Software-Defined Networking (SDN) has transformed network architectures by decoupling the control and data-planes, enabling fine-grained control over packet processing and forwarding. P4, a language designed for programming data-plane devices, allows developers to define custom packet processing behaviors directly on programmable network devices. This provides greater control over packet forwarding, inspection, and modification. However, the increased flexibility provided by P4 also brings significant security challenges, particularly in managing sensitive data and preventing information leakage within the data-plane. This paper presents a novel security type system for analyzing information flow in P4 programs that combines security types with interval analysis. The proposed type system allows the specification of security policies in terms of input and output packet bit fields rather than program variables. We formalize this type system and prove it sound, guaranteeing that well-typed programs satisfy noninterference. Our prototype implementation, TAP4S, is evaluated on several use cases, demonstrating its effectiveness in detecting security violations and information leakages.

When specifying security policies for databases, it is often natural to formulate disjunctive dependencies, where a piece of information may depend on at most one of two dependencies$P_{1}$or$P_{2}$, but not both. A formal semantic model of such disjunctive dependencies, the Quantale of Information, was recently introduced by Hunt and Sands as a generalization of the Lattice of Information. In this paper, we seek to contribute to the understanding of disjunctive dependencies in database-backed programs and introduce a practical framework to statically enforce disjunctive security policies. To that end, we introduce the Determinacy Quantale, a new query-based structure which captures the ordering of disjunctive information in databases. This structure can be understood as a query-based counterpart to the Quantale of Information. Based on this structure, we design a sound enforcement mechanism to check disjunctive policies for database-backed programs. This mechanism is based on a type-based analysis for a simple imperative language with database queries, which is precise enough to accommodate a variety of row-and column-level database policies flexibly while keeping track of disjunctions due to control flow. We validate our mechanism by implementing it in a tool, Divert, and demonstrate its feasibility on a number of use cases.

Information flow control and dynamic policies is a difficult relationship yet to be fully understood. While dynamic policies are a natural choice in many real-world applications that downgrade and upgrade the sensitivity of information, understanding the meaning of security in this setting is challenging. In this paper we revisit the knowledge-based security conditions to reinstate a simple and intuitive security condition for dynamic policies: A program is secure if at any point during the execution the attacker's knowledge is in accordance with the active security policy at that execution point. Our key observation is the new notion of policy consistency to prevent policy changes whenever an attacker is already in possession of the information that the new policy intends to protect. We use this notion to study a range of realistic attackers including the perfect recall attacker, bounded attackers, and forgetful attackers, and their relationship. Importantly, our new security condition provides a clean connection between the dynamic policy and the underlying attacker model independently of the specific use case. We illustrate this by considering the different facets of dynamic policies in our framework. On the verification side, we design and implement DynCoVer, a tool for checking dynamic information-flow policies for Java programs via symbolic execution and SMT solving. Our verification operates by first extracting a graph of program dependencies and then visiting the graph to check dynamic policies for a range of attackers. We evaluate the effectiveness and efficiency of DyncoVeron a benchmark of use cases from the literature and designed by ourselves, as well as the case study of a social network. The results show that DynCoVer can analyze small but intricate programs indicating that it can help verify security-critical parts of Java applications. We release Dyncover publicly to support open science and encourage researchers to explore the topic further.

Confidential computing is a promising technology for securing code and data-in-use on untrusted host machines, e.g., the cloud. Many hardware vendors offer different implementations of Trusted Execution Environments (TEEs). A TEE is a hardware protected execution environment that allows performing confidential computations over sensitive data on untrusted hosts. Despite the appeal of achieving strong security guarantees against low-level attackers, two challenges hinder the adoption of TEEs. First, developing software in high-level managed languages, e.g., Java or Scala, taking advantage of existing TEEs is complex and error-prone. Second, partitioning an application into components that run inside and outside a TEE may break application-level security policies, resulting in an insecure application when facing a realistic attacker. In this work, we study both these challenges. We present JE, a programming model that seamlessly integrates a TEE, abstracting away low-level programming details such as initialization and loading of data into the TEE. JE only requires developers to add annotations to their programs to enable the execution within the TEE. Drawing on information flow control, we develop a security type system that checks confidentiality and integrity policies against realistic attackers with full control over the code running outside the TEE. We formalize the security type system for the JE core and prove it sound for a semantic characterization of security. We implement JE and the security type system, enable Java programs to run on Intel SGX with strong security guarantees. We evaluate our approach on use cases from the literature, including a battleship game, a secure event processing system, and a popular processing framework for big data, showing that we correctly handle complex cases of partitioning, information flow, declassification, and trust.

A massive multiple-input, multiple-output (mMIMO) downlink is considered with fixed wideband beams known as Grid of Beams (GoBs). The radio channel of a typical urban macro scenario will be shown to be sparse, and in combination with a linear maximum ratio combining beamforming method is used at the user equipment. Simulation results for urban macro cells show that reasonable spectral efficiencies are achieved with a moderate number of relevant channel components (RCCs) and accordingly limited feedback overhead for reporting of channel state information (CSI).

Joint transmission coordinated multipoint (JT CoMP) has been identified as a potential differentiator for future 5G radio systems due to its superior interference mitigation capabilities. Further, the combination with massive multiple-input-multiple-output (mMIMO) when a set of fixed grid of beams is used at eNodeB results in sparse overall channel matrices with a relatively low number of relevant channel components, which reduces the feedback overhead for reporting of channel state information (CSI). Although JT CoMP faces several challenges from synchronization to CSI outdating, in this paper the focus will be on complexity reduction of the precoding over large clustered cells utilizing massive MIMO. It will be derived how the typical sparse number of relevant channel components per user equipment can be exploited to reduce the number of floating point operations (FLOPs) by a factor of ten compared to state-of-the-art solutions for the calculation of the Moore Penrose pseudo inverse of the channel matrix.