arXiv subjects

Amr Youssef

Publications and source records attributed to Amr Youssef.

32 records · Page 2Linked to original sources

arXiv2023

An Observer-Based Key Agreement Scheme for Remotely Controlled Mobile Robots

Remotely controlled mobile robots are important examples of Cyber-Physical Systems (CPSs). Recently, these robots are being deployed in many safety critical applications. Therefore, ensuring their cyber-security is of paramount importance. Different control schemes that have been proposed to secure such systems against sophisticated cyber-attacks require the exchange of secret messages between their smart actuators and the remote controller. Thus, these schemes require pre-shared secret keys, or an established Public Key Infrastructure (PKI) that allows for key agreement. Such cryptographic approaches might not always be suitable for the deployment environments of such remotely mobile robots. To address this problem, in this paper, we consider a control theoretic approach for establishing a secret key between the remotely controlled robot and the networked controller without resorting to traditional cryptographic techniques. Our key agreement scheme leverages a nonlinear unknown input observer and an error correction code mechanism to allow the robot to securely agree on a secret key with its remote controller. To validate the proposed scheme, we implement it using a Khepera-IV differential drive robot and evaluate its efficiency and the additional control cost acquired by it. Our experimental results confirm the effectiveness of the proposed key establishment scheme.

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arXiv2023

Learning-Based Detection of Malicious Volt-VAr Control Parameters in Smart Inverters

Distributed Volt-Var Control (VVC) is a widely used control mode of smart inverters. However, necessary VVC curve parameters are remotely communicated to the smart inverter, which opens doors for cyberattacks. If the VVC curves of an inverter are maliciously manipulated, the attacked inverter's reactive power injection will oscillate, causing undesirable voltage oscillations to manifest in the distribution system, which, in turn, threatens the system's stability. In contrast with previous works that proposed methods to mitigate the oscillations after they are already present in the system, this paper presents an intrusion detection method to detect malicious VVC curves once they are communicated to the inverter. The proposed method utilizes a Multi-Layer Perceptron (MLP) that is trained on features extracted from only the local measurements of the inverter. After a smart inverter is equipped with the proposed method, any communicated VVC curve will be verified by the MLP once received. If the curve is found to be malicious, it will be rejected, thus preventing unwanted oscillations beforehand. Otherwise, legitimate curves will be permitted. The performance of the proposed scheme is verified using the 9-bus Canadian urban benchmark distribution system simulated in PSCAD/EMTDC environment. Our results show that the proposed solution can accurately detect malicious VVC curves.

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arXiv2023

Security Weaknesses in IoT Management Platforms

A diverse set of Internet of Things (IoT) devices are becoming an integrated part of daily lives, and playing an increasingly vital role in various industry, enterprise and agricultural settings. The current IoT ecosystem relies on several IoT management platforms to manage and operate a large number of IoT devices, their data, and their connectivity. Considering their key role, these platforms must be properly secured against cyber attacks. In this work, we first explore the core operations/features of leading platforms to design a framework to perform a systematic security evaluation of these platforms. Subsequently, we use our framework to analyze a representative set of 52 IoT management platforms, including 42 web-hosted and 10 locally-deployable platforms. We discover a number of high severity unauthorized access vulnerabilities in 9/52 evaluated IoT management platforms, which could be abused to perform attacks such as remote IoT SIM deactivation, IoT SIM overcharging and IoT device data forgery. More seriously, we also uncover instances of broken authentication in 13/52 platforms, including complete account takeover on 8/52 platforms along with remote code execution on 2/52 platforms. In effect, 17/52 platforms were affected by vulnerabilities that could lead to platform-wide attacks. Overall, vulnerabilities were uncovered in 33 platforms, out of which 28 platforms responded to our responsible disclosure. We were also assigned 11 CVEs and awarded bounty for our findings.

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arXiv2023

Measuring the Leakage and Exploitability of Authentication Secrets in Super-apps: The WeChat Case

We conduct a large-scale measurement of developers' insecure practices leading to mini-app to super-app authentication bypass, among which hard-coding developer secrets for such authentication is a major contributor. We also analyze the exploitability and security consequences of developer secret leakage in mini-apps by examining individual super-app server-side APIs. We develop an analysis framework for measuring such secret leakage, and primarily analyze 110,993 WeChat mini-apps, and 10,000 Baidu mini-apps (two of the most prominent super-app platforms), along with a few more datasets to test the evolution of developer practices and platform security enforcement over time. We found a large number of WeChat mini-apps (36,425, 32.8%) and a few Baidu mini-apps (112) leak their developer secrets, which can cause severe security and privacy problems for the users and developers of mini-apps. A network attacker who does not even have an account on the super-app platform, can effectively take down a mini-app, send malicious and phishing links to users, and access sensitive information of the mini-app developer and its users. We responsibly disclosed our findings and also put forward potential directions that could be considered to alleviate/eliminate the root causes of developers hard-coding the app secrets in the mini-app's front-end code.

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arXiv2022

Blindfold: Keeping Private Keys in PKIs and CDNs out of Sight

Public key infrastructure (PKI) is a certificate-based technology that helps in authenticating systems identities. HTTPS/TLS relies mainly on PKI to minimize fraud over the Internet. Nowadays, websites utilize CDNs to improve user experience, performance, and resilience against cyber attacks. However, combining HTTPS/TLS with CDNs has raised new security challenges. In any PKI system, keeping private keys private is of utmost importance. However, it has become the norm for CDN-powered websites to violate that fundamental assumption. Several solutions have been proposed to make HTTPS CDN-friendly. However, protection of private keys from the very instance of generation; and how they can be made secure against exposure by malicious (CDN) administrators and malware remain unexplored. We utilize trusted execution environments to protect private keys by never exposing them to human operators or untrusted software. We design Blindfold to protect private keys in HTTPS/TLS infrastructures, including CAs, website on-premise servers, and CDNs. We implemented a prototype to assess Blindfold's performance and performed several experiments on both the micro and macro levels. We found that Blindfold slightly outperforms SoftHSM in key generation by 1% while lagging by 0.01% for certificate issuance operations.

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arXiv2022

SAUSAGE: Security Analysis of Unix domain Socket Usage in Android

The Android operating system is currently the most popular mobile operating system in the world. Android is based on Linux and therefore inherits its features including its Inter-Process Communication (IPC) mechanisms. These mechanisms are used by processes to communicate with one another and are extensively used in Android. While Android-specific IPC mechanisms have been studied extensively, Unix domain sockets have not been examined comprehensively, despite playing a crucial role in the IPC of highly privileged system daemons. In this paper, we propose SAUSAGE, an efficient novel static analysis framework to study the security properties of these sockets. SAUSAGE considers access control policies implemented in the Android security model, as well as authentication checks implemented by the daemon binaries. It is a fully static analysis framework, specifically designed to analyze Unix domain socket usage in Android system daemons, at scale. We use this framework to analyze 200 Android images across eight popular smartphone vendors spanning Android versions 7-9. As a result, we uncover multiple access control misconfigurations and insecure authentication checks. Our notable findings include a permission bypass in highly privileged Qualcomm system daemons and an unprotected socket that allows an untrusted app to set the scheduling priority of other processes running on the system, despite the implementation of mandatory SELinux policies. Ultimately, the results of our analysis are worrisome; all vendors except the Android Open Source Project (AOSP) have access control issues, allowing an untrusted app to communicate to highly privileged daemons through Unix domain sockets introduced by hardware manufacturer or vendor customization.

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arXiv2021

LSTM-based approach to detect cyber attacks on market-based congestion management methods

Market-based congestion management methods adopt Demand Side Management (DSM) techniques to alleviate congestion in the day-ahead market. Reliance of these methods on the communication layer makes it prone to cyber attacks affecting the security, reliability, and economic operation of the distribution network. In this paper, we focus on Load Altering Attacks that would compromise the operation of market-based congestion management methods. A detection technique is proposed using Long Short-term Memory (LSTM) Recurrent Neural Networks (RNN). IEEE 33 bus system is used as a case study to demonstrate the effectiveness of the proposed technique. An accuracy of 97% was obtained proving the capability of using LSTM-RNN to detect a load altering cyber attack compromising aggregators in the network.

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arXiv2021

Wyner wiretap-like encoding scheme for cyber-physical systems

In this study, the authors consider the problem of exchanging secrete messages in cyber-physical systems (CPSs) without resorting to cryptographic solutions. In particular, they consider a CPS where the networked controller wants to send a secrete message to the plant. They show that such a problem can be solved by exploiting a Wyner wiretap-like encoding scheme taking advantage of the closed-loop operations typical of feedback control systems. Specifically, by resorting to the control concept of one-step reachable sets, they first show that a wiretap-like encoding scheme exists whenever there is an asymmetry in the plant model knowledge available to control system (the defender) and to the eavesdropper. The effectiveness of the proposed scheme is confirmed by means of a numerical example. Finally, they conclude the study by presenting open design challenges that can be addressed by the research community to improve, in different directions, the secrete message exchange problem in CPSs

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arXiv2021

On Securing Cloud-hosted Cyber-physical Systems Using Trusted Execution Environments

Recently, cloud control systems have gained increasing attention from the research community as a solution to implement networked cyber-physical systems (CPSs). Such an architecture can reduce deployment and maintenance costs albeit at the expense of additional security and privacy concerns. In this paper, first, we discuss state-of-the-art security solutions for cloud control systems and their limitations. Then, we propose a novel control architecture based on Trusted Execution Environments (TEE). We show that such an approach can potentially address major security and privacy issues for cloud-hosted control systems. Finally, we present an implementation setup based on Intel Software Guard Extensions (SGX) and validate its effectiveness on a testbed system.

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arXiv2021

Impact of Electric Vehicles Botnets on the Power Grid

The increased penetration of Electric Vehicles (EVs) in the transportation sector has increased the requirement of Fast Charging Direct Current (FCDC) stations to meet customer's speedy charging requirements. However, both charging stations and EVs connection to the communication infrastructure as well as the power grid makes it vulnerable to cyber attacks. In this paper, the vulnerability of the EV charging process is initially studied. We then show how a botnet of compromised EVs and FCDC stations can be utilized to launch cyber attacks on the power grid resulting in an increase in the load at a specific time. The effect of such attacks on the distribution network in terms of line congestion and voltage limit violations is investigated. Moreover, the effect of the botnet of the transmission network is also studied.

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arXiv2020

Multiple-Association Supporting HTC/MTC in Limited-Backhaul Capacity Ultra-Dense Networks

Coexistence of Human-Type Communications (HTCs) and Machine-Type Communications (MTCs) is inevitable. Ultra-Dense Networks (UDNs) will be efficacious in supporting both types of communications. In a UDN, a massive number of low-power and low-cost Small Cells (SCs) are deployed with density higher than that of the HTC users. In such a scenario, the backhaul capacities constitute an intrinsic bottleneck for the system. Hence, we propose a multiple association scheme where each HTC user associates to and activates multiple SCs to overcome the backhaul capacity constraints. In addition, having more active cells allows for more MTC devices to be supported by the network. Using tools from stochastic geometry, we formulate a novel mathematical framework investigating the performance of the limited-backhaul capacity UDN in terms of Area Spectral Efficiency (ASE) for both HTC and MTC and the density of supported MTC devices. Extensive simulations were conducted to verify the accuracy of the mathematical analysis under different system parameters. Results show the existence of an optimum number of SCs to which an HTC user may connect under backhaul capacity constraints. Besides, the proposed multiple association scheme significantly improves the performance of MTC in terms of both ASE and density of supported devices.

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arXiv2019

On Privacy Risks of Public WiFi Captive Portals

Open access WiFi hotspots are widely deployed in many public places, including restaurants, parks, coffee shops, shopping malls, trains, airports, hotels, and libraries. While these hotspots provide an attractive option to stay connected, they may also track user activities and share user/device information with third-parties, through the use of trackers in their captive portal and landing websites. In this paper, we present a comprehensive privacy analysis of 67 unique public WiFi hotspots located in Montreal, Canada, and shed some light on the web tracking and data collection behaviors of these hotspots. Our study reveals the collection of a significant amount of privacy-sensitive personal data through the use of social login (e.g., Facebook and Google) and registration forms, and many instances of tracking activities, sometimes even before the user accepts the hotspot's privacy and terms of service policies. Most hotspots use persistent third-party tracking cookies within their captive portal site; these cookies can be used to follow the user's browsing behavior long after the user leaves the hotspots, e.g., up to 20 years. Additionally, several hotspots explicitly share (sometimes via HTTP) the collected personal and unique device information with many third-party tracking domains.

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arXiv2018

Playing With Danger: A Taxonomy and Evaluation of Threats to Smart Toys

Smart toys have captured an increasing share of the toy market, and are growing ubiquitous in households with children. Smart toys are a subset of Internet of Things (IoT) devices, containing sensors, actuators, and/or artificial intelligence capabilities. They frequently have internet connectivity, directly or indirectly through companion apps, and collect information about their users and environments. Recent studies have found security flaws in many smart toys that have led to serious privacy leaks, or allowed tracking a child's physical location. Some well-publicized discoveries of this nature have prompted actions from governments around the world to ban some of these toys. Compared to other IoT devices, smart toys pose unique risks because of their easily-vulnerable user base, and our work is intended to define these risks and assess a subset of toys against them. We provide a classification of threats specific to smart toys in order to unite and complement existing adhoc analyses, and help comprehensive evaluation of other smart toys. Our threat classification framework addresses the potential security and privacy flaws that can lead to leakage of private information or allow an adversary to control the toy to lure, harm, or distress a child. Using this framework, we perform a thorough experimental analysis of eleven smart toys and their companion apps. Our systematic analysis has uncovered that several current toys still expose children to multiple threats for attackers with physical, nearby, or remote access to the toy.

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arXiv2018

The Sorry State of TLS Security in Enterprise Interception Appliances

Network traffic inspection, including TLS traffic, in enterprise environments is widely practiced. Reasons for doing so are primarily related to improving enterprise security (e.g., malware detection) and meeting legal requirements. To analyze TLS-encrypted data, network appliances implement a Man-in-the-Middle TLS proxy, by acting as the intended web server to a requesting client (e.g., a browser), and acting as the client to the outside web server. As such, the TLS proxy must implement both a TLS client and a server, and handle a large amount of traffic, preferably, in real-time. However, as protocol and implementation layer vulnerabilities in TLS/HTTPS are quite frequent, these proxies must be, at least, as secure as a modern, up-to-date web browser, and a properly configured web server. As opposed to client-end TLS proxies (e.g., as in several anti-virus products), the proxies in network appliances may serve hundreds to thousands of clients, and any vulnerability in their TLS implementations can significantly downgrade enterprise security. To analyze TLS security of network appliances, we develop a comprehensive framework, by combining and extending tests from existing work on client-end and network-based interception studies. We analyze thirteen representative network appliances over a period of more than a year (including versions before and after notifying affected vendors, a total of 17 versions), and uncover several security issues. For instance, we found that four appliances perform no certificate validation at all, three use pre-generated certificates, and eleven accept certificates signed using MD5, exposing their clients to MITM attacks. Our goal is to highlight the risks introduced by widely-used TLS proxies in enterprise and government environments, potentially affecting many systems hosting security, privacy, and financially sensitive data.

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