Biblio

With the widespread adoption of Internet of Things (IoT) applications around the world, security related problems become a challenge since the number of cybercrimes that must be identified and investigated increased dramatically. The volume of data generated and handled is immense due to the increased number of IoT applications around the world. As a result, when a cybercrime happens, the volume of digital data needs to be dealt with is massive. Consequently, more effort and time are needed to handle the security issues. As a result, in digital forensics, the analysis phase is an important and challenging phase. This paper proposes a generic proactive model for the cybercrime analysis process in the Internet of Things. The model is focused on the classification of evidences in advance based on its significance and relation to past crimes, as well as the severity of the evidence in terms of the probability occurrence of a cybercrime. This model is supposed to save time and effort during the automated forensic investigation process.

The importance of peer-to-peer (P2P) network overlays produced enormous interest in the research community due to their robustness, scalability, and increase of data availability. P2P networks are overlays of logically connected hosts and other nodes including servers. P2P networks allow users to share their files without the need for any centralized servers. Since P2P networks are largely constructed of end-hosts, they are susceptible to abuse and malicious activity, such as sybil attacks. Impostors perform sybil attacks by assigning nodes multiple addresses, as opposed to a single address, with the goal of degrading network quality. Sybil nodes will spread malicious data and provide bogus responses to requests. To prevent sybil attacks from occurring, a novel defense mechanism is proposed. In the proposed scheme, the DHT key-space is divided and treated in a similar manner to radio frequency allocation incensing. An overlay of trusted nodes is used to detect and handle sybil nodes with the aid of source-destination pairs reporting on each other. The simulation results show that the proposed scheme detects sybil nodes in large sized networks with thousands of interactions.

Since MANETs are infrastructure-less, they heavily use secret sharing techniques to distribute and decentralize the role of a trusted third party, where the MANET secret s is shared among the legitimate nodes using (t, n) threshold secret sharing scheme. For long lived MANETs, the shared secret is periodically updated without changing the MANET secret based on proactive secret sharing using Elliptic Curve Cryptography(ECC). Hence, the adversary trying to learn the secret, needs to gain at-least t partial shares in the same time period. If the time period and the threshold value t are selected properly, proactive verifiable secret sharing can maintain the overall security of the information in long lived MANETs. The conventional cryptographic algorithms are heavy weight, require lot of computation power thus consuming lot of resources. In our proposal we used Elliptic Curve Cryptography to verify commitments as it requires smaller keys compared to existing proactive secret sharing techniques and makes it useful for MANETs, Which are formed of resource constraint devices.