Building robust ways to outwit MEV strategies by network validators in cryptocurrency applications is garnering rapid interests now. Encrypting mempools with (varieties of) threshold encryption systems is seen as one of the leading solutions to this problem. Particularly, the notion of Batched Threshold Encryption (BTE) proposed in multiple recent papers by Choudhuri et al. [USENIX 2024, 2025] and Agarwal et al. [CRYPTO 2025] gives promising approaches to build scalable encrypted mempools. However, the existing BTE does not address collusion among (potentially malicious) validators (leaking confidential information).

The rising commerciality of cryptocurrencies and blockchains in DeFi applications raises the importance of implementing robust methods to protect its regular users against parties with enormous amounts of resources that allows them to balefully influence the market through various Maximal Extractable Value (MEV) strategies. There are typical situations in such scenarios where an end-user may want to hide its transaction details till it has been executed. Ensuring the privacy of pending mempool transactions thus becomes an important goal. To this end, various decentralized versions of threshold encryption (TE) systems have been recently shown particularly effective.

Enterprises are looking at grid computing as a technology of enormous potential. One such issue is the issue of grid application migration, where legacy applications are migrated to the grid environment. The grid application migration framework (GAMF), is an attempt to provide a systematic approach for handling the migration process. The framework consists of three independently deployable components: grid code analyzer (GCA), grid task generator (GTG), and grid simulator (GS). The GCA component analyzes the different applications and generates a directed acyclic graph (DAG) based on the information obtained from analysis. The DAG is based on both static and runtime information available from application profiling. The DAG information is then analyzed and grid tasks are generated based on different DAG reducing and clustering algorithms. The simulator takes the generated DAG as input and provides and analyzes the application performance with respect to grid infrastructure and policies

A grid is described as a distributed network which comprises of heterogeneous and non-dedicated elements. The heterogeneity of a grid is not only defined in terms of computing elements and operating systems but also in terms of implementation of policies, policy decisions and the environment. Currently, most grid solutions are targeted at the high performance community for e-sciences and hence are not adequate for enterprises. In this paper, we present an enterprise level workflow and grid management system called the unified grid management and data architecture (UGanDA) which takes care of most needs of enterprises and can be used in traditional e-sciences high performance community as well. It consists of two components: a grid workflow manager called GridWorM and a grid infrastructure manager called MAGI. The two independently deployable components orchestrate to provide the final goal. Representative results are discussed to prove the effectiveness of the system.

The issue of handling network failures is becoming increasingly important. In this paper, we address the problem of constrained routing by treating reliability as one of the QoS requirements. The problem is to create a feasible path from a given node to the destination such that the bandwidth and reliability requirements of the path are satisfied and the cost of the path is minimized (Reliability Constrained Least Cost Routing Problem). To solve the problem, we propose an approach which employs a novel concept, called partial protection, wherein backup paths are created for a selected set of domains in the network so as to meet the reliability constraints. The Partial Protection Approach (PPA) has two steps: Primary Path Creation and Backup Path Creation if necessary. To implement PPA, we propose three scalable two-pass resource reservation schemes, viz., Conservative, Optimistic, and Hybrid schemes. These schemes differ depending on whether the backup paths are created during the forward pass, reverse pass, or both. We evaluate the performance of the proposed schemes for dynamic multicast groups with different bandwidth and reliability requirements using average call acceptance rate and average tree cost as performance metrics. Our studies show that group dynamics and reliability requirements have significant impact on the performance of the schemes.

The Internet infrastructure security has been gaining importance in recent years due to growing concerns for cyberwarfare. Among different network threats, the routing table poisoning attack is the most devastating and least researched topic, which needs immediate research attention. In this paper, we develop a scalable algorithm for detecting and recovering from router attacks in distance vector routing protocols. The algorithm is able to detect and recover from malicious updates under certain well-defined conditions. We carry out extensive simulation studies to evaluate the proposed pivot based algorithm for inconsistency recovery (PAIR) for three performance metrics, viz. detection probability, recovery probability and malicious distance under different network and attack scenarios. Our studies show that the PAIR is extremely scalable and offers high detection and recovery capability.

The routing table poisoning attack is one of the most devastating and least researched topic among Internet attacks, which needs immediate research attention. In this paper, we develop a scalable method for detecting router attacks and locating the malicious routers (within a small bounded set of nodes) in link state routing protocols. We carry out analytical and simulation studies to evaluate the proposed secure link state protocol (SLIP) for two performance metrics, viz. attack detection probability and fault detection time, under different network and attack scenarios. Our studies show that the SLIP offers a very high attack detection capability with a little degradation in fault detection time compared to the link state protocol.

The proliferation of QoS-aware group applications coupled with the limited availability of network resources demands efficient mechanisms to support QoS multicasting. During a life-cycle of a multicast session, three important events can occur: membership dynamics, network dynamics, and traffic dynamics. The first two are concerned with maintaining a good quality (cost) multicast tree taking into account dynamic join/leave of members, and changes in network topology due to link/node failures/additions, respectively. The third aspect is concerned with flow, congestion, and error control. There have been many solutions proposed for dealing with each of these issues. However, the issue of tree migration has not been addressed as part of these solutions. In this paper, we highlight the importance of tree migration as a mechanism for handling membership and network dynamics in core-based I multicasting, prove that it is NP-complete, and propose four heuristic algorithms for it. The proposed algorithms are evaluated under two performance metrics: service disruption and resource wastage. Our simulation studies show that two of the algorithms offer comparable performance to that of the other two, in addition to being highly scalable and easily implementable.