While various covert botnets were proposed in the past, they still lack complete anonymization for their servers/botmasters or suffer from slow communication between the botmaster and the bots. In this paper, we first propose a new generation hybrid botnet that covertly and efficiently communicates over Bitcoin Lightning Network (LN), called LNBot. Exploiting various anonymity features of LN, we show the feasibility of a scalable two-layer botnet which completely anonymizes the identity of the botmaster. In the first layer, the botmaster anonymously sends the commands to the command and control (C&C) servers through regular LN payments. Specifically, LNBot allows botmaster's commands to be sent in the form of surreptitious multi-hop LN payments, where the commands are either encoded with the payments or attached to the payments to provide covert communications. In the second layer, C&C servers further relay those commands to the bots in their mini-botnets to launch any type of attacks to victim machines. We further improve on this design by introducing D-LNBot; a distributed version of LNBot that generates its C&C servers by infecting users on the Internet and forms the C&C connections by opening channels to the existing nodes on LN. In contrary to the LNBot, the whole botnet formation phase is distributed and the botmaster is never involved in the process. By utilizing Bitcoin's Testnet and the new message attachment feature of LN, we show that D-LNBot can be run for free and commands are propagated faster to all the C&C servers compared to LNBot. We presented proof-of-concept implementations for both LNBot and D-LNBot on the actual LN and extensively analyzed their delay and cost performance. Finally, we also provide and discuss a list of potential countermeasures to detect LNBot and D-LNBot activities and minimize their impacts.

Bitcoin has emerged as a revolutionary payment system with its decentralized ledger concept; however it has significant problems such as high transaction fees and low throughput. Lightning Network (LN), which was introduced much later, solves most of these problems with an innovative concept called off-chain payments. With this advancement, Bitcoin has become an attractive venue to perform micro-payments which can also be adopted in many IoT applications (e.g., toll payments). Nevertheless, it is not feasible to host LN and Bitcoin on IoT devices due to the storage, memory, and processing restrictions. Therefore, in this paper, we propose a secure and efficient protocol that enables an IoT device to use LN's functions through an untrusted gateway node. Through this gateway which hosts the LN and Bitcoin nodes, the IoT device can open & close LN channels and send & receive LN payments. This delegation approach is powered by a threshold cryptography based scheme that requires the IoT device and the LN gateway to jointly perform all LN operations. Specifically, we propose thresholdizing LN's Bitcoin public and private keys as well as its public and private keys for the new channel states (i.e., commitment points). We prove with a game theoretical security analysis that the IoT device is secure against collusion attacks. We implemented the proposed protocol by changing LN's source code and thoroughly evaluated its performance using several Raspberry Pis. Our evaluation results show that the protocol; is fast, does not bring extra cost overhead, can be run on low data rate wireless networks, is scalable and has negligible energy consumption overhead. To the best of our knowledge, this is the first work that implemented threshold cryptography in LN.

Bitcoin has emerged as a revolutionary payment system with its decentralized ledger concept however it has significant problems such as high transaction fees and long confirmation times. Lightning Network (LN), which was introduced much later, solves most of these problems with an innovative concept called off-chain payments. With this advancement, Bitcoin has become an attractive venue to perform micro-payments which can also be adopted in many IoT applications (e.g. toll payments). Nevertheless, it is not feasible to host LN and Bitcoin on IoT devices due to the storage, memory, and processing requirements. Therefore, in this paper, we propose an efficient and secure protocol that enables an IoT device to use LN through an untrusted gateway node. The gateway hosts LN and Bitcoin nodes and can open & close LN channels, send LN payments on behalf of the IoT device. This delegation approach is powered by a (2,2)-threshold scheme that requires the IoT device and the LN gateway to jointly perform all LN operations which in turn secures both parties' funds. Specifically, we propose to thresholdize LN's Bitcoin public and private keys as well as its commitment points. With these and several other protocol level changes, IoT device is protected against revoked state broadcast, collusion, and ransom attacks. We implemented the proposed protocol by changing LN's source code and thoroughly evaluated its performance using a Raspberry Pi. Our evaluation results show that computational and communication delays associated with the protocol are negligible. To the best of our knowledge, this is the first work that implemented threshold cryptography in LN.

Malicious USB devices can disguise themselves as benign devices (e.g., keyboard, mouse, etc.) to insert malicious commands on end devices. Advanced software-based detection schemes (deeper operating system level) are used to identify the malicious nature of such mimic devices. However, a powerful adversary (e.g., as rootkits or advanced persistent threats) can subvert those software-based detection schemes. To address these concerns, we present our ongoing work to dynamically detect these threats in hardware. Specifically, we utilize a novel hardware-assistance mechanism to collect unaltered USB data at the physical layer which is fed into a machine learning-based classifier to determine the true nature of the USB device.

In this study, the authors discuss the implementation of a low latency decoding algorithm for turbo codes and repeat accumulate codes and compare the implementation results in terms of maximum available clock speed, resource consumption, error correction performance and the data (information bit) rate. In order to decrease the latency a parallellised decoder structure is introduced for these mentioned codes and the results are obtained by implementing the decoders on a field programmable gate array. The memory collision problem is avoided by using collision-free interleavers. Through a proposed quantisation scheme and normalisation in forward/backward recursions, computational issues are handled for overcoming the overflow and underflow issues in a fixed point arithmetic. Also, the effect of different implementation styles are observed.