Wireless communication provides unique security challenges, but also enables novel ways to defend against attacks. In the past few years, a number of works discussed the use of friendly jamming to protect the confidentiality of the communicated data as well as to enable message authentication and access control. In this work, we analytically and experimentally evaluate the confidentiality that can be achieved by the use of friendly jamming, given an attacker with multiple receiving antennas. We construct a MIMO-based attack that allows the attacker to recover data protected by friendly jamming and refine the conditions for which this attack is most effective. Our attack shows that friendly jamming cannot provide strong confidentiality guarantees in all settings. We further test our attack in a setting where friendly jamming is used to protect the communication to medical implants.

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Abstract. We consider the classical problem of establishing initial security associations in wireless sensor networks. More specifically, we focus on pre-deployment phase in which sensor nodes have not yet been loaded with shared secrets or other forms of authentic information.In this paper, we propose two novel multichannel protocols for initialization of large scale wireless sensor networks. The first protocol uses only secret key cryptography and is suitable for CPU-constrained sensor nodes. The second protocol is based on public key cryptography. Both protocols involve communication over a bidirectional radio channel and an unidirectional out-of-band visible light channel. A notable feature of the proposed "public key"-based key deployment protocol is that it is designed to be secure in a very strong attacker model, where an attacker can eavesdrop, jam and modify transmitted messages by adding his own message to both a radio and a visible light channel; the attacker however cannot disable the visible light communication channel. We show that many existing protocols that rely on the visible light channel are insecure in this strong adversary model.We implemented the proposed protocols on the Meshnetics wireless sensor platform. The proposed protocols are cheap to implement, secure in the very strong attacker model, easy to use and scalable. We also designed and tested a simple random number generator suitable for sensor platforms.

Many terminals are used in safety-critical operations in which humans, through terminal user interfaces, become a part of the system control loop (e.g., medical and industrial systems). These terminals are typically embedded, single-purpose devices with restricted functionality, sometimes air-gapped and increasingly hardened.We describe a new way of attacking such terminals in which an adversary has only temporary, non-invasive, physical access to the terminal. In this attack, the adversary attaches a small device to the interface that connects user input peripherals to the terminal. The device executes the attack when the authorized user is performing safety-critical operations, by modifying or blocking user input, or injecting new input events.Given that the attacker has access to user input, the execution of this attack might seem trivial. However, to succeed, the attacker needs to overcome a number of challenges including the inability to directly observe the user interface and avoid being detected by the users. We present techniques that allow user interface state and input tracking. We evaluate these techniques and show that they can be implemented efficiently. We further evaluate the effectiveness of our attack through an online user study and find input modification attacks that are hard for the users to detect and would therefore lead to serious violations of the input integrity.

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We show that the new hover (floating touch) technology, available in a number of today's smartphone models, can be abused by malicious Android applications to record all touchscreen input into applications system-wide. Leveraging this attack, a malicious application running on the system is able to capture sensitive input such as passwords and PINs, record all user's social interactions, as well as profile user's behavior. To evaluate our attack we implemented Hoover, a proof-of-concept malicious application that runs in the background and records all input to all foreground applications. We evaluated Hoover with 20 users, across two different Android devices and two input methods, stylus and finger. In the case of touchscreen input by finger, Hoover estimated the positions of users' clicks within an error of 100 pixels and keyboard input with an accuracy of 79%. Hoover captured users' input by stylus even more accurately, estimating users' clicks within 2 pixels and keyboard input with an accuracy of 98%. Differently from existing well-known side channel attacks, this is the first work that proves the security implications of the hover technology and its potential to steal all user inputs with high granularity. We discuss ways of mitigating this attack and show that this cannot be done by simply restricting access to permissions or imposing additional cognitive load on the users since this would significantly constrain the intended use of the hover technology