A Vehicular Ad-hoc Network (VANET) comprises a group of moving or stationary vehicles connected by a wireless network. VANETs play a vital role in providing safety and comfort to drivers in vehicular environments. They provide smart traffic control and real-time information, event allocation. VANETs have received attention in support of safe driving, intelligent navigation, emergency and entertainment applications in vehicles. Nevertheless, these increasingly linked vehicles pose a range of new safety and security risks to both the host and its associated properties and may even have fatal consequences. Violations of national privacy and vehicle identities are a major obstacle to introducing forced contact protocols in vehicles. Location privacy refers to the privacy of the vehicle (driver) and the location of the vehicle. Whenever a vehicle sends a message, no one but authorized entities should know their real identity and location of the vehicle. All the messages sent by the vehicle must be authenticated before processing, hence location privacy is an important design aspect to be considered in VANETs operations. The novelty of this paper is that it specifically reviews location privacy in VANETs in terms of operational and safety concerns. Furthermore, it presents a critical analysis of various attacks, identity thefts, manipulation and other techniques in vogue for location privacy protection available in state-of-the-art solutions for VANETs. The efforts in this paper will help researchers to develop a great breadth of understanding pertaining to location privacy issues and various security threats encountered by VANETs and present the critical analysis of the available state-of-the- art solutions to maintain location privacy in VANETs.

The privacy preservation has received considerable attention from organizations as the growing population is apprehensive regarding personal data being preserved.There are several privacy and security issues in existing systems, such as identity and location disclosure, availability, and authenticity. Smart parking systems utilize third-party parking recommender systems to offer customized parking space recommendations to its users based on user’s past parking experience. However, indiscriminately sharing a user’s data with a third party recommendation system may violate their personal information because their activity and node mobility can be deduced from their previous paring experience. Another problem with existing solutions is that most distributed systems need a third party to anonymize user data to preserve the user’s privacy. Therefore, this article provides three solutions that address the problems mentioned above; at first, based on elliptic curve cryptography (ECC), we proposed the mutual authentication mechanism using HMAC to provide anonymity and integrity during communication; secondly, given the risks to security and privacy posed by untrustworthy third parties, we used local differential privacy, which uses the Laplace distribution technique to add noise randomly and eliminates any necessity for a third party for data perturbation. And thirdly, in addition to LDP , we utilize the IOTA distributed ledger technology to provide a new level of security that ensures immutability, scalability, and quantum secrecy and decentralized the system. Our experiments demonstrate that, in addition to preserving the driver’s privacy and security, our proposed model has low storage overheads, computation, and communication costs.

There exists a gap between existing security mechanisms and their ability to detect advancing threats. Antivirus and EDR (End Point Detection and Response) aim to detect and prevent threats; such security mechanisms are reactive. This approach did not prove to be effective in protecting against stealthy attacks. SCADA (Supervisory Control and Data Acquisition) security is crucial for any country. However, SCADA is always an easy target for adversaries due to a lack of security for heterogeneous devices. An attack on SCADA is mainly considered a national-level threat. Recent research on SCADA security has not considered “unknown threats,” which has left a gap in security. The proactive approach, such as threat hunting, is the need of the hour. In this research, we investigated that threat hunting in conjunction with cyber deception and kill chain has countervailing effects on detecting SCADA threats and mitigating them. We have used the concept of “decoy farm” in the SCADA network, where all attacks are engaged. Moreover, we present a novel threat detection and prevention approach for SCADA, focusing on unknown threats. To test the effectiveness of approach, we emulated several SCADA, Linux and Windows based attacks on a simulated SCADA network. We have concluded that our approach detects and prevents the attacker before using the current reactive approach and security mechanism for SCADA with enhanced protection for heterogeneous devices. The results and experiments show that the proposed threat hunting approach has significantly improved the threat detection ability.

Cyber-attacks on financial institutions and corporations are on the rise, particularly during pandemics. These attacks are becoming more sophisticated. Reports of hacking activities against government and commercial sector organisations have garnered a lot of attention in the last several years. By design, the focus of Cyber Threat Intelligence (CTI) is exclusively defensive. This is because most of the CTI-derived analysis output is intended to prevent breaches or facilitate early detection. So, there is a need to have a new mechanism for unmasking the attacker. In this research, we demonstrate cyber threat intelligence enrichment with counterintelligence and counterattack combined with certain new methods to exploit the adversary’s vulnerability and fully control the attacker’s system. Attackers use a VPN to establish an anonymous connection. A VPN creates a secure “tunnelling” to the internet, with the VPN server acting as a middleman between the attacker and the web. This provides anonymity because the attacker’s IP address seems to be that of the VPN rather than his own, masking the IP address. So, hackers used this application to create persistence because it is automatically launched each time a computer is restarted. As a result, we are attempting to eliminate the persistence by removing it from the startup and registry. This research will help firms detect and identify an assault in its earliest phases, allowing them to respond accordingly. This project will develop new and innovative strategies to bypass VPNs and other security measures in order to obtain correct source information. Companies will be able to identify new methods by which their systems are penetrated and rapidly harden them. Using counterattack and counterintelligence, a proposed technique can bypass a VPN and get adversarial intel. The main goal of this research is to find the attacker’s footprints or tracks and find out why the attack was planned in the first place.

The ever-growing ecosystem of the Internet of Things (IoT) integrating with the ever-evolving wireless communication technology paves the way for adopting new applications in a smart society. The core concept of smart society emphasizes utilizing information and communication technology (ICT) infrastructure to improve every aspect of life. Among the variety of smart services, eHealth is at the forefront of these promises. eHealth is rapidly gaining popularity to overcome the insufficient healthcare services and provide patient-centric treatment for the rising aging population with chronic diseases. Keeping in view the sensitivity of medical data, this interfacing between healthcare and technology has raised many security concerns. Among the many contemporary solutions, attribute-based encryption (ABE) is the dominant technology because of its inherent support for one-to-many transfer and fine-grained access control mechanisms to confidential medical data. ABE uses costly bilinear pairing operations, which are too heavy for eHealth’s tiny wireless body area network (WBAN) devices despite its proper functionality. We present an efficient and secure ABE architecture with outsourcing intense encryption and decryption operations in this work. For practical realization, our scheme uses elliptic curve scalar point multiplication as the underlying technology of ABE instead of costly pairing operations. In addition, it provides support for attribute/users revocation and verifiability of outsourced medical data. Using the selective-set security model, the proposed scheme is secure under the elliptic curve decisional Diffie–Hellman (ECDDH) assumption. The performance assessment and top-ranked value via the help of fuzzy logic’s evaluation based on distance from average solution (EDAS) method show that the proposed scheme is efficient and suitable for access control in eHealth smart societies.

Attackers compromise organizations with increasingly sophisticated ways, such as Advanced Persistent Threat (APT) attackers. Usually, such attacks have the intention to exploit endpoints to gain access to critical data. For security controls and defense evaluation, organizations may employ offensive security activities. The most important one is penetration testing and red teaming, but such operations are usually resource exhaustive and extend over a longer period of time. Furthermore, traditional Venerability Assessment and Penetration Testing (VAPT) works effectively in the mitigation of known attacks but did not prove to be effective against stealthy attacks. VAPT considers the whole offsec as an acting problem but in reality, an attacker has to deal with uncertainty while conducting real-world attacks. In this paper, we are presenting an adversary emulation approach based on MITRE ATT&CK adversary emulation plan with consideration of planning as a major part of each attack phase. The approach utilizes stealthy attack vectors and paths to emulate adversary for defense evaluation. For effective defense evaluation, we picked more than 40 techniques from ATT&CK, deployed their mitigation on target machines, and then launched attacks against all those techniques. We show that attack paths and payloads generated using our approach are strong enough to evade security controls at endpoints. This approach provides a special environment for cyber defenders to think like adversary, and create new attack vectors and paths to evaluate organizational security preparedness. This process constructs a special environment to expand the attack landscape view and defense evaluation with minimal resources for the organization.