Biblio

Infrastructure-as-a-Service (IaaS), more generally the "cloud," changed the landscape of system operations on the Internet. Clouds' elasticity allow operators to rapidly allocate and use resources as needed, from virtual machines, to storage, to IP addresses, which is what made clouds popular. We show that the dynamic component paired with developments in trust-based ecosystems (e.g., TLS certificates) creates so far unknown attacks. We demonstrate that it is practical to allocate IP addresses to which stale DNS records point. Considering the ubiquity of domain validation in trust ecosystems, like TLS, an attacker can then obtain a valid and trusted certificate. The attacker can then impersonate the service, exploit residual trust for phishing, or might even distribute malicious code. Even worse, an aggressive attacker could succeed in less than 70 seconds, well below common time-to-live (TTL) for DNS. In turn, she could exploit normal service migrations to obtain a valid certificate, and, worse, she might not be bound by DNS records being (temporarily) stale. We introduce a new authentication method for trust-based domain validation, like IETF's automated certificate management environment (ACME), that mitigates staleness issues without incurring additional certificate requester effort by incorporating the existing trust of a name into the validation process. Based on previously published work [1]. [1] Kevin Borgolte, Tobias Fiebig, Shuang Hao, Christopher Kruegel, Giovanni Vigna. February 2018. Cloud Strife: Mitigating the Security Risks of Domain-Validated Certificates. In Proceedings of the 25th Network and Distributed Systems Security Symposium (NDSS '18). Internet Society (ISOC). DOI: 10.14722/ndss.2018.23327. URL: https://doi.org/10.14722/nd

Companies analyse large amounts of data on clusters of machines, using big data analytic tools such as Apache Spark and Apache Flink to analyse the data. Big data analytic tools are mainly tested regarding speed and reliability. Efforts about Security and thus authentication are spent only at second glance. In such big data analytic tools, authentication is achieved with the help of the Kerberos protocol that is basically built as authentication on top of big data analytic tools. However, Kerberos is vulnerable to attacks, and it lacks providing high availability when users are all over the world. To improve the authentication, this work presents first an analysis of the authentication in Hadoop and the data analytic tools. Second, we propose a concept to deploy Transport Layer Security (TLS) not only for the security of data transportation but as well for authentication within the big data tools. This is done by establishing the connections using certificates with a short lifetime. The proof of concept is realized in Apache Spark, where Kerberos is replaced by the method proposed. We deploy new short living certificates for authentication that are less vulnerable to abuse. With our approach the requirements of the industry regarding multi-factor authentication and scalability are met.