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Register a new userSPARROW: A Novel Covert Communication Scheme Exploiting Broadcast Signals in LTE, 5G & Beyond
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Added by
Reza Soosahabi
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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This work proposes a novel framework to identify and exploit vulnerable MAC layer procedures in commercial wireless technologies for covert communication. Examples of covert communication include data exfiltration, remote command-and-control (CnC) and espionage. In this framework, the SPARROW schemes use the broadcast power of incumbent wireless networks to covertly relay messages across a long distance without connecting to them. This enables the SPARROW schemes to bypass all security and lawful-intercept systems and gain ample advantage over existing covert techniques in terms of maximum anonymity, more miles per Watts and less hardware. The SPARROW schemes can also serve as an efficient solution for long-range M2M applications. This paper details one recently disclosed vulnerability (CVD-2021-0045 in GSMA coordinated vulnerability disclosure program) in the common random-access procedure in the LTE and 5G standards This work also proposes a rigorous remediation for similar access procedures in current and future standards that disrupts the most sophisticated SPARROW schemes with minimal impact on other users.
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The purpose of the covert communication system is to implement the communication process without causing third party perception. In order to achieve complete covert communication, two aspects of security issues need to be considered. The first one is to cover up the existence of information, that is, to ensure the content security of information; the second one is to cover up the behavior of transmitting information, that is, to ensure the behavioral security of communication. However, most of the existing information hiding models are based on the Prisoners Model, which only considers the content security of carriers, while ignoring the behavioral security of the sender and receiver. We think that this is incomplete for the security of covert communication. In this paper, we propose a new covert communication framework, which considers both content security and behavioral security in the process of information transmission. In the experimental part, we analyzed a large amount of collected real Twitter data to illustrate the security risks that may be brought to covert communication if we only consider content security and neglect behavioral security. Finally, we designed a toy experiment, pointing out that in addition to most of the existing content steganography, under the proposed new framework of covert communication, we can also use users behavior to implement behavioral steganography. We hope this new proposed framework will help researchers to design better covert communication systems.
CSI (Channel State Information) of WiFi systems contains the environment channel response between the transmitter and the receiver, so the people/objects and their movement in between can be sensed. To get CSI, the receiver performs channel estimation based on the pre-known training field of the transmitted WiFi signal. CSI related technology is useful in many cases, but it also brings concerns on privacy and security. In this paper, we open sourced a CSI fuzzer to enhance the privacy and security of WiFi CSI applications. It is built and embedded into the transmitter of openwifi, which is an open source full-stack WiFi chip design, to prevent unauthorized sensing without sacrificing the WiFi link performance. The CSI fuzzer imposes an artificial channel response to the signal before it is transmitted, so the CSI seen by the receiver will indicate the actual channel response combined with the artificial response. Only the authorized receiver, that knows the artificial response, can calculate the actual channel response and perform the CSI sensing. Another potential application of the CSI fuzzer is covert channels based on a set of pre-defined artificial response patterns. Our work resolves the pain point of implementing the anti-sensing idea based on the commercial off-the-shelf WiFi devices.
A new scenario for generating a secret key and two private keys among three Terminals in the presence of an external eavesdropper is considered. Terminals 1, 2 and 3 intend to share a common secret key concealed from the external eavesdropper (Terminal 4) and simultaneously, each of Terminals 1 and 2 intends to share a private key with Terminal 3 while keeping it concealed from each other and from Terminal 4. All four Terminals observe i.i.d. outputs of correlated sources and there is a public channel from Terminal 3 to Terminals 1 and 2. An inner bound of the secret key-private keys capacity region is derived and the single letter capacity regions are obtained for some special cases.
With the evolution of WCN (Wireless communication networks), the absolute fulfillment of security occupies the fundamental concern. In view of security, we have identified another research direction based on the attenuation impact of rain in WCN. An approach is initiated by an eavesdropper in which a secure communication environment is degraded by generating Artificial Rain (AR), which creates an abatement in the secrecy rate, and the cybersecurity gets compromised. By doing so, an attacking scenario is perceived, in which an intruder models a Half-Duplex (HD) attack. Half-Duplex specifies the attack on the downlink instead of targeting both uplink and downlink. This allows the attacker to alleviate the miss-rate of the attacking attempts. The layout for the HD attack is explained using RRC (Radio Resource Control)-setup. Further, we have determined and examined the performance parameters such as secrecy rate, energy efficiency, miss-rate, sensitivity in the presence of AR. Further comparison of rural and urban scenarios in the presence and absence of AR is carried out concerning the variation in secrecy rate with respect to the millimeter-wave frequencies and distance. Lastly, the methodology of the HD attack is simulated, revealing that the HD attack maintains a low miss rate with improved performance as compared to the performance and miss-rate attained by the full-duplex attack
This paper presents a novel fingerprinting scheme for the Intellectual Property (IP) protection of Generative Adversarial Networks (GANs). Prior solutions for classification models adopt adversarial examples as the fingerprints, which can raise stealthiness and robustness problems when they are applied to the GAN models. Our scheme constructs a composite deep learning model from the target GAN and a classifier. Then we generate stealthy fingerprint samples from this composite model, and register them to the classifier for effective ownership verification. This scheme inspires three concrete methodologies to practically protect the modern GAN models. Theoretical analysis proves that these methods can satisfy different security requirements necessary for IP protection. We also conduct extensive experiments to show that our solutions outperform existing strategies in terms of stealthiness, functionality-preserving and unremovability.
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