Recent research activities are focused on improving Vehicle-to-Vehicle Communication (V2V) based on the 5G Technology. V2V applications are important because they are expected to reduce the risk of accidents up to 80%, enhance traffic management, mitigate congestion, and optimize fuel consumption. Typical autonomous vehicle applications require a high bandwidth transmission channel, so the 5G communication channel might be a reliable solution to support this technology. The dedicated short-range communications (DSRC), characterized by a frequency bandwidth of 5.9 GHz, were used as vehicular connectivity with bandwidth up to 200 mb/s and limited capacity, and it is here utilized for comparison to 5G. The 5G band can support connected autonomous vehicles with higher data rates and larger bandwidth. The 5G communication channel is suitable for vehicular connectivity since it has a very high bandwidth in the millimeter waves spectrum range. The quality of 5G wireless communication channels between connected vehicles is affected by weather conditions such as rain, snow, fog, dust, and sand. In this paper, the effect of dust and sand on the propagation of millimeter waves is presented. The effect of dust and sand on the communication path loss of DSRC and 5G frequency band is investigated in the case of Urban area and Highway condition. Results show that the attenuation caused by dust and sand depends on the particle size of sand,frequency of propagating wave, and concentration of dust. Finally, a new model of link margin is proposed to estimate the effect of dust and sand on DSRC (5.9 GHz) and 5G (28 GHz-73.5 GHz) communication path loss.

Without physical boundaries, a wireless network faces many more vulnerabilities than a wired network does. IEEE 802.16 provides a security sublayer in the MAC layer to address the privacy issues across the fixed BWA (broadband wireless access). Several articles have been published to address the flaws in IEEE 802.16 security after IEEE 802.16-2001 was released. However, even the enhanced version IEEE 802.16-2004 does not settle all the problems and additional flaws emerge. In addition, we found that PKM (privacy and key management) protocols version 2 (PKMv2), proposed by recently released IEEE 802.16e, is also vulnerable to new attacks. In this paper, we first overview the IEEE 802.16 standard, especially the security sublayer, and then investigate possible attacks on the basic PKM protocol in IEEE 802.16 as well as in its other versions from related works and the newest PKMv2. We also give possible solutions to counter those attacks and verify our analysis using formal (BAN) logic.

Advancements in blockchain technology and network technology are bringing in a new era in electronic voting systems. These systems are characterized by enhanced security, efficiency, and accessibility. In this paper, we compose a comparative analysis of blockchain-based electronic voting (e-voting) systems using blockchain technology, cryptographic techniques, counting methods, and security requirements. The core of the analysis involves a detailed examination of blockchain-based electronic voting systems, focusing on the variations in architecture, cryptographic techniques, vote counting methods, and security. We also introduce a novel blockchain-based e-voting system, which integrates advanced methodologies, including the Borda count and Condorcet method, into e-voting systems for improved accuracy and representation in vote tallying. The system’s design features a flexible and amendable blockchain structure, ensuring robustness and security. Practical implementation on a Raspberry Pi 3 Model B+ demonstrates the system’s feasibility and adaptability in diverse environments. Our study of the evolution of e-voting systems and the incorporation of blockchain technology contributes to the development of secure, transparent, and efficient solutions for modern democratic governance.

Real time network monitoring for intrusions is offered by various host and network based intrusion detection systems. These systems largely use signature or pattern matching techniques at the core and thus are ineffective in detecting unknown anomalous activities. In this paper, we apply signal processing techniques in intrusion detection systems, and develop and implement a framework, called Waveman, for real time wavelet-based analysis of network traffic anomalies. Then, we use two metrics, namely percentage deviation and entropy, to evaluate the performance of various wavelet functions on detecting different types of anomalies like denial of service (DoS) attacks and portscans. Our evaluation results show that Coiflet and Paul wavelets perform better than other wavelets in detecting most anomalies considered in this work

Application repackaging is a severe threat to Android users and the market. Not only does it infringe on intellectual property, but it is also one of the most common ways of propagating mobile malware. Existing countermeasures mostly detect repackaging based on app similarity measurement, which tends to be imprecise when obfuscations are applied to repackaged apps. Moreover, they rely on a central party, typically the hosting app store, to perform the detection, but many app stores fail to commit proper effort to piracy detection. We consider building the application repackaging detection capability into apps, such that user devices are made use to detect repackaging in a decentralized fashion. The main challenge is how to protect the detection code from being manipulated by attacks. We propose a creative use of logic bombs, which are otherwise regularly used in malware. The trigger conditions of bombs are constructed to exploit the differences between the attacker and users, such that a bomb that lies dormant on the attacker side will be activated on the user side. The detection code, which is part of the bomb payload, is executed only if the bomb is activated. We introduce cryptographically obfuscated logic bomb to enhance the bomb: (1) the detection code is woven into the neighboring original app code, (2) the mixed code gets encrypted using a key, and (3) the key is deleted from the app and can only be derived when the bomb is activated. Thus, attacks that try to modify or delete the detection code will corrupt the app itself, and searching the key in the application will be in vain. Moreover, we propose a bomb spraying technique that allows many bombs to be injected into an app, multiplying the needed adversary effort for bypassing the detection. In addition to repackaging detection, we present application tampering detection to fight attacks that insert malicious code into repackaged apps. We have implemented a prototype, named BombDroid, that builds repackaging and tampering detection into apps through bytecode instrumentation. The evaluation and the security analysis show that the technique is effective, efficient, and resilient to various bomb analysis techniques including fuzzing, symbolic execution, multi-path exploration, and program slicing. Ethical issues due to the use of logic bombs are also discussed.