generates a certificate for the at least one node. The generated certificate is transmitted to the at least one node

Key Management for Secure Multicast in Hybrid Satellite Networks

Keywords: This paper proposes a design for key management for secure multicast in hybrid satellite networks. Communication satellites offer an efficient way to extend IP multicast services for groups in wide-area networks. In order to be commercially viable, the multicast traffic should be accessible only to paying subscribers. Access control can be achieved by data encryption. This requires secure and efficient methods to generate, distribute and update the keys. Most current key management protocols do not scale well when applied to large dynamic groups in wide-area networks. This paper attempts to solve the above problem for groups in a hybrid network that is composed of terrestrial Ethernet LANs interconnected by ATM-based satellite channels. We investigate current group key management protocols, and design a framework for secure and scalable key management for the multicast routing architecture in the satellite network. The proposed framework is presented in detail, alongwith analysis and simulation results. Satellite network, secure multicast, group key management. 1

PIM-SM = Protocol Independent Multicast- Sparse Mode

This paper proposes a design for IP multicast routing in hybrid satellite networks. The emergence of IP multicast for Internet group communication has placed focus on communication satellites as an efficient way to extend the multicast services for groups with distributed membership in wide-area networks. This poses interesting challenges for routing. Hybrid satellite networks can have both wired and wireless links and also combine different link-layer technologies like Ethernet and ATM. No proposed IP multicast routing protocol for wired networks offers an integrated solution for such networks. This paper attempts to provide a solution by proposing a design for IP multicast routing in wide-area networks that have terrestrial Ethernet LANs interconnected by A TM-based satellite channels. The paper reviews the multicast services offered by IP and A TM, and proposes a multicast routing framework that combines PIM-SM protocol for terrestrial multicasting with the A TM MARS and VC mesh architecture for multicast routing over the satellite links. Modifications are made to the standard protocols to suit the unique needs of the network being considered. The feasibility of the proposed design is tested by performing simulations. The proposed framework is presented in detail, along with analysis and simulation results

Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy-clone, object splicing, and removal, which mislead the viewers. In contrast, the identification of these manipulations becomes a very challenging task as manipulated regions are not visually apparent. This paper proposes a high-confidence manipulation localization architecture which utilizes resampling features, Long-Short Term Memory (LSTM) cells, and encoder-decoder network to segment out manipulated regions from non-manipulated ones. Resampling features are used to capture artifacts like JPEG quality loss, upsampling, downsampling, rotation, and shearing. The proposed network exploits larger receptive fields (spatial maps) and frequency domain correlation to analyze the discriminative characteristics between manipulated and non-manipulated regions by incorporating encoder and LSTM network. Finally, decoder network learns the mapping from low-resolution feature maps to pixel-wise predictions for image tamper localization. With predicted mask provided by final layer (softmax) of the proposed architecture, end-to-end training is performed to learn the network parameters through back-propagation using ground-truth masks. Furthermore, a large image splicing dataset is introduced to guide the training process. The proposed method is capable of localizing image manipulations at pixel level with high precision, which is demonstrated through rigorous experimentation on three diverse datasets

Boosting Image Forgery Detection using Resampling Features and Copy-move analysis

Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods. While resampling detection algorithms are effective in detecting splicing and resampling, copy-move detection algorithms excel in detecting cloning and region removal. In this paper, we combine these complementary approaches in a way that boosts the overall accuracy of image manipulation detection. We use the copy-move detection method as a pre-filtering step and pass those images that are classified as untampered to a deep learning based resampling detection framework. Experimental results on various datasets including the 2017 NIST Nimble Challenge Evaluation dataset comprising nearly 10,000 pristine and tampered images shows that there is a consistent increase of 8%-10% in detection rates, when copy-move algorithm is combined with different resampling detection algorithms