scholarly journals Digital Immunity Module: Preventing Unwanted Encryption using Source Coding

Author(s):  
Arash Mahboubi ◽  
Keyvan Ansari ◽  
Seyit Camtepe ◽  
Jarek Duda ◽  
Paweł Morawiecki ◽  
...  

Unwanted data encryption, such as ransomware attacks, continues to be a significant cybersecurity threat. Ransomware is a preferred weapon of cybercriminals who target small to large organizations' computer systems and data centres. It is malicious software that infects a victim's computer system and encrypts all its valuable data files. The victim needs to pay a ransom, often in cryptocurrency, in return for a decryption key. Many solutions use methods, including the inspection of file signatures, runtime process behaviors, API calls, and network traffic, to detect ransomware code. However, unwanted data encryption is still a top threat. This paper presents the first immunity solution, called the digital immunity module (DIM). DIM focuses on protecting valuable business-related data files from unwanted encryption rather than detecting malicious codes or processes. We show that methods such as file entropy and fuzzy hashing can be effectively used to sense unwanted encryption on a protected file, triggering our novel source coding method to paralyze the malicious manipulation of data such as ransomware encryption. Specifically, maliciously encrypted data blocks consume exponentially larger space and longer writing time on the DIM-protected file system. As a result, DIM creates enough time for system/human intervention and forensics analysis. Unlike the existing solutions, DIM protects the data regardless of ransomware families and variants. Additionally, DIM can defend against simultaneously active multiple ransomware, including the most recent hard to detect and stop fileless ones. We tested our solution on 39 ransomware families, including the most recent ransomware attacks. DIM successfully defended our sample file dataset (1335 pdf, jpg, and tiff files) against those ransomware attacks with zero file loss.

2022 ◽  
Author(s):  
Arash Mahboubi ◽  
Keyvan Ansari ◽  
Seyit Camtepe ◽  
Jarek Duda ◽  
Paweł Morawiecki ◽  
...  

Unwanted data encryption, such as ransomware attacks, continues to be a significant cybersecurity threat. Ransomware is a preferred weapon of cybercriminals who target small to large organizations' computer systems and data centres. It is malicious software that infects a victim's computer system and encrypts all its valuable data files. The victim needs to pay a ransom, often in cryptocurrency, in return for a decryption key. Many solutions use methods, including the inspection of file signatures, runtime process behaviors, API calls, and network traffic, to detect ransomware code. However, unwanted data encryption is still a top threat. This paper presents the first immunity solution, called the digital immunity module (DIM). DIM focuses on protecting valuable business-related data files from unwanted encryption rather than detecting malicious codes or processes. We show that methods such as file entropy and fuzzy hashing can be effectively used to sense unwanted encryption on a protected file, triggering our novel source coding method to paralyze the malicious manipulation of data such as ransomware encryption. Specifically, maliciously encrypted data blocks consume exponentially larger space and longer writing time on the DIM-protected file system. As a result, DIM creates enough time for system/human intervention and forensics analysis. Unlike the existing solutions, DIM protects the data regardless of ransomware families and variants. Additionally, DIM can defend against simultaneously active multiple ransomware, including the most recent hard to detect and stop fileless ones. We tested our solution on 39 ransomware families, including the most recent ransomware attacks. DIM successfully defended our sample file dataset (1335 pdf, jpg, and tiff files) against those ransomware attacks with zero file loss.


Author(s):  
DECY NATALIANA ◽  
FEBRIAN HADIATNA ◽  
AHMAD FAUZI

ABSTRAKPada penelitian ini mencoba untuk memanfaatkan tag RFID sebagai media untuk menyimpan data berupa nilai nominal uang. Metode enkripsi data Ceasar Cipher akan diterapkan ke dalam sistem yang dirancang sehingga data nominal uang pada tag merupakan data yang terenkripsi. Enkripsi data ini dilakukan untuk memperkuat sistem keamanan yang telah terdapat pada tag, sehingga proses peretasan data akan lebih sulit untuk dilakukan. Perangkat keras yang digunakan untuk merealisasikan sistem terdiri dari unit reader RFID-RC522, tag MIFARE Classic S50 1 kbyte, dan Arduino UNO R3. Dari hasil pengujian diperoleh bahwa tag dapat digunakan untuk menyimpan data berupa nilai nominal uang dan dari sistem yang telah direalisasikan nilai nominal uang tersebut dapat ditambah atau dikurang jumlahnya dari Rp 0 – Rp 4.294.967.295. Penerapan metode Ceasar Cipher berhasil mengubah nilai nominal uang menjadi data yang terenkripsi.Kata Kunci: RFID, pembayaran elektronik, sistem keamanan, enkripsi data, ceasar cipher ABSTRACTIn this research will try to utilize RFID tag as data storage for a certain value of money. Ceasar cipher as encryption method will be applied to the implemented system so that this certain value of money inside the tag turned into an encrypted data. Ecryption of the data is done to hardened the security sistem that already exists in the tag itself, so any violation behavior like data cracking will be harder to accomplish. The hardware that used on the system consist of a reader unit RFID-RC522, MIFARE Classic tag S50 1kbyte, and Arduino UNO R3. The result of this research proofed that the tag could be utilized to store a certain value of money and with a well built implemented system, the data value could be incremented or decremented ranging from Rp 0 – Rp 4.294.967.295. Implementation of Ceasar Cipher method has succesfully turn that certain value of money inside the tag into an encrypted data.Keywords: RFID, Electronic payment, security system, data encryption, ceasar cipher


2019 ◽  
Author(s):  
Jenna E Gallegos ◽  
Diptendu M. Kar ◽  
Indrakshi Ray ◽  
Indrajit Ray ◽  
Jean Peccoud

AbstractSynthetic biology relies on an ever-growing supply chain of synthetic genetic material. Technologies to secure the exchange of this material are still in their infancy. Solutions proposed thus far have focused on watermarks, a dated security approach that can be used to claim authorship, but is subject to counterfeit, and does not provide any information about the integrity of the genetic material itself. We describe how data encryption and digital signature algorithms can be used to ensure the integrity and authenticity of synthetic genetic constructs. Using a pilot software that generates digital signatures and other encrypted data for plasmids, we demonstrate that we can predictably extract information about the author, the identity, and the integrity of plasmid sequences from sequencing data alone without a reference sequence, all without compromising the function of the plasmids. We discuss how this technology can be improved, applied, and expanded to support the new bioeconomy.


2020 ◽  
Vol 4 (1) ◽  
pp. 87
Author(s):  
Zana Thalage Omar ◽  
Fadhil Salman Abed

Fully homomorphic encryption (FHE) reaped the importance and amazement of most researchers and followers in data encryption issues, as programs are allowed to perform arithmetic operations on encrypted data without decrypting it and obtain results similar to the effects of arithmetic operations on unencrypted data. The first (FHE) model was introduced by Craig Gentry in 2009, and it was just theoretical research, but later significant progress was made on it, this research offers FHE system based on directly of factoring big prime numbers which consider open problem now, The proposed scheme offers a fully homomorphic system for data encryption and stores it in encrypted form on the cloud based on a new algorithm that has been tried on a local cloud and compared with two previous encryption systems (RSA and Paillier) and shows us that this algorithm reduces the time of encryption and decryption by 5 times compared to other systems.


Author(s):  
K V Sreelakshmi ◽  
Dileesh E D

Malicious codes have become one of the major threats to computer systems. The malicious software which is also referred to as malware is designed by the attackers and can change their code as they propagate. The existing defense against malware is highly affected by the diversity and volume of malware variants that are being created rapidly. The variants of malware families exhibit typical behavioral patterns exhibiting their origin and purpose. The behavioral patterns can be exploited statically or dynamically to detect and classify malware into their known families. This paper provides a detailed survey of techniques to detect and classify malware into their respective families.


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