Ittay Eyal?

Senior Lecturer (Assistant Prof.), EE, Technion.

Associate Director, Initiative For Cryptocurrencies & Contracts.

My research focuses on the security and scalability of distributed systems, in particular blockchain protocols and trusted execution environments. I have previously worked on distributed storage algorithms and data aggregation in sensor networks. I completed my Ph.D. in 2013 in the Technion's Electrical Engineering Department under the supervision of Prof. Idit Keidar and Prof. Raphi Rom.





Publications in Google Scholar

Selected projects:


Blockchain protocols, implementing variants of Bitcoin's blockchain, have an inherent scalability limit. This limit bounds the possibility to improve the user-perceived latency and maximum throughput. The consequence is that one must trade off bandwidth, latency, and security. We present metrics for evaluating blockchain protocols, and measurements from large scale experiments of the Bitcoin core client.

The blockchain promises to become an infrastructure for anonymous online transactions, cheap remittance and smart contracts. To realize this promise in global scale, a blockchain should enable better latency and bandwidth. We present bitcoin-NG, a novel blockchain protocol that allows for bandwidth limited only by the individual nodes' processing power and latency determined by the network's property.

Bitcoin-NG: A Next Generation Blockchain. With Adem Efe Gencer, Emin Gün Sirer, and Robbert van Renesse
USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2016.
Technical Report, 2015. [arXiv] [Bibtex]
In ScalingBitcoin workshop, Montreal, 2015. [Youtube]

The Miner's Dilemma

One of the most central threats on the Bitcoin system is centralization, where a small number of entities control the majority of mining power, and can therefore take control of the system. In Bitcoin and most similar cryptocurrencies, small miners tend to form mining pools. On the one hand, this is positive, as pools enable the existance of small miners a The largest such entities are open mining pools, where miners join forces to mine together.

The Miner's Dilemma.
In the IEEE Symposium on Security and Privacy (Oakland), 2015. [PDF] [Bibtex]

Selfish Mining

Since its inception, Bitcoin's blockchain was considered secure against attackers commanding less than 50% of the mining power. Specifically, it was believed that a minority attacker cannot create more blockchain blocks than his fair share. We show that this is not the case. A minority miner can use a strategy we call selfish mining, where he generates blocks, keep them secret, and publishes them judiciously according to the system state. With this attack, a minority miner's presence in the blockchain can grow beyond its fair share.

The implications of this phenomena are dangerous, since the revenue of an attacker grows superlinearly with its size. Miners are motivated to join such an attacker, and the attacker is motivated to join other miners, forming a pool with a size that tends towards a majority of the minining power. If such a huge pool forms, the system becomes centralized, losing its basic premise.

Majority is not Enough: Bitcoin Mining is Vulnerable. With Emin Gün Sirer
In the the 18th International Conference on Financial Cryptography and Data Security (FC), 2014. [PDF] [Bibtex]

Distributed Storage Architectures

Large scale data stores refrain from supporting consistent transactional operations due to performance concerns. We propose an architecture that utilizes predictable (though inaccurate) object access to improve transaction performance. However, even with perfect backend transactional support, the users of large Internet applications typically access incoherent caches. We present T-Cache, a transaction-aware cache layer. We demonstrate with realistic workloads that T-Cache significantly improves consistency for cache-accessing users.
Cache Serializability: Reducing Inconsistency in Edge Transactions. With Ken Birman and Robbert van Renesse
In the IEEE International Conference on Distributed Computing Systems (ICDCS), 2015. [PDF] [Bibtex]
Fault-Tolerant Transaction Architectures.
In Distributed Computing Column 51, SIGACT News Volume 44, Number 3, September 2013. [PDF] [Bibtex]
Ordering Transactions with Prediction in Distributed Object Stores. With Ken Birman, Idit Keidar, and Robbert van-Renesse
In the 7th Workshop on Large-Scale Distributed Systems and Middleware (LADIS), 2013. [PDF] [Bibtex] [SOSP'15 poster]
Key-value stores (KVSs), maintained by external cloud providers are the choice object store of numerous Internet applications. However, KVS cloud providers can and do temporarily fail, and the natural solution is to replicate the object store among multiple providers. However, standard replication techniques do not work in this scenario, due to the limited interface of KVSs. We introduce an algorithm for a KVS replicated among multiple providers, and demonstrate its efficiency with experiments and simulations.
Robust Data Sharing with Key-Value Stores. With Cristina Basescu, Christian Cachin, Robert Haas, Alessandro Sorniotti, Marko Vukolic, and Ido Zachevsky
In the 42nd annual IEEE/IFIP international conference on Dependable Systems and Networks (DSN), 2012. [PDF] [Bibtex]

Other Research

Global Estimation with Local Communication. With Idit Keidar, Stacy Patterson and Raphi Rom
In the 27th Int'l Symp. on DIStributed Computing (DISC), 2013. [PDF] [Bibtex]
Tech. Rep. CCIT 809, Technion EE, May 2012 - EE Pub. No. 1766.. [PDF]
Thinner Clouds with Preallocation. With Flavio Junqueira and Idit Keidar
In the 5th UNSENIX Workshop on Hot Topics in Cloud Computing (HotCloud), 2013. [PDF] [Bibtex]
LiMoSense - Live Monitoring in Dynamic Sensor Networks. With Idit Keidar and Raphi Rom
Distributed Computing: Volume 27, Issue 5 (2014), Page 313-328. [PDF] [Springer] [Bibtex]
In the 7th International Symposium on Algorithms for Sensor Systems, Weireless Ad Hoc Networks and Autonomous Mobile Entities (ALGOSENSOR), 2011. [PDF] [Slides]
Distributed Data Clustering in Sensor Networks With Idit Keidar and Raphi Rom
Distributed Data Clustering in Sensor Networks. Distributed Computing, Volume 24, Issue 5 (2011), pages 207-222. [PDF] [Springer] [Bibtex]
Distributed Data Classification in Sensor Networks. In the 29th Annual ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing (PODC), 2010. [PDF]
Distributed Clustering for Robust Aggregation in Large Networks. In the 5th Workshop on Hot Topics in System Dependability (HotDep), 2009. [PDF]

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