Publications by Year

Conferences & Workshops
Anat Bremler-Barr, Hanoch Levy, Michael Czeizler, Jhonatan Tavori
INFOCOM,
2024

Today’s software development landscape has witnessed a shift towards microservices based architectures. Using this approach, large software systems are implemented by combining loosely-coupled services, each responsible for specific task and defined with separate scaling properties.
Auto-scaling is a primary capability of cloud computing which allows systems to adapt to fluctuating traffic loads by dynamically increasing (scale-up) and decreasing (scale-down) the number of resources used.

We observe that when microservices which utilize separate auto-scaling mechanisms operate in tandem to process traffic, they may perform ineffectively, especially under overload conditions, due to DDoS attacks. This can result in throttling (Denial of service — DoS) and over-provisioning of resources (Economic Denial of Sustainability — EDoS).

This paper demonstrates how an attacker can exploit the tandem behavior of microservices with different auto-scaling mechanisms to create an attack we denote as the \emph{Tandem Attack}. We demonstrate the attack on a typical \emph{Serverless} architecture and analyze its economical and performance damages. One intriguing finding is that some attacks may make a cloud customer paying for service denied requests.

We conclude that independent scaling of loosely coupled components might form an inherent difficulty and end-to-end controls might be needed.

Poster and brief announcement
Yehuda Afek, Anat Bremler-Barr, Shani Stajnrod
Usenix Security ,
2023

To fully understand the root cause of the NRDelegationAttack and to analyze its amplification factor, we developed mini- lab setup, disconnected from the Internet, that contains all
the components of the DNS system, a client, a resolver, and authoritative name servers. This setup is built to analyze and examine the behavior of a resolver (or any other component) under the microscope. On the other hand it is not useful for performance analysis (stress analysis).
Here we provide the code and details of this setup enabling to reproduce our analysis. Moreover, researchers may find it useful for farther behavioral analysis and examination of different components in the DNS system.

Conferences & Workshops
Anat Bremler-Barr, David Hay, Bar Meyuhas, Shoham Danino
ACM/IRTF Applied Networking Research Workshop (ANRW),
2023

We explore the impact of device location on the communication endpoints of IoT devices within the context of Manufacturer Usage Description (MUD), an IETF security framework for IoT devices.
Two types of device location are considered: IP-based location, which corresponds to the physical location of the device based on its IP address; and user-defined location, which is chosen during device registration.
Our findings show that IP-based location barely affects the domain set with which IoT devices interact. Conversely, user-defined location drastically changes this set, mainly through region-specific domains that embody location identifiers selected by the user at registration.
We examine these findings’ effects on creating MUD file tools and IoT device identification. As MUD files rely on allowlists of domain allowlists, we show that security appliances supporting MUD need to manage a significantly larger number of MUD rules than initially anticipated. 
To address this challenge, we leverage EDNS Client Subnet (ECS) extension to differentiate user-defined locations without needing regional domains, consequently reducing the number of Access Control Entries (ACEs) required by security appliances.

Poster and brief announcement
Anat Bremler-Barr, Hanoch Levy, Jhonatan Tavori
ACM CoNEXT,
2023

Retry mechanisms are commonly used in microservices architectures as a mechanism for recovering from transit errors, including network failures and service overloading. This research aims at studying the operation of cloud retry mechanisms under deliberated DDoS attacks, and their effect on the application performance and operational costs. In this poster we focus on the economic aspect, and demonstrate that enabling such mechanisms improperly might be counter-productive and expose the system to substantial
and quadratic economical damage in the presence of attacks.

Poster and brief announcement
Anat Bremler-Barr, Michael Czeizler
INFOCOM,
2023

Auto-scaling is a fundamental capability of cloud computing which allows consuming resources dynamically according to changing traffic needed to be served.
By the micro-services architecture paradigm, software systems are built as a set of loosely-coupled applications and services that can be individually scaled.
In this paper, we present a new attack the \emph{Tandem Attack} that exploits the Tandem behavior of micro-services with different scaling properties. Such issues can result in Denial of Service (DoS) and Economic Denial of Sustainability (EDoS) created by malicious attackers or self-inflicted due to wrong configurations set up by administrators. We demonstrate the Tandem attack using a popular AWS serverless infrastructure modeling two services and show that removing servers’ management responsibility from the cloud users does not mitigate the different scaling properties challenge and can even make the problem harder to solve.

Conferences & Workshops
Yehuda Afek, Anat Bremler-Barr, Dor Israeli and Alon Noy
The International Symposium on Cyber Security, Cryptology and Machine Learning (CSCML),
2023

This paper presents a new localhost browser based vulnerability and corresponding attack that opens the door to new attacks on private networks and local devices. We show that this new vulnerability may put hundreds of millions of internet users and their IoT devices at risk. Following the attack presentation, we suggest three new protection mechanisms to mitigate this vulnerability.
This new attack bypasses recently suggested protection mechanisms designed to stop browser-based attacks on private devices and local applications.

Conferences & Workshops
Yehuda Afek, Anat Bremler-Barr, Shani Stajnrod
Usenix Security ,
2023

Malicious actors carrying out distributed denial-of-service (DDoS) attacks are interested in requests that consume a large amount of resources and provide them with ammunition. We present a severe complexity attack on DNS resolvers, where a single malicious query to a DNS resolver can significantly increase its CPU load. Even a few such concurrent queries can result in resource exhaustion and lead to a denial of its service to legitimate clients. This attack is unlike most recent DDoS attacks on DNS servers, which use communication amplification attacks where a single query generates a large number of message exchanges between DNS servers.

The attack described here involves a malicious client whose request to a target resolver is sent to a collaborating malicious authoritative server; this server, in turn, generates a carefully crafted referral response back to the (victim) resolver. The chain reaction of requests continues, leading to the delegation of queries. These ultimately direct the resolver to a server that does not respond to DNS queries. The exchange generates a long sequence of cache and memory accesses that dramatically increase the CPU load on the target resolver. Hence the name non-responsive delegation attack, or NRDelegationAttack.

We demonstrate that three major resolver implementations, BIND9, Unbound, and Knot, are affected by the NRDelegationAttack, and carry out a detailed analysis of the amplification factor on a BIND9 based resolver. As a result of this work, three common vulnerabilities and exposures (CVEs) regarding NRDelegationAttack were issued by these resolver implementations. We also carried out minimal testing on 16 open resolvers, confirming that the attack affects them as well.

Technical reports
Yehuda Afek, Anat Bremler-Barr, Niv Focus,
2023

The objective of this study is to propose an efficient solution for Low-Rate Attacks (LRA), such as scraping attacks that aim to download all the Uniform Resource Identifiers (URIs) of a website. Attackers attempt to evade detection by behaving like regular users while browsing a small set of distinct pages (URI) at small time scales. However, at larger time scales, the attacker becomes a distinct heavy hitter that requests numerous distinct URIs. Although there are several space-efficient and time-efficient methods to detect distinct heavy hitters, they still require excessive memory to track all users over a large time scale. In this research, an innovative streaming algorithm is proposed to detect the attacker.

Poster and brief announcement
Anat Bremler-Barr, Tal Shapira, Daniel Alfasi
Systor,
2023

With the continuous increase in reported Common Vulnerabilities and Exposures (CVEs), security teams are overwhelmed by vast amounts of data, which are often analyzed manually, leading to a slow and inefficient process. To address cybersecurity threats effectively, it is essential to establish connections across multiple security entity databases, including CVEs, Common Weakness Enumeration (CWEs), and Common Attack Pattern Enumeration and Classification (CAPECs). In this study, we introduce a new approach that leverages the RotatE [4] knowledge graph embedding model, initialized with embeddings from Ada language model developed by OpenAI [3]. Additionally, we extend this approach by initializing the embeddings for the relations.

Conferences & Workshops
Anat Bremler-Barr, David Hay, Daniel Bachar
IFIP Networking,
2023

With the advent of cloud and container technologies, enterprises develop applications using a microservices architecture, managed by orchestration systems (e.g. Kubernetes), that group the microservices into clusters. As the number of application setups across multiple clusters and different clouds is increasing, technologies that enable communication and service discovery between the clusters are emerging (mainly as part of the Cloud Native ecosystem).
In such a multi-cluster setting, copies of the same microservice may be deployed in different geo-locations, each with different cost and latency penalties. Yet, current service selection and load balancing mechanisms do not take into account these locations and corresponding penalties.
We present \emph{MCOSS}, a novel solution for optimizing the service selection, given a certain microservice deployment among clouds and clusters in the system. Our solution is agnostic to the different multi-cluster networking layers, cloud vendors, and discovery mechanisms used by the operators. Our simulations show a reduction in outbound traffic cost by up to 72% and response time by up to 64%, compared to the currently-deployed service selection mechanisms.

Conferences & Workshops
Anat Bremler-Barr, Matan Sabag
IFIP Networking,
2022

Distributed denial of service (DDoS) attacks, especially distributed reflection denial of service attacks (DRDoS), have increased dramatically in frequency and volume in recent years. Such attacks are possible due to the attacker’s ability to spoof the source address of IP packets. Since the early days of the internet, authenticating the IP source address has remained unresolved in the real world. Although there are many methods available to eliminate source spoofing, they are not widely used, primarily due to a lack of economic incentives.
We propose a collaborative on-demand route-based defense technique (CORB) to offer efficient DDoS mitigation as a paid-for-service, and efficiently assuage reflector attacks before they reach the reflectors and flood the victim. The technique uses scrubbing facilities located across the internet at internet service providers (ISPs) and internet exchange points (IXPs).
By transmitting a small amount of data based on border gateway protocol (BGP) information from the victim to the scrubbing facilities, we can filter out the attack without any false-positive cases. For example, the data can be sent using DOTS, a new signaling DDoS protocol that was standardized by the IETF. CORB filters the attack before it is amplified by the reflector, thereby reducing the overall cost of the attack. This provides a win-win financial situation for the victim and the scrubbing facilities that provide the service.
We demonstrate the value of CORB by simulating a Memcached DRDoS attack using real-life data. Our evaluation found that deploying CORB on scrubbing facilities at approximately 40 autonomous systems blocks 90% of the attack and can reduce the mitigation cost by 85%.

Conferences & Workshops
Neta Rozen-Schiff, Klaus-Tycho Foerster, Stefan Schmid, David Hay
26th International Conference on Principles of Distributed Systems (OPODIS 2022),
2022

The performance of distributed and data-centric applications often critically depends on the interconnecting network. Emerging reconfigurable datacenter networks (RDCNs) are a particularly innovative approach to improve datacenter throughput. Relying on a dynamic optical topology which can be adjusted towards the workload in a demand-aware manner, RDCNs allow to exploit temporal and spatial locality in the communication pattern, and to provide topological shortcuts for frequently communicating racks. The key challenge, however, concerns how to realize demand-awareness in RDCNs in a scalable fashion.

Conferences & Workshops
Ihab Zhaika and David Hay
IEEE Global Communications Conference (GLOBECOM 2022),
2022

Wi-Fi (IEEE 802.11) is the most-used protocol for wireless internet access on customer premises. The MAC address of each connected device, which used to be static, is being recently randomized (by the device’s operating system) as frequently as daily to prevent tracking and fingerprinting of devices and users. While this feature might be useful in public areas, it disturbs some day-to-day functionalities, such as firewalls, parental control, and similar applications that require a static identifier per device. In this work, we present methods to ensure the functionalities of these applications, even when the MAC address is changed every time the device connects to the network. Our methods work even if the latest MAC randomization techniques are applied and provide these device identifications only to the gateway router. (Potentially malicious) devices that are connected to the same LAN, still see the randomized MAC

Conferences & Workshops
Anat Bremler-Barr, Bar Meyuhas, Ran Shister
IEEE/IFIP NOMS,
2022

Analyzing the network behavior of IoT devices, including which domains, protocols, and ports the device communicates with, is a fundamental challenge for IoT security and identification. Solutions that analyze and manage these areas must be able to learn what constitutes normal device behavior and then extract rules and features to permit only legitimate behavior or identify the device. The Manufacturer Usage Description (MUD) is an IETF white-list protection scheme that formalizes the authorized network behavior in a MUD file; this MUD file can then be used as a type of firewall mechanism.

We demonstrate that learning what is normal behavior for an IoT device is more challenging than expected. In many cases, the same IoT device, with the same firmware, can exhibit different behavior or connect to different domains with different protocols, depending on the device’s geographical location.

Then, we present a technique to generalize MUD files. By processing MUD files that originate in different locations, we can generalize and create a comprehensive MUD file that is applicable for all locations.
To conduct the research, we created MUDIS, a MUD Inspection System tool, that compares and generalizes MUD files. Our open-source MUDIS tool and dataset are available online to researchers and IoT manufacturers, allowing anyone to visualize, compare, and generalize MUD files.

Poster and brief announcement
Anat Bremler-Barr, Bar Meyuhas, Ran Shister
IEEE/IFIP NOMS,
2022

The Manufacturer Usage Description (MUD) is an IETF white-list protection scheme that formalizes the authorized network behavior in a MUD file; this MUD file can then be used as a type of firewall mechanism.

This demo introduces MUDIS, a MUD Inspection System that inspects the network behavior of devices, based on their formal description in the MUD file. We present several use-cases in which MUDIS is useful, including examining the impact of device location, the impact of a firmware update, the correlation of network behavior between different devices of the same manufacture, and more.

MUDIS inspects two MUD files, clusters together and graph- ically visualizes identical, similar, and dissimilar rules. It then calculates a similarity score that measures the similarity between them both. It also generalizes the two MUD files where possible, such that the resulting generalized MUD covers all the permitted (white-list) network behavior for both MUDs.

Our open-source MUDIS tool and proof-of-concept dataset are available for researchers and IoT manufacturers, allowing anyone to gain meaningful insights over the network behavior of IoT devices.

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